https://circa.cs.ualberta.ca/index.php?title=Special:Contributions&feed=atom&target=RechartiCIRCA - User contributions [en]2021-06-15T23:14:56ZFrom CIRCAMediaWiki 1.15.1https://circa.cs.ualberta.ca/index.php/CIRCA:Game_of_WritingCIRCA:Game of Writing2014-01-07T22:06:52Z<p>Recharti: </p>
<hr />
<div>This page gathers '''The Writing Game''' documents<br />
<br />
=== About the Project ===<br />
The Writing Game is a project supported by [http://grand-nce.ca GRAND] that is developing an online writing environment with gamification features. Users can start projects, challenge themselves to meet deadlines, challenge others to finish writing projects, or use writing tactics to complete projects. The Writing Game is being developed by Matt Bouchard. Geoffrey Rockwell is the project director. University of Alberta GRAND researchers who have contributed include: Michael Burden, Joyce Yu, Sean Gouglas, Betsy Sargent and Shannon Lucky. Special thanks to the University of Alberta GRAND team for their ideas and support.<br />
<br />
We are now working on version 2.0 with Roger Graves, Heather Graves, and Ryan Chartier.<br />
<br />
Current location of beta: http://arrl-web002.artsrn.ualberta.ca/gwrit<br />
<br />
Version 1.0 Beta: http://research.artsrn.ualberta.ca/gwrit/<br />
<br />
=== Tutorials and Help ===<br />
* [[CIRCA:TWGTutorial | Simple Tutorial]]<br />
* [[CIRCA:FullTutorial | Full Tutorial]]<br />
<br />
=== Literature and Links ===<br />
* [[CIRCA: Links | Relevant Links]]: Links to similar or relevant projects.<br />
* [[CIRCA: Literature | Literature Review]]: Research literature on gaming and writing.<br />
<br />
==== Google Doc Links====<br />
* [https://docs.google.com/a/ualberta.ca/document/d/1jMZ6RZYMZlaonH7drj21TT0vh01Wf9oITcdHpss_un4/edit Blended Learning Application Draft]<br />
* [https://docs.google.com/a/ualberta.ca/file/d/0B1c_jjRRAn1LV3V3YnVTWkdmRFE/edit Gwrit Five Year Plan]<br />
* [https://docs.google.com/a/ualberta.ca/file/d/0B1c_jjRRAn1LRERLQ2J0X1hQU1E/edit Blended Learning Application Form]<br />
* [https://docs.google.com/a/ualberta.ca/file/d/0B1c_jjRRAn1LUnhqeWFDU3RtZGJaV1Z5aDBvQm1vaEhUNFE0/edit Blended Learning Symposium Notes]<br />
* [https://docs.google.com/a/ualberta.ca/document/d/12e15B2RmiZ3njjVp8hD62iS3td5dGqaiLtT-LTvJ5tk/edit#heading=h.u5l5p8qfnqjk Game of Writing Project Draft]<br />
* [https://docs.google.com/a/ualberta.ca/document/d/1GTbNeM1g3uuw46A5ygiEUu6-OXHRAjPJPW2E5W7lZko/edit Research Question Ideas]<br />
<br />
=== Personas and Scenarios ===<br />
* [[CIRCA: New Personas | New version 2.0 personas]]: A summary of the new personas.<br />
* [[CIRCA: Samila | Samila Writes a Review]]: Samila is a undergraduate student who decides to try this out to write a book review.<br />
* [[CIRCA: John | John's first encounter]]: John is a graduate student who hears about it and decides to give it a try.<br />
* [[CIRCA: Mario-Bowser | Mario and Bowser compete to write a love letter]]: Mario challenges Bowser to write a long love letter to the princess.<br />
* [[CIRCA: PearlWriting | Clarice]]: Clarice uses the Perl Writing Project for a course.<br />
<br />
=== Wireframes ===<br />
<br />
* [[CIRCA: Wireframes1 | Wireframes for Virgil persona]].<br />
* [https://drive.google.com/a/ualberta.ca/file/d/0B-D4JX_uDLdVOUtOeDNyQ3VQZUVuV1hhVzJEVGYwU2RqSjU0/edit?usp=sharing Gwrit wireframes 1]<br />
** Ideas not represented.<br />
*** Collaborative project ownership.<br />
*** Internal private messaging.<br />
*** Internal Chat.<br />
<br />
=== Testing ===<br />
* [[CIRCA: GWrit Tasks | GWrit Tasks]] are the tasks for a Think Aloud test.<br />
* [[CIRCA: Testing Questions | Questions for the Think Aloud assessment]].<br />
<br />
=== Bugs, Features and Other ===<br />
* [[CIRCA: Version 2.0 Feature List | Feature List for Version 2.0]]<br />
* [[CIRCA: FeatureList | Feature List from Matt]]<br />
* [[CIRCA: WritingGameFeatures | Features for Future Consideration]]<br />
* [[CIRCA: OptimalGameExperience | Optimal Game Experience]]<br />
* [[CIRCA: Goals | Goals and Rewards]]<br />
* [[CIRCA: WritingTips | Writing Tips]]<br />
<br />
=== Meeting Notes ===<br />
* [[CIRCA: Aug262011 | August 26th Meeting Notes]]: Meeting notes for The Writing Game.<br />
* [[CIRCA: July152011 | July 15th Meeting Notes]]: Meeting notes for The Writing Game.</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Game_of_WritingCIRCA:Game of Writing2014-01-07T22:00:57Z<p>Recharti: </p>
<hr />
<div>This page gathers '''The Writing Game''' documents<br />
<br />
=== About the Project ===<br />
The Writing Game is a project supported by [http://grand-nce.ca GRAND] that is developing an online writing environment with gamification features. Users can start projects, challenge themselves to meet deadlines, challenge others to finish writing projects, or use writing tactics to complete projects. The Writing Game is being developed by Matt Bouchard. Geoffrey Rockwell is the project director. University of Alberta GRAND researchers who have contributed include: Michael Burden, Joyce Yu, Sean Gouglas, Betsy Sargent and Shannon Lucky. Special thanks to the University of Alberta GRAND team for their ideas and support.<br />
<br />
We are now working on version 2.0 with Roger Graves, Heather Graves, and Ryan Chartier.<br />
<br />
Current location of beta: http://arrl-web002.artsrn.ualberta.ca/gwrit<br />
<br />
Version 1.0 Beta: http://research.artsrn.ualberta.ca/gwrit/<br />
<br />
=== Tutorials and Help ===<br />
* [[CIRCA:TWGTutorial | Simple Tutorial]]<br />
* [[CIRCA:FullTutorial | Full Tutorial]]<br />
<br />
=== Literature and Links ===<br />
* [[CIRCA: Links | Relevant Links]]: Links to similar or relevant projects.<br />
* [[CIRCA: Literature | Literature Review]]: Research literature on gaming and writing.<br />
<br />
==== Google Doc Links====<br />
* [https://docs.google.com/a/ualberta.ca/document/d/1jMZ6RZYMZlaonH7drj21TT0vh01Wf9oITcdHpss_un4/edit Blended Learning Application Draft]<br />
* [https://docs.google.com/a/ualberta.ca/file/d/0B1c_jjRRAn1LV3V3YnVTWkdmRFE/edit Gwrit Five Year Plan]<br />
* [https://docs.google.com/a/ualberta.ca/file/d/0B1c_jjRRAn1LRERLQ2J0X1hQU1E/edit Blended Learning Application Form]<br />
* [https://docs.google.com/a/ualberta.ca/file/d/0B1c_jjRRAn1LUnhqeWFDU3RtZGJaV1Z5aDBvQm1vaEhUNFE0/edit Blended Learning Symposium Notes]<br />
* [https://docs.google.com/a/ualberta.ca/document/d/12e15B2RmiZ3njjVp8hD62iS3td5dGqaiLtT-LTvJ5tk/edit#heading=h.u5l5p8qfnqjk Game of Writing Project Draft]<br />
* [https://docs.google.com/a/ualberta.ca/document/d/1GTbNeM1g3uuw46A5ygiEUu6-OXHRAjPJPW2E5W7lZko/edit Research Question Ideas]<br />
<br />
=== Personas and Scenarios ===<br />
* [[CIRCA: New Personas | New version 2.0 personas]]: A summary of the new personas.<br />
* [[CIRCA: Samila | Samila Writes a Review]]: Samila is a undergraduate student who decides to try this out to write a book review.<br />
* [[CIRCA: John | John's first encounter]]: John is a graduate student who hears about it and decides to give it a try.<br />
* [[CIRCA: Mario-Bowser | Mario and Bowser compete to write a love letter]]: Mario challenges Bowser to write a long love letter to the princess.<br />
* [[CIRCA: PearlWriting | Clarice]]: Clarice uses the Perl Writing Project for a course.<br />
<br />
=== Wireframes ===<br />
<br />
* [[CIRCA: Wireframes1 | Wireframes for Virgil persona]].<br />
* [https://drive.google.com/a/ualberta.ca/file/d/0B-D4JX_uDLdVOUtOeDNyQ3VQZUVuV1hhVzJEVGYwU2RqSjU0/edit?usp=sharing Gwrit wireframes 1]<br />
<br />
=== Testing ===<br />
* [[CIRCA: GWrit Tasks | GWrit Tasks]] are the tasks for a Think Aloud test.<br />
* [[CIRCA: Testing Questions | Questions for the Think Aloud assessment]].<br />
<br />
=== Bugs, Features and Other ===<br />
* [[CIRCA: Version 2.0 Feature List | Feature List for Version 2.0]]<br />
* [[CIRCA: FeatureList | Feature List from Matt]]<br />
* [[CIRCA: WritingGameFeatures | Features for Future Consideration]]<br />
* [[CIRCA: OptimalGameExperience | Optimal Game Experience]]<br />
* [[CIRCA: Goals | Goals and Rewards]]<br />
* [[CIRCA: WritingTips | Writing Tips]]<br />
<br />
=== Meeting Notes ===<br />
* [[CIRCA: Aug262011 | August 26th Meeting Notes]]: Meeting notes for The Writing Game.<br />
* [[CIRCA: July152011 | July 15th Meeting Notes]]: Meeting notes for The Writing Game.</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Game_of_WritingCIRCA:Game of Writing2014-01-07T21:56:56Z<p>Recharti: </p>
<hr />
<div>This page gathers '''The Writing Game''' documents<br />
<br />
=== About the Project ===<br />
The Writing Game is a project supported by [http://grand-nce.ca GRAND] that is developing an online writing environment with gamification features. Users can start projects, challenge themselves to meet deadlines, challenge others to finish writing projects, or use writing tactics to complete projects. The Writing Game is being developed by Matt Bouchard. Geoffrey Rockwell is the project director. University of Alberta GRAND researchers who have contributed include: Michael Burden, Joyce Yu, Sean Gouglas, Betsy Sargent and Shannon Lucky. Special thanks to the University of Alberta GRAND team for their ideas and support.<br />
<br />
We are now working on version 2.0 with Roger Graves, Heather Graves, and Ryan Chartier.<br />
<br />
Current location of beta: http://arrl-web002.artsrn.ualberta.ca/gwrit<br />
<br />
Version 1.0 Beta: http://research.artsrn.ualberta.ca/gwrit/<br />
<br />
=== Tutorials and Help ===<br />
* [[CIRCA:TWGTutorial | Simple Tutorial]]<br />
* [[CIRCA:FullTutorial | Full Tutorial]]<br />
<br />
=== Literature and Links ===<br />
* [[CIRCA: Links | Relevant Links]]: Links to similar or relevant projects.<br />
* [[CIRCA: Literature | Literature Review]]: Research literature on gaming and writing.<br />
<br />
==== Google Doc Links====<br />
* Blended Learning Application Draft - https://docs.google.com/a/ualberta.ca/document/d/1jMZ6RZYMZlaonH7drj21TT0vh01Wf9oITcdHpss_un4/edit<br />
* Gwrit Five Year Plan - https://docs.google.com/a/ualberta.ca/file/d/0B1c_jjRRAn1LV3V3YnVTWkdmRFE/edit<br />
* Blended Learning Application Form - https://docs.google.com/a/ualberta.ca/file/d/0B1c_jjRRAn1LRERLQ2J0X1hQU1E/edit<br />
* Blended Learning Symposium Notes - https://docs.google.com/a/ualberta.ca/file/d/0B1c_jjRRAn1LUnhqeWFDU3RtZGJaV1Z5aDBvQm1vaEhUNFE0/edit<br />
* Game of Writing Project Draft - https://docs.google.com/a/ualberta.ca/document/d/12e15B2RmiZ3njjVp8hD62iS3td5dGqaiLtT-LTvJ5tk/edit#heading=h.u5l5p8qfnqjk<br />
* Research Question Ideas - https://docs.google.com/a/ualberta.ca/document/d/1GTbNeM1g3uuw46A5ygiEUu6-OXHRAjPJPW2E5W7lZko/edit<br />
<br />
=== Personas and Scenarios ===<br />
* [[CIRCA: New Personas | New version 2.0 personas]]: A summary of the new personas.<br />
* [[CIRCA: Samila | Samila Writes a Review]]: Samila is a undergraduate student who decides to try this out to write a book review.<br />
* [[CIRCA: John | John's first encounter]]: John is a graduate student who hears about it and decides to give it a try.<br />
* [[CIRCA: Mario-Bowser | Mario and Bowser compete to write a love letter]]: Mario challenges Bowser to write a long love letter to the princess.<br />
* [[CIRCA: PearlWriting | Clarice]]: Clarice uses the Perl Writing Project for a course.<br />
<br />
=== Wireframes ===<br />
<br />
* [[CIRCA: Wireframes1 | Wireframes for Virgil persona]].<br />
* Gwrit Wireframes version 1 - https://drive.google.com/a/ualberta.ca/file/d/0B-D4JX_uDLdVOUtOeDNyQ3VQZUVuV1hhVzJEVGYwU2RqSjU0/edit?usp=sharing<br />
<br />
=== Testing ===<br />
* [[CIRCA: GWrit Tasks | GWrit Tasks]] are the tasks for a Think Aloud test.<br />
* [[CIRCA: Testing Questions | Questions for the Think Aloud assessment]].<br />
<br />
=== Bugs, Features and Other ===<br />
* [[CIRCA: Version 2.0 Feature List | Feature List for Version 2.0]]<br />
* [[CIRCA: FeatureList | Feature List from Matt]]<br />
* [[CIRCA: WritingGameFeatures | Features for Future Consideration]]<br />
* [[CIRCA: OptimalGameExperience | Optimal Game Experience]]<br />
* [[CIRCA: Goals | Goals and Rewards]]<br />
* [[CIRCA: WritingTips | Writing Tips]]<br />
<br />
=== Meeting Notes ===<br />
* [[CIRCA: Aug262011 | August 26th Meeting Notes]]: Meeting notes for The Writing Game.<br />
* [[CIRCA: July152011 | July 15th Meeting Notes]]: Meeting notes for The Writing Game.</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Game_of_WritingCIRCA:Game of Writing2014-01-07T21:41:52Z<p>Recharti: </p>
<hr />
<div>This page gathers '''The Writing Game''' documents<br />
<br />
=== About the Project ===<br />
The Writing Game is a project supported by [http://grand-nce.ca GRAND] that is developing an online writing environment with gamification features. Users can start projects, challenge themselves to meet deadlines, challenge others to finish writing projects, or use writing tactics to complete projects. The Writing Game is being developed by Matt Bouchard. Geoffrey Rockwell is the project director. University of Alberta GRAND researchers who have contributed include: Michael Burden, Joyce Yu, Sean Gouglas, Betsy Sargent and Shannon Lucky. Special thanks to the University of Alberta GRAND team for their ideas and support.<br />
<br />
We are now working on version 2.0 with Roger Graves, Heather Graves, and Ryan Chartier.<br />
<br />
Current location of beta: http://arrl-web002.artsrn.ualberta.ca/gwrit<br />
<br />
Version 1.0 Beta: http://research.artsrn.ualberta.ca/gwrit/<br />
<br />
=== Tutorials and Help ===<br />
* [[CIRCA:TWGTutorial | Simple Tutorial]]<br />
* [[CIRCA:FullTutorial | Full Tutorial]]<br />
<br />
=== Literature and Links ===<br />
* [[CIRCA: Links | Relevant Links]]: Links to similar or relevant projects.<br />
* [[CIRCA: Literature | Literature Review]]: Research literature on gaming and writing.<br />
<br />
==== Google Doc Links====<br />
* Blended Learning Application Draft - https://docs.google.com/a/ualberta.ca/document/d/1jMZ6RZYMZlaonH7drj21TT0vh01Wf9oITcdHpss_un4/edit<br />
* Gwrit Five Year Plan - https://docs.google.com/a/ualberta.ca/file/d/0B1c_jjRRAn1LV3V3YnVTWkdmRFE/edit<br />
* Blended Learning Application Form - https://docs.google.com/a/ualberta.ca/file/d/0B1c_jjRRAn1LRERLQ2J0X1hQU1E/edit<br />
* Blended Learning Symposium Notes - https://docs.google.com/a/ualberta.ca/file/d/0B1c_jjRRAn1LUnhqeWFDU3RtZGJaV1Z5aDBvQm1vaEhUNFE0/edit<br />
* Game of Writing Project Draft - https://docs.google.com/a/ualberta.ca/document/d/12e15B2RmiZ3njjVp8hD62iS3td5dGqaiLtT-LTvJ5tk/edit#heading=h.u5l5p8qfnqjk<br />
* Research Question Ideas - https://docs.google.com/a/ualberta.ca/document/d/1GTbNeM1g3uuw46A5ygiEUu6-OXHRAjPJPW2E5W7lZko/edit<br />
<br />
=== Personas and Scenarios ===<br />
* [[CIRCA: New Personas | New version 2.0 personas]]: A summary of the new personas.<br />
* [[CIRCA: Samila | Samila Writes a Review]]: Samila is a undergraduate student who decides to try this out to write a book review.<br />
* [[CIRCA: John | John's first encounter]]: John is a graduate student who hears about it and decides to give it a try.<br />
* [[CIRCA: Mario-Bowser | Mario and Bowser compete to write a love letter]]: Mario challenges Bowser to write a long love letter to the princess.<br />
* [[CIRCA: PearlWriting | Clarice]]: Clarice uses the Perl Writing Project for a course.<br />
<br />
=== Wireframes ===<br />
<br />
* [[CIRCA: Wireframes1 | Wireframes for Virgil persona]].<br />
* [[CIRCA: Wireframes2 | Gwrit Wireframes version 1]].<br />
<br />
=== Testing ===<br />
* [[CIRCA: GWrit Tasks | GWrit Tasks]] are the tasks for a Think Aloud test.<br />
* [[CIRCA: Testing Questions | Questions for the Think Aloud assessment]].<br />
<br />
=== Bugs, Features and Other ===<br />
* [[CIRCA: Version 2.0 Feature List | Feature List for Version 2.0]]<br />
* [[CIRCA: FeatureList | Feature List from Matt]]<br />
* [[CIRCA: WritingGameFeatures | Features for Future Consideration]]<br />
* [[CIRCA: OptimalGameExperience | Optimal Game Experience]]<br />
* [[CIRCA: Goals | Goals and Rewards]]<br />
* [[CIRCA: WritingTips | Writing Tips]]<br />
<br />
=== Meeting Notes ===<br />
* [[CIRCA: Aug262011 | August 26th Meeting Notes]]: Meeting notes for The Writing Game.<br />
* [[CIRCA: July152011 | July 15th Meeting Notes]]: Meeting notes for The Writing Game.</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Game_of_WritingCIRCA:Game of Writing2014-01-07T21:39:38Z<p>Recharti: </p>
<hr />
<div>This page gathers '''The Writing Game''' documents<br />
<br />
=== About the Project ===<br />
The Writing Game is a project supported by [http://grand-nce.ca GRAND] that is developing an online writing environment with gamification features. Users can start projects, challenge themselves to meet deadlines, challenge others to finish writing projects, or use writing tactics to complete projects. The Writing Game is being developed by Matt Bouchard. Geoffrey Rockwell is the project director. University of Alberta GRAND researchers who have contributed include: Michael Burden, Joyce Yu, Sean Gouglas, Betsy Sargent and Shannon Lucky. Special thanks to the University of Alberta GRAND team for their ideas and support.<br />
<br />
We are now working on version 2.0 with Roger Graves, Heather Graves, and Ryan Chartier.<br />
<br />
Current location of beta: http://arrl-web002.artsrn.ualberta.ca/gwrit<br />
<br />
Version 1.0 Beta: http://research.artsrn.ualberta.ca/gwrit/<br />
<br />
=== Tutorials and Help ===<br />
* [[CIRCA:TWGTutorial | Simple Tutorial]]<br />
* [[CIRCA:FullTutorial | Full Tutorial]]<br />
<br />
=== Literature and Links ===<br />
* [[CIRCA: Links | Relevant Links]]: Links to similar or relevant projects.<br />
* [[CIRCA: Literature | Literature Review]]: Research literature on gaming and writing.<br />
<br />
==== Google Doc Links====<br />
* Blended Learning Application Draft - https://docs.google.com/a/ualberta.ca/document/d/1jMZ6RZYMZlaonH7drj21TT0vh01Wf9oITcdHpss_un4/edit<br />
* Gwrit Five Year Plan - https://docs.google.com/a/ualberta.ca/file/d/0B1c_jjRRAn1LV3V3YnVTWkdmRFE/edit<br />
* Blended Learning Application Form - https://docs.google.com/a/ualberta.ca/file/d/0B1c_jjRRAn1LRERLQ2J0X1hQU1E/edit<br />
* Blended Learning Symposium Notes - https://docs.google.com/a/ualberta.ca/file/d/0B1c_jjRRAn1LUnhqeWFDU3RtZGJaV1Z5aDBvQm1vaEhUNFE0/edit<br />
* Game of Writing Project Draft - https://docs.google.com/a/ualberta.ca/document/d/12e15B2RmiZ3njjVp8hD62iS3td5dGqaiLtT-LTvJ5tk/edit#heading=h.u5l5p8qfnqjk<br />
* Research Question Ideas - https://docs.google.com/a/ualberta.ca/document/d/1GTbNeM1g3uuw46A5ygiEUu6-OXHRAjPJPW2E5W7lZko/edit<br />
<br />
=== Personas and Scenarios ===<br />
* [[CIRCA: New Personas | New version 2.0 personas]]: A summary of the new personas.<br />
* [[CIRCA: Samila | Samila Writes a Review]]: Samila is a undergraduate student who decides to try this out to write a book review.<br />
* [[CIRCA: John | John's first encounter]]: John is a graduate student who hears about it and decides to give it a try.<br />
* [[CIRCA: Mario-Bowser | Mario and Bowser compete to write a love letter]]: Mario challenges Bowser to write a long love letter to the princess.<br />
* [[CIRCA: PearlWriting | Clarice]]: Clarice uses the Perl Writing Project for a course.<br />
<br />
=== Wireframes ===<br />
<br />
* [[CIRCA: Wireframes1 | Wireframes for Virgil persona]].<br />
<br />
=== Testing ===<br />
* [[CIRCA: GWrit Tasks | GWrit Tasks]] are the tasks for a Think Aloud test.<br />
* [[CIRCA: Testing Questions | Questions for the Think Aloud assessment]].<br />
<br />
=== Bugs, Features and Other ===<br />
* [[CIRCA: Version 2.0 Feature List | Feature List for Version 2.0]]<br />
* [[CIRCA: FeatureList | Feature List from Matt]]<br />
* [[CIRCA: WritingGameFeatures | Features for Future Consideration]]<br />
* [[CIRCA: OptimalGameExperience | Optimal Game Experience]]<br />
* [[CIRCA: Goals | Goals and Rewards]]<br />
* [[CIRCA: WritingTips | Writing Tips]]<br />
<br />
=== Meeting Notes ===<br />
* [[CIRCA: Aug262011 | August 26th Meeting Notes]]: Meeting notes for The Writing Game.<br />
* [[CIRCA: July152011 | July 15th Meeting Notes]]: Meeting notes for The Writing Game.</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Wireframes1CIRCA:Wireframes12013-11-05T21:45:34Z<p>Recharti: </p>
<hr />
<div>[[IMage:Gwrit wireframes 1.jpeg|Wireframe1]]<br />
<br />
[[IMage:Gwrit wireframes 2.jpeg|Wireframe1]]<br />
<br />
[[IMage:Gwrit wireframes 3.jpeg|Wireframe1]]<br />
<br />
[[IMage:Gwrit wireframes 4.jpeg|Wireframe1]]</div>Rechartihttps://circa.cs.ualberta.ca/index.php/File:Gwrit_wireframes_4.jpegFile:Gwrit wireframes 4.jpeg2013-11-05T21:45:27Z<p>Recharti: </p>
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<div></div>Rechartihttps://circa.cs.ualberta.ca/index.php/File:Gwrit_wireframes_3.jpegFile:Gwrit wireframes 3.jpeg2013-11-05T21:45:15Z<p>Recharti: </p>
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<div></div>Rechartihttps://circa.cs.ualberta.ca/index.php/File:Gwrit_wireframes_2.jpegFile:Gwrit wireframes 2.jpeg2013-11-05T21:43:35Z<p>Recharti: </p>
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<div></div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Wireframes1CIRCA:Wireframes12013-11-05T21:43:04Z<p>Recharti: Created page with 'Wireframe1'</p>
<hr />
<div>[[IMage:Gwrit wireframes 1.jpeg|Wireframe1]]</div>Rechartihttps://circa.cs.ualberta.ca/index.php/File:Gwrit_wireframes_1.jpegFile:Gwrit wireframes 1.jpeg2013-11-05T21:39:44Z<p>Recharti: </p>
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<div></div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Game_of_WritingCIRCA:Game of Writing2013-11-05T21:32:07Z<p>Recharti: /* Wireframes */</p>
<hr />
<div>This page gathers '''The Writing Game''' documents<br />
<br />
=== About the Project ===<br />
The Writing Game is a project supported by [http://grand-nce.ca GRAND] that is developing an online writing environment with gamification features. Users can start projects, challenge themselves to meet deadlines, challenge others to finish writing projects, or use writing tactics to complete projects. The Writing Game is being developed by Matt Bouchard. Geoffrey Rockwell is the project director. University of Alberta GRAND researchers who have contributed include: Michael Burden, Joyce Yu, Sean Gouglas, Betsy Sargent and Shannon Lucky. Special thanks to the University of Alberta GRAND team for their ideas and support.<br />
<br />
We are now working on version 2.0 with Roger Graves, Heather Graves, and Ryan Chartier.<br />
<br />
Current location of beta: http://arrl-web002.artsrn.ualberta.ca/gwrit<br />
<br />
Version 1.0 Beta: http://research.artsrn.ualberta.ca/gwrit/<br />
<br />
=== Tutorials and Help ===<br />
* [[CIRCA:TWGTutorial | Simple Tutorial]]<br />
* [[CIRCA:FullTutorial | Full Tutorial]]<br />
<br />
=== Literature and Links ===<br />
* [[CIRCA: Links | Relevant Links]]: Links to similar or relevant projects.<br />
* [[CIRCA: Literature | Literature Review]]: Research literature on gaming and writing.<br />
<br />
=== Personas and Scenarios ===<br />
* [[CIRCA: New Personas | New version 2.0 personas]]: A summary of the new personas.<br />
* [[CIRCA: Samila | Samila Writes a Review]]: Samila is a undergraduate student who decides to try this out to write a book review.<br />
* [[CIRCA: John | John's first encounter]]: John is a graduate student who hears about it and decides to give it a try.<br />
* [[CIRCA: Mario-Bowser | Mario and Bowser compete to write a love letter]]: Mario challenges Bowser to write a long love letter to the princess.<br />
* [[CIRCA: PearlWriting | Clarice]]: Clarice uses the Perl Writing Project for a course.<br />
<br />
=== Wireframes ===<br />
<br />
* [[CIRCA: Wireframes1 | Wireframes for Virgil persona]].<br />
<br />
=== Testing ===<br />
* [[CIRCA: GWrit Tasks | GWrit Tasks]] are the tasks for a Think Aloud test.<br />
* [[CIRCA: Testing Questions | Questions for the Think Aloud assessment]].<br />
<br />
=== Bugs, Features and Other ===<br />
* [[CIRCA: Version 2.0 Feature List | Feature List for Version 2.0]]<br />
* [[CIRCA: FeatureList | Feature List from Matt]]<br />
* [[CIRCA: WritingGameFeatures | Features for Future Consideration]]<br />
* [[CIRCA: OptimalGameExperience | Optimal Game Experience]]<br />
* [[CIRCA: Goals | Goals and Rewards]]<br />
* [[CIRCA: WritingTips | Writing Tips]]<br />
<br />
=== Meeting Notes ===<br />
* [[CIRCA: Aug262011 | August 26th Meeting Notes]]: Meeting notes for The Writing Game.<br />
* [[CIRCA: July152011 | July 15th Meeting Notes]]: Meeting notes for The Writing Game.</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Game_of_WritingCIRCA:Game of Writing2013-11-05T21:27:34Z<p>Recharti: </p>
<hr />
<div>This page gathers '''The Writing Game''' documents<br />
<br />
=== About the Project ===<br />
The Writing Game is a project supported by [http://grand-nce.ca GRAND] that is developing an online writing environment with gamification features. Users can start projects, challenge themselves to meet deadlines, challenge others to finish writing projects, or use writing tactics to complete projects. The Writing Game is being developed by Matt Bouchard. Geoffrey Rockwell is the project director. University of Alberta GRAND researchers who have contributed include: Michael Burden, Joyce Yu, Sean Gouglas, Betsy Sargent and Shannon Lucky. Special thanks to the University of Alberta GRAND team for their ideas and support.<br />
<br />
We are now working on version 2.0 with Roger Graves, Heather Graves, and Ryan Chartier.<br />
<br />
Current location of beta: http://arrl-web002.artsrn.ualberta.ca/gwrit<br />
<br />
Version 1.0 Beta: http://research.artsrn.ualberta.ca/gwrit/<br />
<br />
=== Tutorials and Help ===<br />
* [[CIRCA:TWGTutorial | Simple Tutorial]]<br />
* [[CIRCA:FullTutorial | Full Tutorial]]<br />
<br />
=== Literature and Links ===<br />
* [[CIRCA: Links | Relevant Links]]: Links to similar or relevant projects.<br />
* [[CIRCA: Literature | Literature Review]]: Research literature on gaming and writing.<br />
<br />
=== Personas and Scenarios ===<br />
* [[CIRCA: New Personas | New version 2.0 personas]]: A summary of the new personas.<br />
* [[CIRCA: Samila | Samila Writes a Review]]: Samila is a undergraduate student who decides to try this out to write a book review.<br />
* [[CIRCA: John | John's first encounter]]: John is a graduate student who hears about it and decides to give it a try.<br />
* [[CIRCA: Mario-Bowser | Mario and Bowser compete to write a love letter]]: Mario challenges Bowser to write a long love letter to the princess.<br />
* [[CIRCA: PearlWriting | Clarice]]: Clarice uses the Perl Writing Project for a course.<br />
<br />
=== Wireframes ===<br />
<br />
=== Testing ===<br />
* [[CIRCA: GWrit Tasks | GWrit Tasks]] are the tasks for a Think Aloud test.<br />
* [[CIRCA: Testing Questions | Questions for the Think Aloud assessment]].<br />
<br />
=== Bugs, Features and Other ===<br />
* [[CIRCA: Version 2.0 Feature List | Feature List for Version 2.0]]<br />
* [[CIRCA: FeatureList | Feature List from Matt]]<br />
* [[CIRCA: WritingGameFeatures | Features for Future Consideration]]<br />
* [[CIRCA: OptimalGameExperience | Optimal Game Experience]]<br />
* [[CIRCA: Goals | Goals and Rewards]]<br />
* [[CIRCA: WritingTips | Writing Tips]]<br />
<br />
=== Meeting Notes ===<br />
* [[CIRCA: Aug262011 | August 26th Meeting Notes]]: Meeting notes for The Writing Game.<br />
* [[CIRCA: July152011 | July 15th Meeting Notes]]: Meeting notes for The Writing Game.</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Game_of_WritingCIRCA:Game of Writing2013-11-05T21:23:23Z<p>Recharti: /* About the Project */</p>
<hr />
<div>This page gathers '''The Writing Game''' documents<br />
<br />
=== About the Project ===<br />
The Writing Game is a project supported by [http://grand-nce.ca GRAND] that is developing an online writing environment with gamification features. Users can start projects, challenge themselves to meet deadlines, challenge others to finish writing projects, or use writing tactics to complete projects. The Writing Game is being developed by Matt Bouchard. Geoffrey Rockwell is the project director. University of Alberta GRAND researchers who have contributed include: Michael Burden, Joyce Yu, Sean Gouglas, Betsy Sargent and Shannon Lucky. Special thanks to the University of Alberta GRAND team for their ideas and support.<br />
<br />
We are now working on version 2.0 with Roger Graves, Heather Graves, and Ryan Chartier.<br />
<br />
Current location of beta: http://arrl-web002.artsrn.ualberta.ca/gwrit<br />
<br />
Version 1.0 Beta: http://research.artsrn.ualberta.ca/gwrit/<br />
<br />
=== Tutorials and Help ===<br />
* [[CIRCA:TWGTutorial | Simple Tutorial]]<br />
* [[CIRCA:FullTutorial | Full Tutorial]]<br />
<br />
=== Literature and Links ===<br />
* [[CIRCA: Links | Relevant Links]]: Links to similar or relevant projects.<br />
* [[CIRCA: Literature | Literature Review]]: Research literature on gaming and writing.<br />
<br />
=== Personas and Scenarios ===<br />
* [[CIRCA: New Personas | New version 2.0 personas]]: A summary of the new personas.<br />
* [[CIRCA: Samila | Samila Writes a Review]]: Samila is a undergraduate student who decides to try this out to write a book review.<br />
* [[CIRCA: John | John's first encounter]]: John is a graduate student who hears about it and decides to give it a try.<br />
* [[CIRCA: Mario-Bowser | Mario and Bowser compete to write a love letter]]: Mario challenges Bowser to write a long love letter to the princess.<br />
* [[CIRCA: PearlWriting | Clarice]]: Clarice uses the Perl Writing Project for a course.<br />
<br />
=== Testing ===<br />
* [[CIRCA: GWrit Tasks | GWrit Tasks]] are the tasks for a Think Aloud test.<br />
* [[CIRCA: Testing Questions | Questions for the Think Aloud assessment]].<br />
<br />
=== Bugs, Features and Other ===<br />
* [[CIRCA: Version 2.0 Feature List | Feature List for Version 2.0]]<br />
* [[CIRCA: FeatureList | Feature List from Matt]]<br />
* [[CIRCA: WritingGameFeatures | Features for Future Consideration]]<br />
* [[CIRCA: OptimalGameExperience | Optimal Game Experience]]<br />
* [[CIRCA: Goals | Goals and Rewards]]<br />
* [[CIRCA: WritingTips | Writing Tips]]<br />
<br />
=== Meeting Notes ===<br />
* [[CIRCA: Aug262011 | August 26th Meeting Notes]]: Meeting notes for The Writing Game.<br />
* [[CIRCA: July152011 | July 15th Meeting Notes]]: Meeting notes for The Writing Game.</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Game_of_WritingCIRCA:Game of Writing2013-11-05T21:23:07Z<p>Recharti: /* About the Project */</p>
<hr />
<div>This page gathers '''The Writing Game''' documents<br />
<br />
=== About the Project ===<br />
The Writing Game is a project supported by [http://grand-nce.ca GRAND] that is developing an online writing environment with gamification features. Users can start projects, challenge themselves to meet deadlines, challenge others to finish writing projects, or use writing tactics to complete projects. The Writing Game is being developed by Matt Bouchard. Geoffrey Rockwell is the project director. University of Alberta GRAND researchers who have contributed include: Michael Burden, Joyce Yu, Sean Gouglas, Betsy Sargent and Shannon Lucky. Special thanks to the University of Alberta GRAND team for their ideas and support.<br />
<br />
We are now working on version 2.0 with Roger Graves, Heather Graves, and Ryan Chartier.<br />
<br />
Current location of beta: http://arrl-web002.artsrn.ualberta.ca/gwrit<br />
Version 1.0 Beta: http://research.artsrn.ualberta.ca/gwrit/<br />
<br />
=== Tutorials and Help ===<br />
* [[CIRCA:TWGTutorial | Simple Tutorial]]<br />
* [[CIRCA:FullTutorial | Full Tutorial]]<br />
<br />
=== Literature and Links ===<br />
* [[CIRCA: Links | Relevant Links]]: Links to similar or relevant projects.<br />
* [[CIRCA: Literature | Literature Review]]: Research literature on gaming and writing.<br />
<br />
=== Personas and Scenarios ===<br />
* [[CIRCA: New Personas | New version 2.0 personas]]: A summary of the new personas.<br />
* [[CIRCA: Samila | Samila Writes a Review]]: Samila is a undergraduate student who decides to try this out to write a book review.<br />
* [[CIRCA: John | John's first encounter]]: John is a graduate student who hears about it and decides to give it a try.<br />
* [[CIRCA: Mario-Bowser | Mario and Bowser compete to write a love letter]]: Mario challenges Bowser to write a long love letter to the princess.<br />
* [[CIRCA: PearlWriting | Clarice]]: Clarice uses the Perl Writing Project for a course.<br />
<br />
=== Testing ===<br />
* [[CIRCA: GWrit Tasks | GWrit Tasks]] are the tasks for a Think Aloud test.<br />
* [[CIRCA: Testing Questions | Questions for the Think Aloud assessment]].<br />
<br />
=== Bugs, Features and Other ===<br />
* [[CIRCA: Version 2.0 Feature List | Feature List for Version 2.0]]<br />
* [[CIRCA: FeatureList | Feature List from Matt]]<br />
* [[CIRCA: WritingGameFeatures | Features for Future Consideration]]<br />
* [[CIRCA: OptimalGameExperience | Optimal Game Experience]]<br />
* [[CIRCA: Goals | Goals and Rewards]]<br />
* [[CIRCA: WritingTips | Writing Tips]]<br />
<br />
=== Meeting Notes ===<br />
* [[CIRCA: Aug262011 | August 26th Meeting Notes]]: Meeting notes for The Writing Game.<br />
* [[CIRCA: July152011 | July 15th Meeting Notes]]: Meeting notes for The Writing Game.</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Basic_Statistical_AnalysisCIRCA:Basic Statistical Analysis2013-04-11T04:27:54Z<p>Recharti: /* Rule of Large Numbers */</p>
<hr />
<div><br />
= Basic Statistical Analysis =<br />
<br />
== Definition ==<br />
<br />
==== What are Statistics ====<br />
<br />
Statistics is a quantitative and numerical method that is primarily involved with the collection and interpretation of statistical data. Statistics are frequently used to find relationships between data sets, extracting important properties from data sets, and visualizations.<br />
<br />
As Stats are primarily a numerical method, they only produce facts about the numbers themselves and not the objects under study. A statistical relationship is only as good as the validity of the data being analyzed. A firm understanding of both the statistical method and the numerical interpretations are important in order to get the most out of any statistical analysis.<br />
<br />
== How Statistics Work ==<br />
<br />
Statistics makes a number of very broad assumptions about any data set that is being studied. The most important assumptions will be discussed below.<br />
<br />
==== Random Number ====<br />
<br />
Statistics are generally collected from a representative sample of a larger group of object. Statistics always assumes that each measurement is a single randomly generated value that follows a distribution property associated with the larger group. The most commonly assumed probability distribution is the standard distribution which assumes that most measurements will be close to the classes mean value; variations from the mean are possible but get rarer as distance from the mean increases. One of the main goals of statistics is to find this probability distribution and use it to make inferences about objects outside the representative set. <br />
<br />
There are numerous other mathematical distribution available for study. <br />
<br />
==== Rule of Large Numbers ====<br />
<br />
The rule of large numbers is a simple relationship between the distribution of a sample set, and the distribution of the entire class of objects. In general, larger sample sizes better represent the class as a whole.<br />
<br />
For a dice has an even probability distribution. In theory each side of a dice has equal probability of coming up if rolled. If I were to roll ten dice, then the probability distribution will probably not come up even with some outcomes coming up much more frequently then others. If I were to roll the same dice sixty times, the distribution would be much more even. The rule of large numbers stats that the more I roll the dice, the closer the outcomes will be.<br />
<br />
[[IMage:Dice.png|Dice distribution]]<br />
<br />
==== The P Value ====<br />
<br />
Because statistics makes use of probabilities, there is always a chance that perceived relationships can emerge from data where no relationships actually exists. Most statistical methods will produce a P-value which is effectively the probability of such a coincidence. A low P value indicates a high confidence that the outcome does not represent random fluctuations in the data. High p-values represent low confidence and indicate no relationship beyond simple noise.<br />
<br />
It is important to pick a P value prior to performing any statistical analysis. In general a P value less then 5% is desired; however, for important or sensitive data P values of 1% or lower are generally desired.<br />
<br />
==== Interpreting Correlation ====<br />
<br />
Statistics never produce a causal model of anything that it analyses. A strong statistical relationship between two data sets does not imply that one causes the other. It only implies that one is a good predictor of the other, or that these two values are somehow related. Statistical relationships cannot be used to prove that one object is causally linked to another object; only that these two objects are somehow related.<br />
<br />
==Examples ==<br />
===== T - Test =====<br />
<br />
One statistic useful in text analysis is the average length of word that is used. Similar vocabularies will generally produce similar distributions in the character length of a word. A test for authorship, for example, could assume that all works by the same author would have a similar vocabulary and therfore a similar average word length. T-Tests are a statistical method that compares the mean of two sample sets and asks if these two sets represent the same distribution. <br />
<br />
Using R code (using openNLP package)<br />
<br />
#import two books from project Gutenburg<br />
pride <- scan(file="http://www.gutenberg.org/cache/epub/1342/pg1342.txt", what='char', sep="\n")<br />
flat <- scan(file="http://www.gutenberg.org/cache/epub/97/pg97.txt", what='char', sep="\n")<br />
<br />
#tokenize sentances<br />
pride.sen <- sentDetect(pride)<br />
flat.sen <- sentDetect(flat)<br />
<br />
#get character count for each word<br />
pride.nchar <- nchar(pride.sen)<br />
flat.nchar <- nchar(flat.sen)<br />
<br />
#perform T-test<br />
t.test(pride.nchar, flat.nchar)<br />
<br />
Which produces as output.<br />
<br />
data: pride.nchar and flat.nchar <br />
t = -8.1743, df = 1713.104, p-value = 5.726e-16<br />
alternative hypothesis: true difference in means is not equal to 0 <br />
95 percent confidence interval:<br />
-39.28293 -24.07959 <br />
sample estimates:<br />
mean of x mean of y <br />
125.7389 157.4202 <br />
<br />
The P value in this case is much lower then 1% so there is a strong statistical difference between the average sentance length of 'Pride and Prejudice' and 'Flatland'.<br />
<br />
==References and Further Readings==<br />
<br />
[http://en.wikipedia.org/wiki/Statistics Statistics Wikipedia Article]<br />
<br />
[http://www.r-project.org/ R Project Website]<br />
<br />
[http://www.vassarstats.net/ VassarStats Website]<br />
<br />
[http://www.gutenberg.org/ Project Gutenburg]</div>Rechartihttps://circa.cs.ualberta.ca/index.php/File:Dice.pngFile:Dice.png2013-04-11T04:25:20Z<p>Recharti: </p>
<hr />
<div></div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Basic_Statistical_AnalysisCIRCA:Basic Statistical Analysis2013-04-11T04:24:00Z<p>Recharti: </p>
<hr />
<div><br />
= Basic Statistical Analysis =<br />
<br />
== Definition ==<br />
<br />
==== What are Statistics ====<br />
<br />
Statistics is a quantitative and numerical method that is primarily involved with the collection and interpretation of statistical data. Statistics are frequently used to find relationships between data sets, extracting important properties from data sets, and visualizations.<br />
<br />
As Stats are primarily a numerical method, they only produce facts about the numbers themselves and not the objects under study. A statistical relationship is only as good as the validity of the data being analyzed. A firm understanding of both the statistical method and the numerical interpretations are important in order to get the most out of any statistical analysis.<br />
<br />
== How Statistics Work ==<br />
<br />
Statistics makes a number of very broad assumptions about any data set that is being studied. The most important assumptions will be discussed below.<br />
<br />
==== Random Number ====<br />
<br />
Statistics are generally collected from a representative sample of a larger group of object. Statistics always assumes that each measurement is a single randomly generated value that follows a distribution property associated with the larger group. The most commonly assumed probability distribution is the standard distribution which assumes that most measurements will be close to the classes mean value; variations from the mean are possible but get rarer as distance from the mean increases. One of the main goals of statistics is to find this probability distribution and use it to make inferences about objects outside the representative set. <br />
<br />
There are numerous other mathematical distribution available for study. <br />
<br />
==== Rule of Large Numbers ====<br />
<br />
The rule of large numbers is a simple relationship between the distribution of a sample set, and the distribution of the entire class of objects. In general, larger sample sizes better represent the class as a whole.<br />
<br />
For a dice has an even probability distribution. In theory each side of a dice has equal probability of coming up if rolled. If I were to roll ten dice, then the probability distribution will probably not come up even with some outcomes coming up much more frequently then others. If I were to roll the same dice sixty times, the distribution would be much more even. The rule of large numbers stats that the more I roll the dice, the closer the outcomes will be.<br />
<br />
==== The P Value ====<br />
<br />
Because statistics makes use of probabilities, there is always a chance that perceived relationships can emerge from data where no relationships actually exists. Most statistical methods will produce a P-value which is effectively the probability of such a coincidence. A low P value indicates a high confidence that the outcome does not represent random fluctuations in the data. High p-values represent low confidence and indicate no relationship beyond simple noise.<br />
<br />
It is important to pick a P value prior to performing any statistical analysis. In general a P value less then 5% is desired; however, for important or sensitive data P values of 1% or lower are generally desired.<br />
<br />
==== Interpreting Correlation ====<br />
<br />
Statistics never produce a causal model of anything that it analyses. A strong statistical relationship between two data sets does not imply that one causes the other. It only implies that one is a good predictor of the other, or that these two values are somehow related. Statistical relationships cannot be used to prove that one object is causally linked to another object; only that these two objects are somehow related.<br />
<br />
==Examples ==<br />
===== T - Test =====<br />
<br />
One statistic useful in text analysis is the average length of word that is used. Similar vocabularies will generally produce similar distributions in the character length of a word. A test for authorship, for example, could assume that all works by the same author would have a similar vocabulary and therfore a similar average word length. T-Tests are a statistical method that compares the mean of two sample sets and asks if these two sets represent the same distribution. <br />
<br />
Using R code (using openNLP package)<br />
<br />
#import two books from project Gutenburg<br />
pride <- scan(file="http://www.gutenberg.org/cache/epub/1342/pg1342.txt", what='char', sep="\n")<br />
flat <- scan(file="http://www.gutenberg.org/cache/epub/97/pg97.txt", what='char', sep="\n")<br />
<br />
#tokenize sentances<br />
pride.sen <- sentDetect(pride)<br />
flat.sen <- sentDetect(flat)<br />
<br />
#get character count for each word<br />
pride.nchar <- nchar(pride.sen)<br />
flat.nchar <- nchar(flat.sen)<br />
<br />
#perform T-test<br />
t.test(pride.nchar, flat.nchar)<br />
<br />
Which produces as output.<br />
<br />
data: pride.nchar and flat.nchar <br />
t = -8.1743, df = 1713.104, p-value = 5.726e-16<br />
alternative hypothesis: true difference in means is not equal to 0 <br />
95 percent confidence interval:<br />
-39.28293 -24.07959 <br />
sample estimates:<br />
mean of x mean of y <br />
125.7389 157.4202 <br />
<br />
The P value in this case is much lower then 1% so there is a strong statistical difference between the average sentance length of 'Pride and Prejudice' and 'Flatland'.<br />
<br />
==References and Further Readings==<br />
<br />
[http://en.wikipedia.org/wiki/Statistics Statistics Wikipedia Article]<br />
<br />
[http://www.r-project.org/ R Project Website]<br />
<br />
[http://www.vassarstats.net/ VassarStats Website]<br />
<br />
[http://www.gutenberg.org/ Project Gutenburg]</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Basic_Statistical_AnalysisCIRCA:Basic Statistical Analysis2013-04-11T04:19:03Z<p>Recharti: /* What is Statistics */</p>
<hr />
<div>[This page is not finished.]<br />
<br />
= Basic Statistical Analysis =<br />
<br />
== Definition ==<br />
<br />
==== What are Statistics ====<br />
<br />
Statistics is a quantitative and numerical method that is primarily involved with the collection and interpretation of statistical data. Statistics are frequently used to find relationships between data sets, extracting important properties from data sets, and visualizations.<br />
<br />
As Stats are primarily a numerical method, they only produce facts about the numbers themselves and not the objects under study. A statistical relationship is only as good as the validity of the data being analyzed. A firm understanding of both the statistical method and the numerical interpretations are important in order to get the most out of any statistical analysis.<br />
<br />
== How Statistics Work ==<br />
<br />
Statistics makes a number of very broad assumptions about any data set that is being studied. The most important assumptions will be discussed below.<br />
<br />
==== Random Number ====<br />
<br />
Statistics are generally collected from a representative sample of a larger group of object. Statistics always assumes that each measurement is a single randomly generated value that follows a distribution property associated with the larger group. The most commonly assumed probability distribution is the standard distribution which assumes that most measurements will be close to the classes mean value; variations from the mean are possible but get rarer as distance from the mean increases. One of the main goals of statistics is to find this probability distribution and use it to make inferences about objects outside the representative set. <br />
<br />
There are numerous other mathematical distribution available for study. <br />
<br />
==== Rule of Large Numbers ====<br />
<br />
The rule of large numbers is a simple relationship between the distribution of a sample set, and the distribution of the entire class of objects. In general, larger sample sizes better represent the class as a whole.<br />
<br />
For a dice has an even probability distribution. In theory each side of a dice has equal probability of coming up if rolled. If I were to roll ten dice, then the probability distribution will probably not come up even with some outcomes coming up much more frequently then others. If I were to roll the same dice sixty times, the distribution would be much more even. The rule of large numbers stats that the more I roll the dice, the closer the outcomes will be.<br />
<br />
==== The P Value ====<br />
<br />
Because statistics makes use of probabilities, there is always a chance that perceived relationships can emerge from data where no relationships actually exists. Most statistical methods will produce a P-value which is effectively the probability of such a coincidence. A low P value indicates a high confidence that the outcome does not represent random fluctuations in the data. High p-values represent low confidence and indicate no relationship beyond simple noise.<br />
<br />
It is important to pick a P value prior to performing any statistical analysis. In general a P value less then 5% is desired; however, for important or sensitive data P values of 1% or lower are generally desired.<br />
<br />
==== Interpreting Correlation ====<br />
<br />
Statistics never produce a causal model of anything that it analyses. A strong statistical relationship between two data sets does not imply that one causes the other. It only implies that one is a good predictor of the other, or that these two values are somehow related. Statistical relationships cannot be used to prove that one object is causally linked to another object; only that these two objects are somehow related.<br />
<br />
==Examples ==<br />
===== T - Test =====<br />
<br />
One statistic useful in text analysis is the average length of word that is used. Similar vocabularies will generally produce similar distributions in the character length of a word. A test for authorship, for example, could assume that all works by the same author would have a similar vocabulary and therfore a similar average word length. T-Tests are a statistical method that compares the mean of two sample sets and asks if these two sets represent the same distribution. <br />
<br />
Using R code (using openNLP package)<br />
<br />
#import two books from project Gutenburg<br />
pride <- scan(file="http://www.gutenberg.org/cache/epub/1342/pg1342.txt", what='char', sep="\n")<br />
flat <- scan(file="http://www.gutenberg.org/cache/epub/97/pg97.txt", what='char', sep="\n")<br />
<br />
#tokenize sentances<br />
pride.sen <- sentDetect(pride)<br />
flat.sen <- sentDetect(flat)<br />
<br />
#get character count for each word<br />
pride.nchar <- nchar(pride.sen)<br />
flat.nchar <- nchar(flat.sen)<br />
<br />
#perform T-test<br />
t.test(pride.nchar, flat.nchar)<br />
<br />
Which produces as output.<br />
<br />
data: pride.nchar and flat.nchar <br />
t = -8.1743, df = 1713.104, p-value = 5.726e-16<br />
alternative hypothesis: true difference in means is not equal to 0 <br />
95 percent confidence interval:<br />
-39.28293 -24.07959 <br />
sample estimates:<br />
mean of x mean of y <br />
125.7389 157.4202 <br />
<br />
The P value in this case is much lower then 1% so there is a strong statistical difference between the average sentance length of 'Pride and Prejudice' and 'Flatland'.<br />
<br />
==References and Further Readings==<br />
<br />
[http://en.wikipedia.org/wiki/Statistics Statistics Wikipedia Article]<br />
<br />
[http://www.r-project.org/ R Project Website]<br />
<br />
[http://www.vassarstats.net/ VassarStats Website]<br />
<br />
[http://www.gutenberg.org/ Project Gutenburg]</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Basic_Statistical_AnalysisCIRCA:Basic Statistical Analysis2013-04-11T04:16:25Z<p>Recharti: /* References and Further Readings */</p>
<hr />
<div>[This page is not finished.]<br />
<br />
= Basic Statistical Analysis =<br />
<br />
== Definition ==<br />
<br />
==== What is Statistics ====<br />
<br />
Statistics is a quantitative and numerical method that is primarily involved with the collection and interpretation of statistical data. Statistics are frequently used to find relationships between data sets, extracting important properties from data sets, and visualizations.<br />
<br />
As Stats are primarily a numerical method, they only produce facts about the numbers themselves and not the objects under study. A statistical relationship is only as good as the validity of the data being analyzed. A firm understanding of both the statistical method and the numerical interpretations are important in order to get the most out of any statistical analysis.<br />
<br />
== How Statistics Work ==<br />
<br />
Statistics makes a number of very broad assumptions about any data set that is being studied. The most important assumptions will be discussed below.<br />
<br />
==== Random Number ====<br />
<br />
Statistics are generally collected from a representative sample of a larger group of object. Statistics always assumes that each measurement is a single randomly generated value that follows a distribution property associated with the larger group. The most commonly assumed probability distribution is the standard distribution which assumes that most measurements will be close to the classes mean value; variations from the mean are possible but get rarer as distance from the mean increases. One of the main goals of statistics is to find this probability distribution and use it to make inferences about objects outside the representative set. <br />
<br />
There are numerous other mathematical distribution available for study. <br />
<br />
==== Rule of Large Numbers ====<br />
<br />
The rule of large numbers is a simple relationship between the distribution of a sample set, and the distribution of the entire class of objects. In general, larger sample sizes better represent the class as a whole.<br />
<br />
For a dice has an even probability distribution. In theory each side of a dice has equal probability of coming up if rolled. If I were to roll ten dice, then the probability distribution will probably not come up even with some outcomes coming up much more frequently then others. If I were to roll the same dice sixty times, the distribution would be much more even. The rule of large numbers stats that the more I roll the dice, the closer the outcomes will be.<br />
<br />
==== The P Value ====<br />
<br />
Because statistics makes use of probabilities, there is always a chance that perceived relationships can emerge from data where no relationships actually exists. Most statistical methods will produce a P-value which is effectively the probability of such a coincidence. A low P value indicates a high confidence that the outcome does not represent random fluctuations in the data. High p-values represent low confidence and indicate no relationship beyond simple noise.<br />
<br />
It is important to pick a P value prior to performing any statistical analysis. In general a P value less then 5% is desired; however, for important or sensitive data P values of 1% or lower are generally desired.<br />
<br />
==== Interpreting Correlation ====<br />
<br />
Statistics never produce a causal model of anything that it analyses. A strong statistical relationship between two data sets does not imply that one causes the other. It only implies that one is a good predictor of the other, or that these two values are somehow related. Statistical relationships cannot be used to prove that one object is causally linked to another object; only that these two objects are somehow related.<br />
<br />
==Examples ==<br />
===== T - Test =====<br />
<br />
One statistic useful in text analysis is the average length of word that is used. Similar vocabularies will generally produce similar distributions in the character length of a word. A test for authorship, for example, could assume that all works by the same author would have a similar vocabulary and therfore a similar average word length. T-Tests are a statistical method that compares the mean of two sample sets and asks if these two sets represent the same distribution. <br />
<br />
Using R code (using openNLP package)<br />
<br />
#import two books from project Gutenburg<br />
pride <- scan(file="http://www.gutenberg.org/cache/epub/1342/pg1342.txt", what='char', sep="\n")<br />
flat <- scan(file="http://www.gutenberg.org/cache/epub/97/pg97.txt", what='char', sep="\n")<br />
<br />
#tokenize sentances<br />
pride.sen <- sentDetect(pride)<br />
flat.sen <- sentDetect(flat)<br />
<br />
#get character count for each word<br />
pride.nchar <- nchar(pride.sen)<br />
flat.nchar <- nchar(flat.sen)<br />
<br />
#perform T-test<br />
t.test(pride.nchar, flat.nchar)<br />
<br />
Which produces as output.<br />
<br />
data: pride.nchar and flat.nchar <br />
t = -8.1743, df = 1713.104, p-value = 5.726e-16<br />
alternative hypothesis: true difference in means is not equal to 0 <br />
95 percent confidence interval:<br />
-39.28293 -24.07959 <br />
sample estimates:<br />
mean of x mean of y <br />
125.7389 157.4202 <br />
<br />
The P value in this case is much lower then 1% so there is a strong statistical difference between the average sentance length of 'Pride and Prejudice' and 'Flatland'.<br />
<br />
==References and Further Readings==<br />
<br />
[http://en.wikipedia.org/wiki/Statistics Statistics Wikipedia Article]<br />
<br />
[http://www.r-project.org/ R Project Website]<br />
<br />
[http://www.vassarstats.net/ VassarStats Website]<br />
<br />
[http://www.gutenberg.org/ Project Gutenburg]</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Basic_Statistical_AnalysisCIRCA:Basic Statistical Analysis2013-04-11T04:06:23Z<p>Recharti: /* T - Test */</p>
<hr />
<div>[This page is not finished.]<br />
<br />
= Basic Statistical Analysis =<br />
<br />
== Definition ==<br />
<br />
==== What is Statistics ====<br />
<br />
Statistics is a quantitative and numerical method that is primarily involved with the collection and interpretation of statistical data. Statistics are frequently used to find relationships between data sets, extracting important properties from data sets, and visualizations.<br />
<br />
As Stats are primarily a numerical method, they only produce facts about the numbers themselves and not the objects under study. A statistical relationship is only as good as the validity of the data being analyzed. A firm understanding of both the statistical method and the numerical interpretations are important in order to get the most out of any statistical analysis.<br />
<br />
== How Statistics Work ==<br />
<br />
Statistics makes a number of very broad assumptions about any data set that is being studied. The most important assumptions will be discussed below.<br />
<br />
==== Random Number ====<br />
<br />
Statistics are generally collected from a representative sample of a larger group of object. Statistics always assumes that each measurement is a single randomly generated value that follows a distribution property associated with the larger group. The most commonly assumed probability distribution is the standard distribution which assumes that most measurements will be close to the classes mean value; variations from the mean are possible but get rarer as distance from the mean increases. One of the main goals of statistics is to find this probability distribution and use it to make inferences about objects outside the representative set. <br />
<br />
There are numerous other mathematical distribution available for study. <br />
<br />
==== Rule of Large Numbers ====<br />
<br />
The rule of large numbers is a simple relationship between the distribution of a sample set, and the distribution of the entire class of objects. In general, larger sample sizes better represent the class as a whole.<br />
<br />
For a dice has an even probability distribution. In theory each side of a dice has equal probability of coming up if rolled. If I were to roll ten dice, then the probability distribution will probably not come up even with some outcomes coming up much more frequently then others. If I were to roll the same dice sixty times, the distribution would be much more even. The rule of large numbers stats that the more I roll the dice, the closer the outcomes will be.<br />
<br />
==== The P Value ====<br />
<br />
Because statistics makes use of probabilities, there is always a chance that perceived relationships can emerge from data where no relationships actually exists. Most statistical methods will produce a P-value which is effectively the probability of such a coincidence. A low P value indicates a high confidence that the outcome does not represent random fluctuations in the data. High p-values represent low confidence and indicate no relationship beyond simple noise.<br />
<br />
It is important to pick a P value prior to performing any statistical analysis. In general a P value less then 5% is desired; however, for important or sensitive data P values of 1% or lower are generally desired.<br />
<br />
==== Interpreting Correlation ====<br />
<br />
Statistics never produce a causal model of anything that it analyses. A strong statistical relationship between two data sets does not imply that one causes the other. It only implies that one is a good predictor of the other, or that these two values are somehow related. Statistical relationships cannot be used to prove that one object is causally linked to another object; only that these two objects are somehow related.<br />
<br />
==Examples ==<br />
===== T - Test =====<br />
<br />
One statistic useful in text analysis is the average length of word that is used. Similar vocabularies will generally produce similar distributions in the character length of a word. A test for authorship, for example, could assume that all works by the same author would have a similar vocabulary and therfore a similar average word length. T-Tests are a statistical method that compares the mean of two sample sets and asks if these two sets represent the same distribution. <br />
<br />
Using R code (using openNLP package)<br />
<br />
#import two books from project Gutenburg<br />
pride <- scan(file="http://www.gutenberg.org/cache/epub/1342/pg1342.txt", what='char', sep="\n")<br />
flat <- scan(file="http://www.gutenberg.org/cache/epub/97/pg97.txt", what='char', sep="\n")<br />
<br />
#tokenize sentances<br />
pride.sen <- sentDetect(pride)<br />
flat.sen <- sentDetect(flat)<br />
<br />
#get character count for each word<br />
pride.nchar <- nchar(pride.sen)<br />
flat.nchar <- nchar(flat.sen)<br />
<br />
#perform T-test<br />
t.test(pride.nchar, flat.nchar)<br />
<br />
Which produces as output.<br />
<br />
data: pride.nchar and flat.nchar <br />
t = -8.1743, df = 1713.104, p-value = 5.726e-16<br />
alternative hypothesis: true difference in means is not equal to 0 <br />
95 percent confidence interval:<br />
-39.28293 -24.07959 <br />
sample estimates:<br />
mean of x mean of y <br />
125.7389 157.4202 <br />
<br />
The P value in this case is much lower then 1% so there is a strong statistical difference between the average sentance length of 'Pride and Prejudice' and 'Flatland'.<br />
<br />
==References and Further Readings==</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Basic_Statistical_AnalysisCIRCA:Basic Statistical Analysis2013-04-11T04:05:31Z<p>Recharti: /* Linear Regression */</p>
<hr />
<div>[This page is not finished.]<br />
<br />
= Basic Statistical Analysis =<br />
<br />
== Definition ==<br />
<br />
==== What is Statistics ====<br />
<br />
Statistics is a quantitative and numerical method that is primarily involved with the collection and interpretation of statistical data. Statistics are frequently used to find relationships between data sets, extracting important properties from data sets, and visualizations.<br />
<br />
As Stats are primarily a numerical method, they only produce facts about the numbers themselves and not the objects under study. A statistical relationship is only as good as the validity of the data being analyzed. A firm understanding of both the statistical method and the numerical interpretations are important in order to get the most out of any statistical analysis.<br />
<br />
== How Statistics Work ==<br />
<br />
Statistics makes a number of very broad assumptions about any data set that is being studied. The most important assumptions will be discussed below.<br />
<br />
==== Random Number ====<br />
<br />
Statistics are generally collected from a representative sample of a larger group of object. Statistics always assumes that each measurement is a single randomly generated value that follows a distribution property associated with the larger group. The most commonly assumed probability distribution is the standard distribution which assumes that most measurements will be close to the classes mean value; variations from the mean are possible but get rarer as distance from the mean increases. One of the main goals of statistics is to find this probability distribution and use it to make inferences about objects outside the representative set. <br />
<br />
There are numerous other mathematical distribution available for study. <br />
<br />
==== Rule of Large Numbers ====<br />
<br />
The rule of large numbers is a simple relationship between the distribution of a sample set, and the distribution of the entire class of objects. In general, larger sample sizes better represent the class as a whole.<br />
<br />
For a dice has an even probability distribution. In theory each side of a dice has equal probability of coming up if rolled. If I were to roll ten dice, then the probability distribution will probably not come up even with some outcomes coming up much more frequently then others. If I were to roll the same dice sixty times, the distribution would be much more even. The rule of large numbers stats that the more I roll the dice, the closer the outcomes will be.<br />
<br />
==== The P Value ====<br />
<br />
Because statistics makes use of probabilities, there is always a chance that perceived relationships can emerge from data where no relationships actually exists. Most statistical methods will produce a P-value which is effectively the probability of such a coincidence. A low P value indicates a high confidence that the outcome does not represent random fluctuations in the data. High p-values represent low confidence and indicate no relationship beyond simple noise.<br />
<br />
It is important to pick a P value prior to performing any statistical analysis. In general a P value less then 5% is desired; however, for important or sensitive data P values of 1% or lower are generally desired.<br />
<br />
==== Interpreting Correlation ====<br />
<br />
Statistics never produce a causal model of anything that it analyses. A strong statistical relationship between two data sets does not imply that one causes the other. It only implies that one is a good predictor of the other, or that these two values are somehow related. Statistical relationships cannot be used to prove that one object is causally linked to another object; only that these two objects are somehow related.<br />
<br />
==Examples ==<br />
===== T - Test =====<br />
<br />
One statistic useful in text analysis is the average length of word that is used. Similar vocabularies will generally produce similar distributions in the character length of a word. A test for authorship, for example, could assume that all works by the same author would have a similar vocabulary and therfore a similar average word length. T-Tests are a statistical method that compares the mean of two sample sets and asks if these two sets represent the same distribution. <br />
<br />
Using R code (using openNLP package)<br />
<br />
#import two books from project Gutenburg<br />
pride <- scan(file="http://www.gutenberg.org/cache/epub/1342/pg1342.txt", what='char', sep="\n")<br />
flat <- scan(file="http://www.gutenberg.org/cache/epub/97/pg97.txt", what='char', sep="\n")<br />
<br />
#tokenize sentances<br />
pride.sen <- sentDetect(pride)<br />
flat.sen <- sentDetect(flat)<br />
<br />
#get character count for each word<br />
pride.nchar <- nchar(pride.sen)<br />
flat.nchar <- nchar(flat.sen)<br />
<br />
#perform T-test<br />
t.test(pride.nchar, flat.nchar)<br />
<br />
Which produces as output.<br />
<br />
data: pride.nchar and flat.nchar <br />
t = -8.1743, df = 1713.104, p-value = 5.726e-16<br />
alternative hypothesis: true difference in means is not equal to 0 <br />
95 percent confidence interval:<br />
-39.28293 -24.07959 <br />
sample estimates:<br />
mean of x mean of y <br />
125.7389 157.4202 <br />
<br />
The P value in this case is much lower then 1% so there is a strong statistical difference between the average sentance length of Pride and Prejudice versus Flatland.<br />
<br />
<br />
==References and Further Readings==</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Basic_Statistical_AnalysisCIRCA:Basic Statistical Analysis2013-04-11T04:05:12Z<p>Recharti: </p>
<hr />
<div>[This page is not finished.]<br />
<br />
= Basic Statistical Analysis =<br />
<br />
== Definition ==<br />
<br />
==== What is Statistics ====<br />
<br />
Statistics is a quantitative and numerical method that is primarily involved with the collection and interpretation of statistical data. Statistics are frequently used to find relationships between data sets, extracting important properties from data sets, and visualizations.<br />
<br />
As Stats are primarily a numerical method, they only produce facts about the numbers themselves and not the objects under study. A statistical relationship is only as good as the validity of the data being analyzed. A firm understanding of both the statistical method and the numerical interpretations are important in order to get the most out of any statistical analysis.<br />
<br />
== How Statistics Work ==<br />
<br />
Statistics makes a number of very broad assumptions about any data set that is being studied. The most important assumptions will be discussed below.<br />
<br />
==== Random Number ====<br />
<br />
Statistics are generally collected from a representative sample of a larger group of object. Statistics always assumes that each measurement is a single randomly generated value that follows a distribution property associated with the larger group. The most commonly assumed probability distribution is the standard distribution which assumes that most measurements will be close to the classes mean value; variations from the mean are possible but get rarer as distance from the mean increases. One of the main goals of statistics is to find this probability distribution and use it to make inferences about objects outside the representative set. <br />
<br />
There are numerous other mathematical distribution available for study. <br />
<br />
==== Rule of Large Numbers ====<br />
<br />
The rule of large numbers is a simple relationship between the distribution of a sample set, and the distribution of the entire class of objects. In general, larger sample sizes better represent the class as a whole.<br />
<br />
For a dice has an even probability distribution. In theory each side of a dice has equal probability of coming up if rolled. If I were to roll ten dice, then the probability distribution will probably not come up even with some outcomes coming up much more frequently then others. If I were to roll the same dice sixty times, the distribution would be much more even. The rule of large numbers stats that the more I roll the dice, the closer the outcomes will be.<br />
<br />
==== The P Value ====<br />
<br />
Because statistics makes use of probabilities, there is always a chance that perceived relationships can emerge from data where no relationships actually exists. Most statistical methods will produce a P-value which is effectively the probability of such a coincidence. A low P value indicates a high confidence that the outcome does not represent random fluctuations in the data. High p-values represent low confidence and indicate no relationship beyond simple noise.<br />
<br />
It is important to pick a P value prior to performing any statistical analysis. In general a P value less then 5% is desired; however, for important or sensitive data P values of 1% or lower are generally desired.<br />
<br />
==== Interpreting Correlation ====<br />
<br />
Statistics never produce a causal model of anything that it analyses. A strong statistical relationship between two data sets does not imply that one causes the other. It only implies that one is a good predictor of the other, or that these two values are somehow related. Statistical relationships cannot be used to prove that one object is causally linked to another object; only that these two objects are somehow related.<br />
<br />
==Examples ==<br />
===== T - Test =====<br />
<br />
One statistic useful in text analysis is the average length of word that is used. Similar vocabularies will generally produce similar distributions in the character length of a word. A test for authorship, for example, could assume that all works by the same author would have a similar vocabulary and therfore a similar average word length. T-Tests are a statistical method that compares the mean of two sample sets and asks if these two sets represent the same distribution. <br />
<br />
Using R code (using openNLP package)<br />
<br />
#import two books from project Gutenburg<br />
pride <- scan(file="http://www.gutenberg.org/cache/epub/1342/pg1342.txt", what='char', sep="\n")<br />
flat <- scan(file="http://www.gutenberg.org/cache/epub/97/pg97.txt", what='char', sep="\n")<br />
<br />
#tokenize sentances<br />
pride.sen <- sentDetect(pride)<br />
flat.sen <- sentDetect(flat)<br />
<br />
#get character count for each word<br />
pride.nchar <- nchar(pride.sen)<br />
flat.nchar <- nchar(flat.sen)<br />
<br />
#perform T-test<br />
t.test(pride.nchar, flat.nchar)<br />
<br />
Which produces as output.<br />
<br />
data: pride.nchar and flat.nchar <br />
t = -8.1743, df = 1713.104, p-value = 5.726e-16<br />
alternative hypothesis: true difference in means is not equal to 0 <br />
95 percent confidence interval:<br />
-39.28293 -24.07959 <br />
sample estimates:<br />
mean of x mean of y <br />
125.7389 157.4202 <br />
<br />
The P value in this case is much lower then 1% so there is a strong statistical difference between the average sentance length of Pride and Prejudice versus Flatland.<br />
<br />
<br />
===== Linear Regression =====<br />
<br />
==References and Further Readings==</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Basic_Statistical_AnalysisCIRCA:Basic Statistical Analysis2013-04-11T04:02:34Z<p>Recharti: </p>
<hr />
<div>===== T - Test =====<br />
<br />
One statistic useful in text analysis is the average length of word that is used. Similar vocabularies will generally produce similar distributions in the character length of a word. A test for authorship, for example, could assume that all works by the same author would have a similar vocabulary and therfore a similar average word length. T-Tests are a statistical method that compares the mean of two sample sets and asks if these two sets represent the same distribution. <br />
<br />
Using R code (using openNLP package)<br />
<br />
#import two books from project Gutenburg<br />
pride <- scan(file="http://www.gutenberg.org/cache/epub/1342/pg1342.txt", what='char', sep="\n")<br />
flat <- scan(file="http://www.gutenberg.org/cache/epub/97/pg97.txt", what='char', sep="\n")<br />
<br />
#tokenize sentances<br />
pride.sen <- sentDetect(pride)<br />
flat.sen <- sentDetect(flat)<br />
<br />
#get character count for each word<br />
pride.nchar <- nchar(pride.sen)<br />
flat.nchar <- nchar(flat.sen)<br />
<br />
#perform T-test<br />
t.test(pride.nchar, flat.nchar)<br />
<br />
Which produces as output.<br />
<br />
data: pride.nchar and flat.nchar <br />
t = -8.1743, df = 1713.104, p-value = 5.726e-16<br />
alternative hypothesis: true difference in means is not equal to 0 <br />
95 percent confidence interval:<br />
-39.28293 -24.07959 <br />
sample estimates:<br />
mean of x mean of y <br />
125.7389 157.4202 <br />
<br />
The P value in this case is much lower then 1% so there is a strong statistical difference between the average sentance length of Pride and Prejudice versus Flatland.</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Basic_Statistical_AnalysisCIRCA:Basic Statistical Analysis2013-04-11T03:02:53Z<p>Recharti: /* How Statistics Work */</p>
<hr />
<div>[This page is not finished.]<br />
<br />
= Basic Statistical Analysis =<br />
<br />
== Definition ==<br />
<br />
==== What is Statistics ====<br />
<br />
Statistics is a quantitative and numerical method that is primarily involved with the collection and interpretation of statistical data. Statistics are frequently used to find relationships between data sets, extracting important properties from data sets, and visualizations.<br />
<br />
As Stats are primarily a numerical method, they only produce facts about the numbers themselves and not the objects under study. A statistical relationship is only as good as the validity of the data being analyzed. A firm understanding of both the statistical method and the numerical interpretations are important in order to get the most out of any statistical analysis.<br />
<br />
== How Statistics Work ==<br />
<br />
Statistics makes a number of very broad assumptions about any data set that is being studied. The most important assumptions will be discussed below.<br />
<br />
==== Random Number ====<br />
<br />
Statistics are generally collected from a representative sample of a larger group of object. Statistics always assumes that each measurement is a single randomly generated value that follows a distribution property associated with the larger group. The most commonly assumed probability distribution is the standard distribution which assumes that most measurements will be close to the classes mean value; variations from the mean are possible but get rarer as distance from the mean increases. One of the main goals of statistics is to find this probability distribution and use it to make inferences about objects outside the representative set. <br />
<br />
There are numerous other mathematical distribution available for study. <br />
<br />
==== Rule of Large Numbers ====<br />
<br />
The rule of large numbers is a simple relationship between the distribution of a sample set, and the distribution of the entire class of objects. In general, larger sample sizes better represent the class as a whole.<br />
<br />
For a dice has an even probability distribution. In theory each side of a dice has equal probability of coming up if rolled. If I were to roll ten dice, then the probability distribution will probably not come up even with some outcomes coming up much more frequently then others. If I were to roll the same dice sixty times, the distribution would be much more even. The rule of large numbers stats that the more I roll the dice, the closer the outcomes will be.<br />
<br />
==== The P Value ====<br />
<br />
Because statistics makes use of probabilities, there is always a chance that perceived relationships can emerge from data where no relationships actually exists. Most statistical methods will produce a P-value which is effectively the probability of such a coincidence. A low P value indicates a high confidence that the outcome does not represent random fluctuations in the data. High p-values represent low confidence and indicate no relationship beyond simple noise.<br />
<br />
It is important to pick a P value prior to performing any statistical analysis. In general a P value less then 5% is desired; however, for important or sensitive data P values of 1% or lower are generally desired.<br />
<br />
==== Interpreting Correlation ====<br />
<br />
Statistics never produce a causal model of anything that it analyses. A strong statistical relationship between two data sets does not imply that one causes the other. It only implies that one is a good predictor of the other, or that these two values are somehow related. Statistical relationships cannot be used to prove that one object is causally linked to another object; only that these two objects are somehow related.<br />
<br />
==Examples ==<br />
<br />
===== T - Test =====<br />
<br />
===== Linear Regression =====<br />
<br />
==References and Further Readings==</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Basic_Statistical_AnalysisCIRCA:Basic Statistical Analysis2013-04-11T02:41:22Z<p>Recharti: /* What Statistics is Statistics */</p>
<hr />
<div>[This page is not finished.]<br />
<br />
= Basic Statistical Analysis =<br />
<br />
== Definition ==<br />
<br />
==== What is Statistics ====<br />
<br />
Statistics is a quantitative and numerical method that is primarily involved with the collection and interpretation of statistical data. Statistics are frequently used to find relationships between data sets, extracting important properties from data sets, and visualizations.<br />
<br />
As Stats are primarily a numerical method, they only produce facts about the numbers themselves and not the objects under study. A statistical relationship is only as good as the validity of the data being analyzed. A firm understanding of both the statistical method and the numerical interpretations are important in order to get the most out of any statistical analysis.<br />
<br />
== How Statistics Work ==<br />
<br />
Statistics makes a number of very broad assumptions about any data set that is being studied. The most important assumptions will be discussed below.<br />
<br />
==== Random Number ====<br />
<br />
Statistics assumes that all measurments are random. The true measurement of any numerical value is not a specific value but instead follows some form of probability distribution. In the general case, the standard distribution is assumed; however, there are numerous other mathematical distributions available for comparison. <br />
<br />
==== Rule of Large Numbers ====<br />
<br />
Statistics are generally collected for a subset of the group of objects under study. For example, as it is nearly impossible to collect data on every book ever written, a representative subset can be studied instead. Any subset of a larger dataset will not accuratly represent the true distribution of data.<br />
<br />
The Rule of large numbers governs the relationship between subsets and data sets. It states that the larger the subset the more accuratly the distribution of the subset will reflect the larger set. For example, rolling a six sided dice sixty times will produce a distribution closer to the actual distribution then simply rolling the same dice ten times.<br />
<br />
==== The P Value ====<br />
<br />
Because statistics makes use of probabilities, there is allways a chance that percived relationships can emerge from data where no relationship actually exists. Most statistical methods will produce a P value which is effectivly the probability of such a coincodence. A low P value indicates a high probability that there is real relationship in the data while a high P value indicates that any percived relationship is probobly due to random fluctuations in the data. <br />
<br />
It is important to pick a P value prior to performing any statistical analysis. In general a P value less then 5% is desired; however, for important or sensative data P values lower then 1% and lower are generally desired.<br />
<br />
==== Interpreting Corelation ====<br />
<br />
A strong statistical relationship between two data sets does not imply that one causes the other. It only implies that one is a good predictor of the other, or that these two values are somehow related. Statistical relationships cannot be used to prove that one object is causally linked to another object; only that these two objects have a relationship that merits further study.<br />
<br />
==Examples ==<br />
<br />
===== T - Test =====<br />
<br />
===== Linear Regression =====<br />
<br />
==References and Further Readings==</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Basic_Statistical_AnalysisCIRCA:Basic Statistical Analysis2013-04-03T06:47:52Z<p>Recharti: </p>
<hr />
<div>[This page is not finished.]<br />
<br />
= Basic Statistical Analysis =<br />
<br />
== Definition ==<br />
<br />
==== What Statistics is Statistics ====<br />
<br />
Statistics involve both the collection of data, and numerous methods for analyzing and interpreting the data. Statistics is useful for infering relationship between data sets, extracting properties from data sets, and visualizing patterns in data sets.<br />
<br />
Those involved in Statistics should be careful to note that the relationship between statistical fact and facts about the objects under study is only as good as the relationship between the data set and the objects under study. Statistics never produces facts about the objects directly and only analyses the data under study. Statistical analysis is just as biased as the data being analysed, yet this bias is difficult to see from the perspective of someone without a firm understanding of the method of statistical analysis. <br />
<br />
== How Statistics Work ==<br />
<br />
Statistics makes a number of very broad assumptions about any data set that is being studied. The most important assumptions will be discussed below.<br />
<br />
==== Random Number ====<br />
<br />
Statistics assumes that all measurments are random. The true measurement of any numerical value is not a specific value but instead follows some form of probability distribution. In the general case, the standard distribution is assumed; however, there are numerous other mathematical distributions available for comparison. <br />
<br />
==== Rule of Large Numbers ====<br />
<br />
Statistics are generally collected for a subset of the group of objects under study. For example, as it is nearly impossible to collect data on every book ever written, a representative subset can be studied instead. Any subset of a larger dataset will not accuratly represent the true distribution of data.<br />
<br />
The Rule of large numbers governs the relationship between subsets and data sets. It states that the larger the subset the more accuratly the distribution of the subset will reflect the larger set. For example, rolling a six sided dice sixty times will produce a distribution closer to the actual distribution then simply rolling the same dice ten times.<br />
<br />
==== The P Value ====<br />
<br />
Because statistics makes use of probabilities, there is allways a chance that percived relationships can emerge from data where no relationship actually exists. Most statistical methods will produce a P value which is effectivly the probability of such a coincodence. A low P value indicates a high probability that there is real relationship in the data while a high P value indicates that any percived relationship is probobly due to random fluctuations in the data. <br />
<br />
It is important to pick a P value prior to performing any statistical analysis. In general a P value less then 5% is desired; however, for important or sensative data P values lower then 1% and lower are generally desired.<br />
<br />
==== Interpreting Corelation ====<br />
<br />
A strong statistical relationship between two data sets does not imply that one causes the other. It only implies that one is a good predictor of the other, or that these two values are somehow related. Statistical relationships cannot be used to prove that one object is causally linked to another object; only that these two objects have a relationship that merits further study.<br />
<br />
==Examples ==<br />
<br />
===== T - Test =====<br />
<br />
===== Linear Regression =====<br />
<br />
==References and Further Readings==</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Basic_Statistical_AnalysisCIRCA:Basic Statistical Analysis2013-04-03T06:47:21Z<p>Recharti: </p>
<hr />
<div>= Basic Statistical Analysis =<br />
<br />
== Definition ==<br />
<br />
==== What Statistics is Statistics ====<br />
<br />
Statistics involve both the collection of data, and numerous methods for analyzing and interpreting the data. Statistics is useful for infering relationship between data sets, extracting properties from data sets, and visualizing patterns in data sets.<br />
<br />
Those involved in Statistics should be careful to note that the relationship between statistical fact and facts about the objects under study is only as good as the relationship between the data set and the objects under study. Statistics never produces facts about the objects directly and only analyses the data under study. Statistical analysis is just as biased as the data being analysed, yet this bias is difficult to see from the perspective of someone without a firm understanding of the method of statistical analysis. <br />
<br />
== How Statistics Work ==<br />
<br />
Statistics makes a number of very broad assumptions about any data set that is being studied. The most important assumptions will be discussed below.<br />
<br />
==== Random Number ====<br />
<br />
Statistics assumes that all measurments are random. The true measurement of any numerical value is not a specific value but instead follows some form of probability distribution. In the general case, the standard distribution is assumed; however, there are numerous other mathematical distributions available for comparison. <br />
<br />
==== Rule of Large Numbers ====<br />
<br />
Statistics are generally collected for a subset of the group of objects under study. For example, as it is nearly impossible to collect data on every book ever written, a representative subset can be studied instead. Any subset of a larger dataset will not accuratly represent the true distribution of data.<br />
<br />
The Rule of large numbers governs the relationship between subsets and data sets. It states that the larger the subset the more accuratly the distribution of the subset will reflect the larger set. For example, rolling a six sided dice sixty times will produce a distribution closer to the actual distribution then simply rolling the same dice ten times.<br />
<br />
==== The P Value ====<br />
<br />
Because statistics makes use of probabilities, there is allways a chance that percived relationships can emerge from data where no relationship actually exists. Most statistical methods will produce a P value which is effectivly the probability of such a coincodence. A low P value indicates a high probability that there is real relationship in the data while a high P value indicates that any percived relationship is probobly due to random fluctuations in the data. <br />
<br />
It is important to pick a P value prior to performing any statistical analysis. In general a P value less then 5% is desired; however, for important or sensative data P values lower then 1% and lower are generally desired.<br />
<br />
==== Interpreting Corelation ====<br />
<br />
A strong statistical relationship between two data sets does not imply that one causes the other. It only implies that one is a good predictor of the other, or that these two values are somehow related. Statistical relationships cannot be used to prove that one object is causally linked to another object; only that these two objects have a relationship that merits further study.<br />
<br />
==Examples ==<br />
<br />
===== T - Test =====<br />
<br />
===== Linear Regression =====<br />
<br />
==References and Further Readings==</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Basic_Statistical_AnalysisCIRCA:Basic Statistical Analysis2013-04-03T03:20:28Z<p>Recharti: </p>
<hr />
<div>= Basic Statistical Analysis =<br />
<br />
== Definition ==<br />
<br />
==== What Statistics are ====<br />
<br />
==== What Statistics are not ====<br />
<br />
== How Statistics Work ==<br />
<br />
==== Random Number ====<br />
<br />
==== Rule of Large Numbers ====<br />
<br />
==== The P Value ====<br />
<br />
==== Interpreting Corelation ====<br />
<br />
==Examples ==<br />
<br />
===== T - Test =====<br />
<br />
===== Linear Regression =====<br />
<br />
==References and Further Readings==</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Basic_Statistical_AnalysisCIRCA:Basic Statistical Analysis2013-04-03T03:20:03Z<p>Recharti: Created page with '= Basic Statistical Analysis = == Definition == === What Statistics are === === What Statistics are not === == How Statistics Work == ==== Random Number ==== ==== Rule of L…'</p>
<hr />
<div>= Basic Statistical Analysis =<br />
<br />
== Definition ==<br />
<br />
=== What Statistics are ===<br />
<br />
=== What Statistics are not ===<br />
<br />
== How Statistics Work ==<br />
<br />
==== Random Number ====<br />
<br />
==== Rule of Large Numbers ====<br />
<br />
==== The P Value ====<br />
<br />
==== Interpreting Corelation ====<br />
<br />
==Examples ==<br />
<br />
===== T - Test =====<br />
<br />
===== Linear Regression =====<br />
<br />
==References and Further Readings==</div>Rechartihttps://circa.cs.ualberta.ca/index.php/Main_PageMain Page2013-04-03T01:34:52Z<p>Recharti: </p>
<hr />
<div>== The Alberta Humanities Computing Compendium ==<br />
This wiki is a compendium of research organized by the staff and students associated with the [http://huco.ualberta.ca Humanties Computing] programme at the [http://www.ualberta.ca/ University of Alberta]. The wiki is a project of the [http://ra.tapor.ualberta.ca/~circa Canadian Institute for Research in Computing and the Arts].<br />
{|<br />
|<br />
== Introduction to Humanities Computing ==<br />
*[[CIRCA: April 7th Presentation Schedule|April 7th Presentation Schedule]], posted by Megan Sellmer<br />
*[[CIRCA: Current Issue Links|Current Issue Links]], posted by Megan Sellmer<br />
*[[CIRCA: Fiction and the Digital Humanities|Fiction and the Digital Humanities]], posted by Amy Dyrbye<br />
*[[CIRCA: Humanities Computing Timeline|Humanities Computing Timeline]], posted by Colette Leung<br />
*[[CIRCA: Humanities Computing Thesis Resources| Humanities Computing Thesis Research]], posted by Megan Sellmer<br />
*[http://guides.library.ualberta.ca/content.php?pid=55677 | Library Guide to Humanities Computing]<br />
<br />
== Theoretical Issues ==<br />
<br />
*[[CIRCA:EDUCAUSE - Information Technology Research and Learning |EDUCAUSE - Information Technology Research and Learning]], Submitted by Ugochukwu Udemezue Onyido<br />
<br />
== Project Management Current Issues ==<br />
<br />
*[[CIRCA: Penguin Archive Project|Penguin Archive Project]], posted by Ugochukwu Udemezue Onyido<br />
<br />
*[[CIRCA: Apple: IOS 4.3 Update|Apple: IOS 4.3 Update]], posted by Ugochukwu Udemezue Onyido<br />
<br />
*[[CIRCA: The Gmail Motion: A New Way to Communicate|The Gmail Motion: A New Way to Communicate]], posted by Ugochukwu Udemezue Onyido<br />
<br />
== Research Methods ==<br />
<br />
* [[CIRCA: Thesis Advisors |Thesis Advisors]], posted by Colette Leung<br />
<br />
== Technologies ==<br />
<br />
*[[CIRCA:Arduino |Arduino]], presented by Erik deJong<br />
*[[CIRCA:Content Management Systems|Content Management Systems]], by Sarah Vela<br />
*[[CIRCA:GIS |GIS]], by Michael Burden<br />
*[[CIRCA: HTML5 & Multimedia |HTML5 & Multimedia]], by Sonya Leung<br />
*[[CIRCA: Non Linear Editing|Non Linear Editing]], summarized by Megan Sellmer<br />
*[[CIRCA:Reference links to Semantic Web Resources |Semantic Web Resources]], by Joseph Dung<br />
*[[CIRCA:Semantic Web |Semantic Web]], summarized by Joseph Dung<br />
*[[CIRCA:Scanning |Scanning]], presented by Ugochukwu Udemezue Onyido<br />
*[[CIRCA:TEI XML |TEI XML]], presented by Colette Leung<br />
*[[CIRCA:Text Adventure |Text Adventure]], presented by Ashley Moroz<br />
*[[CIRCA:Wikis |Wikis]], summarized by Amy Dyrbye<br />
*[[CIRCA:WWW |WWW]], presented by Michael Burden<br />
*[[CIRCA: A General WWW History |A General WWW History]], by Domini Gee<br />
*[[CIRCA: Metadata |Metadata]], by Tianyi Li<br />
*[[CIRCA: Web 2.0 |Web 2.0]], by Sandra Sawchuk<br />
<br />
== Reviews ==<br />
* [[CIRCA: Arya, Agustin A. "The Hidden Side of Visualization." | Arya, Agustin A. "The Hidden Side of Visualization."]], reviewed by Erik deJong<br />
* [[CIRCA: Childress, M. and Braswell, R. "Using massively multiplayer online role-playing games for online learning" |Childress, M. and Braswell, R. "Using massively multiplayer online role-playing games for online learning"]], reviewed by Michael Burden<br />
* [[CIRCA: Haraway, Donna. "A Cyborg Manifesto: Science, Technology, and Socialist-Feminism in the Late Twentieth Century", in "Simians, Cyborgs and Women: The Reinvention of Nature" | Haraway, Donna. "A Cyborg Manifesto: Science, Technology, and Socialist-Feminism in the Late Twentieth Century," in "Simians, Cyborgs and Women: The Reinvention of Nature" ]], reviewed by Ugochukwu Udemezue Onyido<br />
* [[CIRCA: Hockey, Susan "History of Humanities Computing" |Hockey, Susan "History of Humanities Computing" ]], reviewed by Megan Sellmer<br />
* [[CIRCA: Kelly, Kevin "Scan This Book!" |Kelly, Kevin "Scan This Book!" ]], reviewed by Ashley Moroz<br />
* [[CIRCA: Postman, Neil. "Invisible Technologies", in "Technopoly: The Surrender of Culture to Technology" |Postman, Neil. "Invisible Technologies" in "Technopoly: The Surrender of Culture to Technology" ]], reviewed by Ugochukwu Udemezue Onyido<br />
* [[CIRCA: Renear, H. Allen. “Text Encoding”| Renear, H. Allen. “Text Encoding”]], reviewed by Joseph Dung<br />
* [[CIRCA: Manovich, Lev. "What is New Media?" in "The Language of New Media" | Manovich, Lev. "What is New Media?" in "The Language of New Media"]], reviewed by Colette Leung<br />
* [[CIRCA: Willinski, John. "Toward the Design of an Open Monograph Press."| Willinski, John. "Toward the Design of an Open Monograph Press."]], reviewed by Amy Dyrbye<br />
* [[CIRCA: Folsom, Ed. "Database as Genre: The Epic Transformation of Archives" | Freedman, Jonathan, Hayles, N. Katherine., McGann, Jerome, McGill, Meredith, Stallybrass, Peter, and Folsom, Ed. "Responses to Ed Folsom's 'Database as Genre: The Epic Transformation of Archives'"]], reviewed by Mihaela Ilovan<br />
<br />
== Best Practices ==<br />
*[[CIRCA:Accessibility | Accessibility]]<br />
<br />
== Projects ==<br />
* [[CIRCA:American and French Research for the Treasury of the French Language (ARTFL) Project | American and French<br />
Research for the Treasury of the French Language (ARTFL) Project]], reviewed by Erik deJong<br />
* [[CIRCA:Arts-humanities.net | Arts-humanities.net Project]], reviewed by Joel Sisk<br />
* [[CIRCA:BrownWomenWriters| Brown Women Writers Project]], reviewed by David Holmes and Lisa Goddard<br />
* [[CIRCA:The Chymistry of Issac Newton | The Chymistry of Isaac Newton]], reviewed by Sarah Vela<br />
* [[CIRCA:Creative Commons | Creative Commons]], reviewed by Ryan Chartier<br />
* [[CIRCA:Cultural Analytics / Software Studies]], reviewed by Justin Houle and Jared Bielby<br />
* [[CIRCA:Mandala Browser Project |Mandala Browser Project]] reviewed by Megan Sellmer<br />
* [[User talk:SonyaLeung | Mapping the Republic of Letters]] reviewed by Sonya Leung<br />
* [[CIRCA:Nines | Nines]], reviewed by Joseph Dung<br />
* [[CIRCA:Outbreak |Outbreak Project]], reviewed by Amy Dyrbye<br />
* [[CIRCA:Shadow of the Valley Project | Shadow of the Valley Project]], reviewed by Colette Leung<br />
* [[CIRCA:TAPoR | TAPoR]], reviewed by Lydia Zvyagintseva and Luciano Frizzera<br />
* [[CIRCA:TAPoR2.0 | TAPoR2.0]], reviewed by Tianyi Li<br />
* [[CIRCA:TextArc | TextArc]], reviewed by Michael Burden<br />
* [[CIRCA:TEI by Example | TEI by Example]], reviewed by Sâmia Pedraça<br />
* [[CIRCA:Vectors | Vectors]], reviewed by Ugochukwu Udemezue Onyido<br />
* [[CIRCA:Victorian Web | Victorian Web]], reviewed by Ashley Moroz<br />
* [[CIRCA:Virtual Peace | Virtual Peace]], reviewed by Vicky Varga<br />
* [[CIRCA:Great Unsolved Mysteries in Canadian History | Great Unsolved Mysteries in Canadian History ]], reviewed by Domini Gee<br />
* [[CIRCA:The Bentham Project | The Bentham Project]], reviewed by Sandra Sawchuk<br />
<br />
== Research Projects ==<br />
* [[CIRCA:Histories and Archives Project | Histories and Archives Project]]<br />
* [[CIRCA:centerNet Translation Project | centerNet Translation Project]]<br />
* [[CIRCA:Ukrainian Folklore Audio Project |Ukrainian Folklore Audio Project]]<br />
* [[CIRCA:Viral Analytics | Viral Analytics]]<br />
* [[CIRCA:Keavy's Project | Keavy's Project]] and [[CIRCA:Whitepaper On Return | Whitepaper on the Ethics of Digitizing Cultural Property]]<br />
* [[CIRCA:GRAND Interactives | GRAND Interactives]]<br />
* [[CIRCA:4Humanities | 4 Humanities]] Initiative to advocate for the humanities<br />
<br />
== Research Methods ==<br />
*[[CIRCA:Narrative Analysis | Narrative Analysis]], by Sâmia Pedraça<br />
*[[CIRCA:A/B Testing | A/B Testing]], by Tianyi Li<br />
*[[CIRCA:Basic Statistical Analysis | Basic Statistical Analysis]], by Ryan Chartier<br />
<br />
== Project Management ==<br />
*[[CIRCA: RockwellGuide | Rockwell's Guide to Project Management in the Digital Humanities]]<br />
*[[CIRCA: Tips | Management Tips]]<br />
*[[CIRCA: Helpful Tools| Helpful Tools]]<br />
*[[CIRCA: Literature Review | How to Write a Literature Review]]<br />
*[[CIRCA: CSL Guideline Brief Notes | CSL Guideline Brief Notes]]<br />
*[[CIRCA: Articles about Project Management | Pointers to Useful Articles and Tools]]<br />
<br />
== Interactive Arts Project ==<br />
* [[CIRCA:UndergradPrograms | Undergraduate programmes]] of interest<br />
* [[CIRCA:Courses in Programs | Courses in other U of A programs]]<br />
<br />
== Scholarly Publishers, Organizations and Centres ==<br />
* [[CIRCA:Publishers | Publishers who specialize in Digital Humanities]]<br />
* [[CIRCA:ADHO | ADHO - Alliance of Digital Humanities Organizations]]<br />
* [[CIRCA:Maryland Institute for Technology in the Humanities | Maryland Institute for Technology in the Humanities (MITH)]], reviewed by Joel Sisk<br />
* [[CIRCA:Scholar's Lab | Scholar's Lab]] - V. Varga and Elena Dergacheva<br />
* [[CIRCA:SHARCNET]] - reviewed by Jared Bielby<br />
* [[CIRCA:Category:HUMlab]] -Alexandrea Flynn<br />
* [[CIRCA:MIT Media Lab | MIT Media Lab]] - David Holmes<br />
* [[CIRCA:HASTAC | HASTAC]] - Lisa Goddard & Justin Houle<br />
* [[CIRCA: Stanford Humanities Lab | Stanford Humanities Lab]] -- Lydia Zvyagintseva<br />
<br />
== Getting Started with this Wiki ==<br />
* [[CIRCA:Very Simple Help | Very Simple Help]]<br />
* [http://circa.cs.ualberta.ca/index.php/Help:Editing Help with Editing]<br />
* [http://www.mediawiki.org/wiki/Manual:Configuration_settings Configuration settings list]<br />
* [http://www.mediawiki.org/wiki/Manual:FAQ MediaWiki FAQ]<br />
* [https://lists.wikimedia.org/mailman/listinfo/mediawiki-announce MediaWiki release mailing list]<br />
[[Category:Humanities Computing]]<br />
<br />
--[[User:GeoffreyRockwell|GeoffreyRockwell]] 01:05, 7 October 2010 (UTC)</div>Rechartihttps://circa.cs.ualberta.ca/index.php/Main_PageMain Page2013-04-03T01:21:15Z<p>Recharti: </p>
<hr />
<div>== The Alberta Humanities Computing Compendium ==<br />
This wiki is a compendium of research organized by the staff and students associated with the [http://huco.ualberta.ca Humanties Computing] programme at the [http://www.ualberta.ca/ University of Alberta]. The wiki is a project of the [http://ra.tapor.ualberta.ca/~circa Canadian Institute for Research in Computing and the Arts].<br />
{|<br />
|<br />
== Introduction to Humanities Computing ==<br />
*[[CIRCA: April 7th Presentation Schedule|April 7th Presentation Schedule]], posted by Megan Sellmer<br />
*[[CIRCA: Current Issue Links|Current Issue Links]], posted by Megan Sellmer<br />
*[[CIRCA: Fiction and the Digital Humanities|Fiction and the Digital Humanities]], posted by Amy Dyrbye<br />
*[[CIRCA: Humanities Computing Timeline|Humanities Computing Timeline]], posted by Colette Leung<br />
*[[CIRCA: Humanities Computing Thesis Resources| Humanities Computing Thesis Research]], posted by Megan Sellmer<br />
*[http://guides.library.ualberta.ca/content.php?pid=55677 | Library Guide to Humanities Computing]<br />
<br />
== Theoretical Issues ==<br />
<br />
*[[CIRCA:EDUCAUSE - Information Technology Research and Learning |EDUCAUSE - Information Technology Research and Learning]], Submitted by Ugochukwu Udemezue Onyido<br />
<br />
== Project Management Current Issues ==<br />
<br />
*[[CIRCA: Penguin Archive Project|Penguin Archive Project]], posted by Ugochukwu Udemezue Onyido<br />
<br />
*[[CIRCA: Apple: IOS 4.3 Update|Apple: IOS 4.3 Update]], posted by Ugochukwu Udemezue Onyido<br />
<br />
*[[CIRCA: The Gmail Motion: A New Way to Communicate|The Gmail Motion: A New Way to Communicate]], posted by Ugochukwu Udemezue Onyido<br />
<br />
== Research Methods ==<br />
<br />
* [[CIRCA: Thesis Advisors |Thesis Advisors]], posted by Colette Leung<br />
<br />
== Technologies ==<br />
<br />
*[[CIRCA:Arduino |Arduino]], presented by Erik deJong<br />
*[[CIRCA:Content Management Systems|Content Management Systems]], by Sarah Vela<br />
*[[CIRCA:GIS |GIS]], by Michael Burden<br />
*[[CIRCA: HTML5 & Multimedia |HTML5 & Multimedia]], by Sonya Leung<br />
*[[CIRCA: Non Linear Editing|Non Linear Editing]], summarized by Megan Sellmer<br />
*[[CIRCA:Reference links to Semantic Web Resources |Semantic Web Resources]], by Joseph Dung<br />
*[[CIRCA:Semantic Web |Semantic Web]], summarized by Joseph Dung<br />
*[[CIRCA:Scanning |Scanning]], presented by Ugochukwu Udemezue Onyido<br />
*[[CIRCA:TEI XML |TEI XML]], presented by Colette Leung<br />
*[[CIRCA:Text Adventure |Text Adventure]], presented by Ashley Moroz<br />
*[[CIRCA:Wikis |Wikis]], summarized by Amy Dyrbye<br />
*[[CIRCA:WWW |WWW]], presented by Michael Burden<br />
*[[CIRCA: A General WWW History |A General WWW History]], by Domini Gee<br />
*[[CIRCA: Metadata |Metadata]], by Tianyi Li<br />
*[[CIRCA: Web 2.0 |Web 2.0]], by Sandra Sawchuk<br />
<br />
== Reviews ==<br />
* [[CIRCA: Arya, Agustin A. "The Hidden Side of Visualization." | Arya, Agustin A. "The Hidden Side of Visualization."]], reviewed by Erik deJong<br />
* [[CIRCA: Childress, M. and Braswell, R. "Using massively multiplayer online role-playing games for online learning" |Childress, M. and Braswell, R. "Using massively multiplayer online role-playing games for online learning"]], reviewed by Michael Burden<br />
* [[CIRCA: Haraway, Donna. "A Cyborg Manifesto: Science, Technology, and Socialist-Feminism in the Late Twentieth Century", in "Simians, Cyborgs and Women: The Reinvention of Nature" | Haraway, Donna. "A Cyborg Manifesto: Science, Technology, and Socialist-Feminism in the Late Twentieth Century," in "Simians, Cyborgs and Women: The Reinvention of Nature" ]], reviewed by Ugochukwu Udemezue Onyido<br />
* [[CIRCA: Hockey, Susan "History of Humanities Computing" |Hockey, Susan "History of Humanities Computing" ]], reviewed by Megan Sellmer<br />
* [[CIRCA: Kelly, Kevin "Scan This Book!" |Kelly, Kevin "Scan This Book!" ]], reviewed by Ashley Moroz<br />
* [[CIRCA: Postman, Neil. "Invisible Technologies", in "Technopoly: The Surrender of Culture to Technology" |Postman, Neil. "Invisible Technologies" in "Technopoly: The Surrender of Culture to Technology" ]], reviewed by Ugochukwu Udemezue Onyido<br />
* [[CIRCA: Renear, H. Allen. “Text Encoding”| Renear, H. Allen. “Text Encoding”]], reviewed by Joseph Dung<br />
* [[CIRCA: Manovich, Lev. "What is New Media?" in "The Language of New Media" | Manovich, Lev. "What is New Media?" in "The Language of New Media"]], reviewed by Colette Leung<br />
* [[CIRCA: Willinski, John. "Toward the Design of an Open Monograph Press."| Willinski, John. "Toward the Design of an Open Monograph Press."]], reviewed by Amy Dyrbye<br />
* [[CIRCA: Folsom, Ed. "Database as Genre: The Epic Transformation of Archives" | Freedman, Jonathan, Hayles, N. Katherine., McGann, Jerome, McGill, Meredith, Stallybrass, Peter, and Folsom, Ed. "Responses to Ed Folsom's 'Database as Genre: The Epic Transformation of Archives'"]], reviewed by Mihaela Ilovan<br />
<br />
== Best Practices ==<br />
*[[CIRCA:Accessibility | Accessibility]]<br />
<br />
== Projects ==<br />
* [[CIRCA:American and French Research for the Treasury of the French Language (ARTFL) Project | American and French<br />
Research for the Treasury of the French Language (ARTFL) Project]], reviewed by Erik deJong<br />
* [[CIRCA:Arts-humanities.net | Arts-humanities.net Project]], reviewed by Joel Sisk<br />
* [[CIRCA:BrownWomenWriters| Brown Women Writers Project]], reviewed by David Holmes and Lisa Goddard<br />
* [[CIRCA:The Chymistry of Issac Newton | The Chymistry of Isaac Newton]], reviewed by Sarah Vela<br />
* [[CIRCA:Creative Commons | Creative Commons]], reviewed by Ryan Chartier<br />
* [[CIRCA:Cultural Analytics / Software Studies]], reviewed by Justin Houle and Jared Bielby<br />
* [[CIRCA:Mandala Browser Project |Mandala Browser Project]] reviewed by Megan Sellmer<br />
* [[User talk:SonyaLeung | Mapping the Republic of Letters]] reviewed by Sonya Leung<br />
* [[CIRCA:Nines | Nines]], reviewed by Joseph Dung<br />
* [[CIRCA:Outbreak |Outbreak Project]], reviewed by Amy Dyrbye<br />
* [[CIRCA:Shadow of the Valley Project | Shadow of the Valley Project]], reviewed by Colette Leung<br />
* [[CIRCA:TAPoR | TAPoR]], reviewed by Lydia Zvyagintseva and Luciano Frizzera<br />
* [[CIRCA:TAPoR2.0 | TAPoR2.0]], reviewed by Tianyi Li<br />
* [[CIRCA:TextArc | TextArc]], reviewed by Michael Burden<br />
* [[CIRCA:TEI by Example | TEI by Example]], reviewed by Sâmia Pedraça<br />
* [[CIRCA:Vectors | Vectors]], reviewed by Ugochukwu Udemezue Onyido<br />
* [[CIRCA:Victorian Web | Victorian Web]], reviewed by Ashley Moroz<br />
* [[CIRCA:Virtual Peace | Virtual Peace]], reviewed by Vicky Varga<br />
* [[CIRCA:Great Unsolved Mysteries in Canadian History | Great Unsolved Mysteries in Canadian History ]], reviewed by Domini Gee<br />
* [[CIRCA:The Bentham Project | The Bentham Project]], reviewed by Sandra Sawchuk<br />
<br />
== Research Projects ==<br />
* [[CIRCA:Histories and Archives Project | Histories and Archives Project]]<br />
* [[CIRCA:centerNet Translation Project | centerNet Translation Project]]<br />
* [[CIRCA:Ukrainian Folklore Audio Project |Ukrainian Folklore Audio Project]]<br />
* [[CIRCA:Viral Analytics | Viral Analytics]]<br />
* [[CIRCA:Keavy's Project | Keavy's Project]] and [[CIRCA:Whitepaper On Return | Whitepaper on the Ethics of Digitizing Cultural Property]]<br />
* [[CIRCA:GRAND Interactives | GRAND Interactives]]<br />
* [[CIRCA:4Humanities | 4 Humanities]] Initiative to advocate for the humanities<br />
<br />
== Research Methods ==<br />
*[[CIRCA:Narrative Analysis | Narrative Analysis]], by Sâmia Pedraça<br />
*[[CIRCA:A/B Testing | A/B Testing]], by Tianyi Li<br />
*[[CIRCA:Basic Statistics | Basic Statistics]], by Ryan Chartier<br />
<br />
== Project Management ==<br />
*[[CIRCA: RockwellGuide | Rockwell's Guide to Project Management in the Digital Humanities]]<br />
*[[CIRCA: Tips | Management Tips]]<br />
*[[CIRCA: Helpful Tools| Helpful Tools]]<br />
*[[CIRCA: Literature Review | How to Write a Literature Review]]<br />
*[[CIRCA: CSL Guideline Brief Notes | CSL Guideline Brief Notes]]<br />
*[[CIRCA: Articles about Project Management | Pointers to Useful Articles and Tools]]<br />
<br />
== Interactive Arts Project ==<br />
* [[CIRCA:UndergradPrograms | Undergraduate programmes]] of interest<br />
* [[CIRCA:Courses in Programs | Courses in other U of A programs]]<br />
<br />
== Scholarly Publishers, Organizations and Centres ==<br />
* [[CIRCA:Publishers | Publishers who specialize in Digital Humanities]]<br />
* [[CIRCA:ADHO | ADHO - Alliance of Digital Humanities Organizations]]<br />
* [[CIRCA:Maryland Institute for Technology in the Humanities | Maryland Institute for Technology in the Humanities (MITH)]], reviewed by Joel Sisk<br />
* [[CIRCA:Scholar's Lab | Scholar's Lab]] - V. Varga and Elena Dergacheva<br />
* [[CIRCA:SHARCNET]] - reviewed by Jared Bielby<br />
* [[CIRCA:Category:HUMlab]] -Alexandrea Flynn<br />
* [[CIRCA:MIT Media Lab | MIT Media Lab]] - David Holmes<br />
* [[CIRCA:HASTAC | HASTAC]] - Lisa Goddard & Justin Houle<br />
* [[CIRCA: Stanford Humanities Lab | Stanford Humanities Lab]] -- Lydia Zvyagintseva<br />
<br />
== Getting Started with this Wiki ==<br />
* [[CIRCA:Very Simple Help | Very Simple Help]]<br />
* [http://circa.cs.ualberta.ca/index.php/Help:Editing Help with Editing]<br />
* [http://www.mediawiki.org/wiki/Manual:Configuration_settings Configuration settings list]<br />
* [http://www.mediawiki.org/wiki/Manual:FAQ MediaWiki FAQ]<br />
* [https://lists.wikimedia.org/mailman/listinfo/mediawiki-announce MediaWiki release mailing list]<br />
[[Category:Humanities Computing]]<br />
<br />
--[[User:GeoffreyRockwell|GeoffreyRockwell]] 01:05, 7 October 2010 (UTC)</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Creative_CommonsCIRCA:Creative Commons2011-11-28T04:16:04Z<p>Recharti: </p>
<hr />
<div>==Overview==<br />
[[IMage:Creative commons webpage.png|250px|thumb|right|Creative Commons Homepage]]<br />
<br />
The Creative Commons is a project in copyright distribution created and run by the Creative Commons not-for-profit organization with headquarters in Mountain View California. Creative Commons started in 2001 with the intent of creating a legal framework that would give content creators the tools to release and distribute their work freely, while also giving content consumers the ability to share and interact with the work, and thereby maximizing the potential of the internet. The Creative Commons released their first set of license agreements in 2002. Since then the Creative Commons has been revising these agreements in order to make them both legally binding, as well as global in nature. <br />
<br />
Unlike some other free information movements the Creative Commons is not about giving up copyright completely. Several of the licenses reserve some rights that copyright was originally intended to protect. All Creative Commons licenses reserve the right to be attributed. Others reserve the right to commercialize the work, and others still restrict how the work is to be distributed: in whole, or in part. In this way, Creative Commons is not a and should not be seen as a system for bypassing copyright. It is instead intended only as a method to ease some of the control copyright laws give to the content creator.<br />
<br />
In order to license a work under the Creative Commons a content creator needs only to place a link to the particular license, and make it clear on the work that it is licensed under Creative Commons. No registration is necessary. However, Creative Commons is not a legal entity and makes it clear that they are only a middle party who writes the licenses and is not responsible for how they are used. <br />
<br />
==Licenses==<br />
Each community commons (cc) licences are designed to allow for free distribution with restrictions only on how the work is to be used. Each of the six cc licenses contain various combinations of the following restrictions.<br />
<br />
===Attribution===<br />
The Attribution clause is the minimal level of rights maintained by all six cc licenses. It simply requires any user of the cc licenced work to properly attribute the work whenever it is reused, remixed, or redistributed.<br />
<br />
===No Derivatives===<br />
The No Derivatives clause states that the work can only be redistributed as a complete whole and cannot be changed or modified.<br />
<br />
===Share-Alike===<br />
The Share-Alike clause is the cc analogue of the software licenses of the Free Software Movement. Works licenced under a Share-Alike cc licence are available for remixing, and redistribution as long as the new product is released under the exact same license as the original. This clause is incompatible with the No Derivatives clause.<br />
<br />
===Noncommercial===<br />
The Noncommercial clause is used when the author is reserving the right to monetize the product. The work can only be redistributed (or remixed if the license allows) if the work is not being used for profit, or for advertisement. Some ambiguity does exist as to what is considered commercial use, and therefore the noncommercial licenses can be the most restrictive of all cc licenses.<br />
<br />
===CC0===<br />
In addition to the six CC licenses the group does encourage the use of a tool that they do not consider to be a license. The CC0 tool is designed to allow an author to waive their copyright rights to the furthest extent allowable by law. The CC0 then, hopes to give authors an opportunity to place their works into the public domain.<br />
<br />
==Criticism and Analysis==<br />
Creative Commons attempts to bridge the gab between two polar views on copyright protection. Both copyright defenders as well as the free information movement have voiced complaints with how the creative commons operates. From a copyright standpoint the creative commons at best only repackages what the copyright system already does, that is give the creator control of how the work is distributed. At worst, it erodes the current copyright system by limiting which rights a creator has control over and at worst erodes the creators incentive to create. On the opposite end of the spectrum the creative commons has been blamed for not truly being free either, as the 'attribution' and 'non-commercial' licenses would need to be supported for the duration of the copyright (In Canada that is Life + 50 years). If for any reason the original attribution where lost, it would once again become illegal to redistribute the work counteracting the original goals of the commons. As well, some of the cc licenses are not compatible with each other and cannot both be used in the same work and redistributed under the same license. Therefore, sectioning off portions of the commons from being used with each other.<br />
<br />
Regardless of these criticisms; however, the creative commons is a tool for authors who want to open up their work to the public while maintaining their copyright on the work. Creative commons maintains six different licences backing their own philosophy that copyright is not a one-size-fits-all situation. Each work and genre is subject to it's own discussion as to how the work should be shared. Creative Commons aims to be a platform to allow this discussion to happen.<br />
<br />
==External Links==<br />
[http://http://creativecommons.org/ Creative Commons Website ] <br /></div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Creative_CommonsCIRCA:Creative Commons2011-11-28T04:14:19Z<p>Recharti: </p>
<hr />
<div>==Overview==<br />
[[IMage:Creative commons webpage.png|250px|thumb|right|Creative Commons Homepage]]<br />
<br />
The Creative Commons is a project in copyright distribution created and run by the Creative Commons not-for-profit organization with headquarters in Mountain View California. Creative Commons started in 2001 with the intent of creating a legal framework that would give content creators the tools to release and distribute their work freely, while also giving content consumers the ability to share and interact with the work, and thereby maximizing the potential of the internet. The Creative Commons released their first set of license agreements in 2002. Since then the Creative Commons has been revising these agreements in order to make them both legally binding, as well as global in nature. <br /><br /><br />
Unlike some other free information movements the Creative Commons is not about giving up copyright completely. Several of the licenses reserve some rights that copyright was originally intended to protect. All Creative Commons licenses reserve the right to be attributed. Others reserve the right to commercialize the work, and others still restrict how the work is to be distributed: in whole, or in part. In this way, Creative Commons is not a and should not be seen as a system for bypassing copyright. It is instead intended only as a method to ease some of the control copyright laws give to the content creator.<br />
<br /><br />
<br /><br />
In order to license a work under the Creative Commons a content creator needs only to place a link to the particular license, and make it clear on the work that it is licensed under Creative Commons. No registration is necessary. However, Creative Commons is not a legal entity and makes it clear that they are only a middle party who writes the licenses and is not responsible for how they are used. <br />
<br />
<br /><br />
<br /><br />
<br />
==Licenses==<br />
Each community commons (cc) licences are designed to allow for free distribution with restrictions only on how the work is to be used. Each of the six cc licenses contain various combinations of the following restrictions.<br />
<br /><br />
<br /><br />
<br />
===Attribution===<br />
The Attribution clause is the minimal level of rights maintained by all six cc licenses. It simply requires any user of the cc licenced work to properly attribute the work whenever it is reused, remixed, or redistributed.<br />
<br /><br />
<br /><br />
<br />
===No Derivatives===<br />
The No Derivatives clause states that the work can only be redistributed as a complete whole and cannot be changed or modified.<br />
<br /><br />
<br /><br />
<br />
===Share-Alike===<br />
The Share-Alike clause is the cc analogue of the software licenses of the Free Software Movement. Works licenced under a Share-Alike cc licence are available for remixing, and redistribution as long as the new product is released under the exact same license as the original. This clause is incompatible with the No Derivatives clause.<br />
<br /><br />
<br /><br />
<br />
===Noncommercial===<br />
The Noncommercial clause is used when the author is reserving the right to monetize the product. The work can only be redistributed (or remixed if the license allows) if the work is not being used for profit, or for advertisement. Some ambiguity does exist as to what is considered commercial use, and therefore the noncommercial licenses can be the most restrictive of all cc licenses.<br />
<br /><br />
<br /><br />
<br />
===CC0===<br />
In addition to the six CC licenses the group does encourage the use of a tool that they do not consider to be a license. The CC0 tool is designed to allow an author to waive their copyright rights to the furthest extent allowable by law. The CC0 then, hopes to give authors an opportunity to place their works into the public domain.<br />
<br /><br />
<br /><br />
<br />
==Criticism and Analysis==<br />
Creative Commons attempts to bridge the gab between two polar views on copyright protection. Both copyright defenders as well as the free information movement have voiced complaints with how the creative commons operates. From a copyright standpoint the creative commons at best only repackages what the copyright system already does, that is give the creator control of how the work is distributed. At worst, it erodes the current copyright system by limiting which rights a creator has control over and at worst erodes the creators incentive to create. On the opposite end of the spectrum the creative commons has been blamed for not truly being free either, as the 'attribution' and 'non-commercial' licenses would need to be supported for the duration of the copyright (In Canada that is Life + 50 years). If for any reason the original attribution where lost, it would once again become illegal to redistribute the work counteracting the original goals of the commons. As well, some of the cc licenses are not compatible with each other and cannot both be used in the same work and redistributed under the same license. Therefore, sectioning off portions of the commons from being used with each other. <br /><br /><br />
Regardless of these criticisms; however, the creative commons is a tool for authors who want to open up their work to the public while maintaining their copyright on the work. Creative commons maintains six different licences backing their own philosophy that copyright is not a one-size-fits-all situation. Each work and genre is subject to it's own discussion as to how the work should be shared. Creative Commons aims to be a platform to allow this discussion to happen.<br />
<br /><br />
<br /><br />
==External Links==<br />
[http://http://creativecommons.org/ Creative Commons Website ] <br /></div>Rechartihttps://circa.cs.ualberta.ca/index.php/File:Creative_commons_webpage.pngFile:Creative commons webpage.png2011-11-28T03:55:26Z<p>Recharti: uploaded a new version of "File:Creative commons webpage.png":&#32;A screen capture of the creative commons webpage November 27 2011.</p>
<hr />
<div>A screen capture of the creative commons webpage November 27 2011.</div>Rechartihttps://circa.cs.ualberta.ca/index.php/File:Creative_commons_webpage.pngFile:Creative commons webpage.png2011-11-28T03:55:07Z<p>Recharti: A screen capture of the creative commons webpage November 27 2011.</p>
<hr />
<div>A screen capture of the creative commons webpage November 27 2011.</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:Creative_CommonsCIRCA:Creative Commons2011-11-25T23:35:04Z<p>Recharti: Created page with '==Overview== The Creative Commons is a project in copyright distribution created and run by a not-for-profit organization with the same name that has its headquarters in Mountain…'</p>
<hr />
<div>==Overview==<br />
The Creative Commons is a project in copyright distribution created and run by a not-for-profit organization with the same name that has its headquarters in Mountain View California. The objective of the Creative Commons is to give content creators a venue to release their works in such a way that others can share, and in some cases remix or modify, their work. Creative Commons has created a number of licensing agreements that creators can choose to license their work under. Their slogan "some rights reserved" refers the licensee’s ability to choose which rights they want to maintain for themselves. <br />
<br />
==Licenses==<br />
Each community commons (cc) licences are designed to allow for free distribution with restrictions only on how the work is to be used. Each of the six cc licenses contain various combinations of the following restrictions.<br />
<br />
===Attribution===<br />
The Attribution clause is the minimal level of rights maintained by all six cc licenses. It simply requires any user of the cc licenced work to properly attribute the work whenever it is reused, remixed, or redistributed.<br />
<br />
===No Derivatives===<br />
The No Derivatives clause states that the work can only be redistributed as a complete whole and cannot be changed or modified.<br />
<br />
===Share-Alike===<br />
The Share-Alike clause is the cc analogue of the software licenses of the Free Software Movement. Works licenced under a Share-Alike cc licence are available for remixing, and redistribution as long as the new product is released under the exact same license as the original. This clause is incompatible with the No Derivatives clause.<br />
<br />
===Noncommercial===<br />
The Noncommercial clause is used when the author is reserving the right to monetize the product. The work can only be redistributed (or remixed if the license allows) if the work is not being used for profit, or for advertisement. Some ambiguity does exist as to what is considered commercial use, and therefore the noncommercial licenses can be the most restrictive of all cc licenses.<br />
<br />
===CC0===<br />
In addition to the six CC licenses the group does encourage the use of a tool that they do not consider to be a license. The CC0 tool is designed to allow an author to waive their copyright rights to the furthest extent allowable by law. The CC0 then, hopes to give authors an opportunity to place their works into the public domain.<br />
<br />
==Criticism and Analysis==<br />
Creative Commons attempts to bridge the gab between two polar views on copyright protection. Both copyright defenders as well as the free information movement have voiced complaints with how the creative commons operates. From a copyright standpoint the creative commons at best only repackages what the copyright system already does, that is give the creator control of how the work is distributed. At worst, it erodes the current copyright system by limiting which rights a creator has control over and at worst erodes the creators incentive to create. On the opposite end of the spectrum the creative commons has been blamed for not truly being free either, as the 'attribution' and 'non-commercial' licenses would need to be supported for the duration of the copyright (In Canada that is Life + 50 years). If for any reason the original attribution where lost, it would once again become illegal to redistribute the work counteracting the original goals of the commons. As well, some of the cc licenses are not compatible with each other and cannot both be used in the same work and redistributed under the same license. Therefore, sectioning off portions of the commons from being used with each other. <br /><br />
Regardless of these criticisms; however, the creative commons is a tool for authors who want to open up their work to the public while maintaining their copyright on the work. Creative commons maintains six different licences backing their own philosophy that copyright is not a one-size-fits-all situation. Each work and genre is subject to it's own discussion as to how the work should be shared. Creative Commons aims to be a platform to allow this discussion to happen.<br />
<br />
==External Links==<br />
[http://http://creativecommons.org/ Creative Commons Website ] <br /></div>Rechartihttps://circa.cs.ualberta.ca/index.php/Main_PageMain Page2011-11-25T20:29:48Z<p>Recharti: /* Projects */</p>
<hr />
<div>== The Alberta Humanities Computing Compendium ==<br />
This wiki is a compendium of research organized by the staff and students associated with the [http://huco.ualberta.ca Humanties Computing] programme at the [http://www.ualberta.ca/ University of Alberta]. The wiki is a project of the [http://ra.tapor.ualberta.ca/~circa Canadian Institute for Research in Computing and the Arts].<br />
{|<br />
|<br />
== Introduction to Humanities Computing ==<br />
*[[CIRCA: April 7th Presentation Schedule|April 7th Presentation Schedule]], posted by Megan Sellmer<br />
*[[CIRCA: Current Issue Links|Current Issue Links]], posted by Megan Sellmer<br />
*[[CIRCA: Fiction and the Digital Humanities|Fiction and the Digital Humanities]], posted by Amy Dyrbye<br />
*[[CIRCA: Humanities Computing Timeline|Humanities Computing Timeline]], posted by Colette Leung<br />
*[[CIRCA: Humanities Computing Thesis Resources| Humanities Computing Thesis Research]], posted by Megan Sellmer<br />
*[http://guides.library.ualberta.ca/content.php?pid=55677 | Library Guide to Humanities Computing]<br />
<br />
== Theoretical Issues ==<br />
<br />
*[[CIRCA:EDUCAUSE - Information Technology Research and Learning |EDUCAUSE - Information Technology Research and Learning]], Submitted by Ugochukwu Udemezue Onyido<br />
<br />
== Project Management Current Issues ==<br />
<br />
*[[CIRCA: Penguin Archive Project|Penguin Archive Project]], posted by Ugochukwu Udemezue Onyido<br />
<br />
*[[CIRCA: Apple: IOS 4.3 Update|Apple: IOS 4.3 Update]], posted by Ugochukwu Udemezue Onyido<br />
<br />
*[[CIRCA: The Gmail Motion: A New Way to Communicate|The Gmail Motion: A New Way to Communicate]], posted by Ugochukwu Udemezue Onyido<br />
<br />
== Research Methods ==<br />
<br />
* [[CIRCA: Thesis Advisors |Thesis Advisors]], posted by Colette Leung<br />
<br />
== Technologies ==<br />
<br />
*[[CIRCA:Arduino |Arduino]], presented by Erik deJong<br />
*[[CIRCA: Non Linear Editing|Non Linear Editing]], summarized by Megan Sellmer<br />
*[[CIRCA:Semantic Web |Semantic Web]], summarized by Joseph Dung<br />
*[[CIRCA:Scanning |Scanning]], presented by Ugochukwu Udemezue Onyido<br />
*[[CIRCA:TEI XML |TEI XML]], presented by Colette Leung<br />
*[[CIRCA:Text Adventure |Text Adventure]], presented by Ashley Moroz<br />
*[[CIRCA:Wikis |Wikis]], summarized by Amy Dyrbye<br />
*[[CIRCA:WWW |WWW]], presented by Michael Burden<br />
*[[CIRCA:GIS |GIS]], by Michael Burden<br />
*[[CIRCA:Reference links to Semantic Web Resources |Semantic Web Resources]], by Joseph Dung<br />
<br />
<br />
== Reviews ==<br />
* [[CIRCA: Arya, Agustin A. "The Hidden Side of Visualization." | Arya, Agustin A. "The Hidden Side of Visualization."]], reviewed by Erik deJong<br />
* [[CIRCA: Childress, M. and Braswell, R. "Using massively multiplayer online role-playing games for online learning" |Childress, M. and Braswell, R. "Using massively multiplayer online role-playing games for online learning"]], reviewed by Michael Burden<br />
* [[CIRCA: Haraway, Donna. "A Cyborg Manifesto: Science, Technology, and Socialist-Feminism in the Late Twentieth Century", in "Simians, Cyborgs and Women: The Reinvention of Nature" | Haraway, Donna. "A Cyborg Manifesto: Science, Technology, and Socialist-Feminism in the Late Twentieth Century," in "Simians, Cyborgs and Women: The Reinvention of Nature" ]], reviewed by Ugochukwu Udemezue Onyido<br />
* [[CIRCA: Hockey, Susan "History of Humanities Computing" |Hockey, Susan "History of Humanities Computing" ]], reviewed by Megan Sellmer<br />
* [[CIRCA: Kelly, Kevin "Scan This Book!" |Kelly, Kevin "Scan This Book!" ]], reviewed by Ashley Moroz<br />
* [[CIRCA: Postman, Neil. "Invisible Technologies", in "Technopoly: The Surrender of Culture to Technology" |Postman, Neil. "Invisible Technologies" in "Technopoly: The Surrender of Culture to Technology" ]], reviewed by Ugochukwu Udemezue Onyido<br />
* [[CIRCA: Renear, H. Allen. “Text Encoding”| Renear, H. Allen. “Text Encoding”]], reviewed by Joseph Dung<br />
* [[CIRCA: Manovich, Lev. "What is New Media?" in "The Language of New Media" | Manovich, Lev. "What is New Media?" in "The Language of New Media"]], reviewed by Colette Leung<br />
* [[CIRCA: Willinski, John. "Toward the Design of an Open Monograph Press."| Willinski, John. "Toward the Design of an Open Monograph Press."]], reviewed by Amy Dyrbye<br />
* [[CIRCA: Folsom, Ed. "Database as Genre: The Epic Transformation of Archives" | Freedman, Jonathan, Hayles, N. Katherine., McGann, Jerome, McGill, Meredith, Stallybrass, Peter, and Folsom, Ed. "Responses to Ed Folsom's 'Database as Genre: The Epic Transformation of Archives'"]], reviewed by Mihaela Ilovan<br />
<br />
== Best Practices ==<br />
*[[CIRCA:Accessibility | Accessibility]]<br />
<br />
== Projects ==<br />
* [[CIRCA:American and French Research for the Treasury of the French Language (ARTFL) Project | American and French<br />
Research for the Treasury of the French Language (ARTFL) Project]], reviewed by Erik deJong<br />
* [[CIRCA:Arts-humanities.net | Arts-humanities.net Project]], reviewed by Joel Sisk<br />
* [[CIRCA:BrownWomenWriters| Brown Women Writers Project]], reviewed by David Holmes and Lisa Goddard<br />
* [[CIRCA:Cultural Analytics / Software Studies]], reviewed by Justin Houle and Jared Bielby<br />
* [[CIRCA:Creative Commons | Creative Commons]], reviewed by Ryan Chartier<br />
* [[CIRCA:Mandala Browser Project |Mandala Browser Project]] reviewed by Megan Sellmer<br />
* [[CIRCA:Nines | Nines]], reviewed by Joseph Dung<br />
* [[CIRCA:Outbreak |Outbreak Project]], reviewed by Amy Dyrbye<br />
* [[CIRCA:Shadow of the Valley Project | Shadow of the Valley Project]], reviewed by Colette Leung<br />
* [[CIRCA:TAPoR | TAPoR]], reviewed by Lydia Zvyagintseva and Luciano Frizzera<br />
* [[CIRCA:TextArc | TextArc]], reviewed by Michael Burden<br />
* [[CIRCA:Victorian Web | Victorian Web]], reviewed by Ashley Moroz<br />
* [[CIRCA:Virtual Peace | Virtual Peace]], reviewed by Vicky Varga<br />
* [[CIRCA:Vectors | Vectors]], reviewed by Ugochukwu Udemezue Onyido<br />
<br />
== Research Projects ==<br />
* [[CIRCA:Histories and Archives Project | Histories and Archives Project]]<br />
* [[CIRCA:centerNet Translation Project | centerNet Translation Project]]<br />
* [[CIRCA:Ukrainian Folklore Audio Project |Ukrainian Folklore Audio Project]]<br />
* [[CIRCA:Viral Analytics | Viral Analytics]]<br />
* [[CIRCA:Keavy's Project | Keavy's Project]] and [[CIRCA:Whitepaper On Return | Whitepaper on the Ethics of Digitizing Cultural Property]]<br />
* [[CIRCA:GRAND Interactives | GRAND Interactives]]<br />
<br />
== Project Management ==<br />
*[[CIRCA: RockwellGuide | Rockwell's Guide to Project Management in the Digital Humanities]]<br />
*[[CIRCA: Tips | Management Tips]]<br />
*[[CIRCA: Helpful Tools| Helpful Tools]]<br />
*[[CIRCA: Literature Review | How to Write a Literature Review]]<br />
*[[CIRCA: CSL Guideline Brief Notes | CSL Guideline Brief Notes]]<br />
*[[CIRCA: Articles about Project Management | Pointers to Useful Articles and Tools]]<br />
<br />
== Interactive Arts Project ==<br />
* [[CIRCA:UndergradPrograms | Undergraduate programmes]] of interest<br />
* [[CIRCA:Courses in Programs | Courses in other U of A programs]]<br />
<br />
== Scholarly Publishers, Organizations and Centres ==<br />
* [[CIRCA:Publishers | Publishers who specialize in Digital Humanities]]<br />
* [[CIRCA:ADHO | ADHO - Alliance of Digital Humanities Organizations]]<br />
* [[CIRCA:Maryland Institute for Technology in the Humanities | Maryland Institute for Technology in the Humanities (MITH)]], reviewed by Joel Sisk<br />
* [[CIRCA:Scholar's Lab | Scholar's Lab]] - V. Varga and Elena Dergacheva<br />
* [[CIRCA:SHARCNET]] - reviewed by Jared Bielby<br />
* [[CIRCA:Category:HUMlab]] -Alexandrea Flynn<br />
* [[CIRCA:MIT Media Lab | MIT Media Lab]] - David Holmes<br />
* [[CIRCA:HASTAC | HASTAC]] - Lisa Goddard & Justin Houle<br />
* [[CIRCA: Stanford Humanities Lab | Stanford Humanities Lab]] -- Lydia Zvyagintseva<br />
<br />
== Getting Started with this Wiki ==<br />
* [[CIRCA:Very Simple Help | Very Simple Help]]<br />
* [http://circa.cs.ualberta.ca/index.php/Help:Editing Help with Editing]]<br />
* [http://www.mediawiki.org/wiki/Manual:Configuration_settings Configuration settings list]<br />
* [http://www.mediawiki.org/wiki/Manual:FAQ MediaWiki FAQ]<br />
* [https://lists.wikimedia.org/mailman/listinfo/mediawiki-announce MediaWiki release mailing list]<br />
[[Category:Humanities Computing]]<br />
<br />
--[[User:GeoffreyRockwell|GeoffreyRockwell]] 01:05, 7 October 2010 (UTC)</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:ADHOCIRCA:ADHO2011-09-26T19:52:27Z<p>Recharti: /* Publication */</p>
<hr />
<div>== ADHO - Alliance of Digital Humanities Organizations==<br />
<br />
The Alliance of Digital Humanities Organizations (ADHO) is an umbrella organization that acts to promote digital research and teaching across its constitution organizations. The ADHO was officially formed in 2005 with it's two founding members the ALLC and the ACH.[http://digitalhumanities.org/]<br />
<br />
ADHO is currently comprised of four main organizations: <br />
* Association for Literary and Linguistic Computing (ALLC)<br />
* Association for Computer and the Humanities (ACH)<br />
* The Society for Digital for Digital Humanities/La Société pour l'étude des Média Interactif (SDH-SEMI)<br />
* centerNet (joining in 2012)<br />
<br />
The main purpose of the ADHO is to manage the Conferences and Publications common to all it's constituent organizations.<br />
<br />
=== Conference ===<br />
<br />
The Digital Humanities Conference (DH) is the main conference in Humanities Computing held annually by the ADHO in the summer. The conference is held in universities alternating each year between North America and Europe. The DH is a combined conference originally created by merging independent conferences held by the ALLC and the ACH in 1989.[http://digitalhumanities.org/conference]<br />
<br />
=== Publication ===<br />
<br />
The main publication on ADHO is "Literary & Linguist Computing - The Journal of Digital Scholarship in the Humanities" (LLC). It is a scholarly journal published quarterly at Oxford originally on behalf of the ALLC, but has since become the flagship publication of the ADHO. The journal is an international journal that covers all aspects of computing and information technology and their applications to the humanities.[http://www.allc.org/publications/llc-journal-digital-scholarship-humanities]<br />
<br />
=== Award ===<br />
<br />
ADHO oversees 4 awards for outstanding contributions. These awards are shared by the ADHO constituent.<br />
* The Roberto Busa Prize for lifetime/career achievement;<br />
* The Antonio Zampolli Prize for a singular project or accomplishment;<br />
* Conference Bursary Awards to assist students or young scholars to present at the annual conference;<br />
* The Paul Fortier Prize for the best young scholar paper of the conference.<br />
<br />
== ALLC - Association for Literary and Linguistic Computing ==<br />
<br />
The Association for Literary and Linguistic Computing was founded in 1973 and is also a founding member of the ADHO. It was created to support the application of computing in the study of language and literature. This goal has since been broadened to encompass all of the all techniques used in the Digital Humanities. Including: text analysis, language corpora, history, art history, music, manuscript studies, image processing and electronic editions. [http://www.allc.org/]<br />
<br />
The ALLC is mainly based out of Europe and supports many workshops, projects and publication in Humanities Computing studies. The ALLC's main publication the LLC was choose to be the flagship publication of the ADHO.<br />
<br />
== ACH - Association for Computer and the Humanities==<br />
<br />
The Association for Computers and the Humanities (ACH) founded in 1978 is a founding member of the ADHO. It was created to support research and to cultivate a vibrant professional community in the humanities computing. ACH is based out of the US, but also boasts an international membership.[http://www.ach.org/about-ach]<br />
<br />
ACH also provides sponsorships for students to go to conferences as well as providing funding for some projects, development, and research.<br />
=== Publication ===<br />
<br />
Digital Humanities Quarterly is an open-access journal of digital humanities published under a creative commons license, supported by ACH and the ADHO.[http://digitalhumanities.org/dhq/]<br />
<br />
== SDH-SEMI -The Society for Digital for Digital Humanities/La Société pour l'étude des Média Interactif ==<br />
<br />
The Society for Digital Humanities / Société pour l'étude des médias interactifs founded in 1986 is a the Canadian based member of the ADHO. It was originally called the Consortium for Computers in the Humanities / Consortium pour ordinateurs en sciences humaines. Its objective is to draw together humanists who are engaged in digital and computer-assisted research, teaching, and creation.<br />
<br />
The society supports interaction between scholers in both of Canada's official language(French and English), as well as providing opprotunities for publication presentation and collaboration among its members. It also supports a number of educational venues and international initiatives as well as acting as an advisory and lobbying force to local, national, and international research and research-funding bodies. SDH become a member of ADHO in 2007. [http://www.sdh-semi.org/indexE.php?page=Index-EN]<br />
<br />
=== Conference ===<br />
<br />
SDH-SEMI holds an annual Canadian conference in Humanities Computing. It began on 1997 under the name of COCH-COSH (Consortium for Computers in the Humanities/Consortium pur Ordinateurs en Sciences Humaines). Since 2006, the conference has been run under the name SDH-SEMI. The conference is hosted in the summer. <br />
<br />
=== Publication ===<br />
<br />
Digital Studies(DS) / Le champ numérique(CN) is a refereed academic open access journal published under a creative commons license. DS/CN was founded for SDH-SEMI at the Electronic Textual Cultures Lab in the University of Victoria in 2008.[http://www.digitalstudies.org/ojs/index.php/digital_studies]<br />
<br />
== centerNet ==<br />
<br />
centerNet is an international network of digital humanities centers formed for cooperative and collaborative action to benefit digital humanities and allied fields in general, and centers as humanities cyberinfrastructure in particular. It developed from a meeting hosted by the U.S. National Endowment for the Humanities and the University of Maryland, College Park, April 12-13, 2007 in Washington, D.C., and is a response to the American Council of Learned Societies report on Cyberinfrastructure for the Humanities and Social Sciences, published in 2006. Since its inception in April 2007, centerNet has added over 200 members from about 100 centers in 19 countries.[http://digitalhumanities.org/centernet/about/]<br />
<br />
centerNet will become a constituent member of the ADHO in 2012.<br />
<br />
== External Links ==<br />
<br />
* [http://digitalhumanities.org/ ADHO website]<br />
* [http://www.allc.org/ ALLC website]<br />
* [http://www.ach.org/ ACH website]<br />
* [http://digitalhumanities.org/dhq/ DHQ website]<br />
* [http://www.sdh-semi.org/ SDH-SEMI website]<br />
* [http://www.digitalstudies.org/ojs/index.php/digital_studies Digital Studies website]<br />
* [http://digitalhumanities.org/dhq/ DHQ website]<br />
* [http://digitalhumanities.org/centernet/ centerNet website]</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:ADHOCIRCA:ADHO2011-09-26T19:52:06Z<p>Recharti: /* External Links */</p>
<hr />
<div>== ADHO - Alliance of Digital Humanities Organizations==<br />
<br />
The Alliance of Digital Humanities Organizations (ADHO) is an umbrella organization that acts to promote digital research and teaching across its constitution organizations. The ADHO was officially formed in 2005 with it's two founding members the ALLC and the ACH.[http://digitalhumanities.org/]<br />
<br />
ADHO is currently comprised of four main organizations: <br />
* Association for Literary and Linguistic Computing (ALLC)<br />
* Association for Computer and the Humanities (ACH)<br />
* The Society for Digital for Digital Humanities/La Société pour l'étude des Média Interactif (SDH-SEMI)<br />
* centerNet (joining in 2012)<br />
<br />
The main purpose of the ADHO is to manage the Conferences and Publications common to all it's constituent organizations.<br />
<br />
=== Conference ===<br />
<br />
The Digital Humanities Conference (DH) is the main conference in Humanities Computing held annually by the ADHO in the summer. The conference is held in universities alternating each year between North America and Europe. The DH is a combined conference originally created by merging independent conferences held by the ALLC and the ACH in 1989.[http://digitalhumanities.org/conference]<br />
<br />
=== Publication ===<br />
<br />
The main publication on ADHO is "Literary & Linguist Computing - The Journal of Digital Scholarship in the Humanities" (LLC). It is a scholarly journal published quarterly at Oxford originally on behalf of the ALLC, but has since become the flagship publication of the ADHO. The journal is an international journal that covers all aspects of computing and information technology and their applications to the humanities. <br />
<br />
[http://www.allc.org/publications/llc-journal-digital-scholarship-humanities]<br />
<br />
=== Award ===<br />
<br />
ADHO oversees 4 awards for outstanding contributions. These awards are shared by the ADHO constituent.<br />
* The Roberto Busa Prize for lifetime/career achievement;<br />
* The Antonio Zampolli Prize for a singular project or accomplishment;<br />
* Conference Bursary Awards to assist students or young scholars to present at the annual conference;<br />
* The Paul Fortier Prize for the best young scholar paper of the conference.<br />
<br />
== ALLC - Association for Literary and Linguistic Computing ==<br />
<br />
The Association for Literary and Linguistic Computing was founded in 1973 and is also a founding member of the ADHO. It was created to support the application of computing in the study of language and literature. This goal has since been broadened to encompass all of the all techniques used in the Digital Humanities. Including: text analysis, language corpora, history, art history, music, manuscript studies, image processing and electronic editions. [http://www.allc.org/]<br />
<br />
The ALLC is mainly based out of Europe and supports many workshops, projects and publication in Humanities Computing studies. The ALLC's main publication the LLC was choose to be the flagship publication of the ADHO.<br />
<br />
== ACH - Association for Computer and the Humanities==<br />
<br />
The Association for Computers and the Humanities (ACH) founded in 1978 is a founding member of the ADHO. It was created to support research and to cultivate a vibrant professional community in the humanities computing. ACH is based out of the US, but also boasts an international membership.[http://www.ach.org/about-ach]<br />
<br />
ACH also provides sponsorships for students to go to conferences as well as providing funding for some projects, development, and research.<br />
=== Publication ===<br />
<br />
Digital Humanities Quarterly is an open-access journal of digital humanities published under a creative commons license, supported by ACH and the ADHO.[http://digitalhumanities.org/dhq/]<br />
<br />
== SDH-SEMI -The Society for Digital for Digital Humanities/La Société pour l'étude des Média Interactif ==<br />
<br />
The Society for Digital Humanities / Société pour l'étude des médias interactifs founded in 1986 is a the Canadian based member of the ADHO. It was originally called the Consortium for Computers in the Humanities / Consortium pour ordinateurs en sciences humaines. Its objective is to draw together humanists who are engaged in digital and computer-assisted research, teaching, and creation.<br />
<br />
The society supports interaction between scholers in both of Canada's official language(French and English), as well as providing opprotunities for publication presentation and collaboration among its members. It also supports a number of educational venues and international initiatives as well as acting as an advisory and lobbying force to local, national, and international research and research-funding bodies. SDH become a member of ADHO in 2007. [http://www.sdh-semi.org/indexE.php?page=Index-EN]<br />
<br />
=== Conference ===<br />
<br />
SDH-SEMI holds an annual Canadian conference in Humanities Computing. It began on 1997 under the name of COCH-COSH (Consortium for Computers in the Humanities/Consortium pur Ordinateurs en Sciences Humaines). Since 2006, the conference has been run under the name SDH-SEMI. The conference is hosted in the summer. <br />
<br />
=== Publication ===<br />
<br />
Digital Studies(DS) / Le champ numérique(CN) is a refereed academic open access journal published under a creative commons license. DS/CN was founded for SDH-SEMI at the Electronic Textual Cultures Lab in the University of Victoria in 2008.[http://www.digitalstudies.org/ojs/index.php/digital_studies]<br />
<br />
== centerNet ==<br />
<br />
centerNet is an international network of digital humanities centers formed for cooperative and collaborative action to benefit digital humanities and allied fields in general, and centers as humanities cyberinfrastructure in particular. It developed from a meeting hosted by the U.S. National Endowment for the Humanities and the University of Maryland, College Park, April 12-13, 2007 in Washington, D.C., and is a response to the American Council of Learned Societies report on Cyberinfrastructure for the Humanities and Social Sciences, published in 2006. Since its inception in April 2007, centerNet has added over 200 members from about 100 centers in 19 countries.[http://digitalhumanities.org/centernet/about/]<br />
<br />
centerNet will become a constituent member of the ADHO in 2012.<br />
<br />
== External Links ==<br />
<br />
* [http://digitalhumanities.org/ ADHO website]<br />
* [http://www.allc.org/ ALLC website]<br />
* [http://www.ach.org/ ACH website]<br />
* [http://digitalhumanities.org/dhq/ DHQ website]<br />
* [http://www.sdh-semi.org/ SDH-SEMI website]<br />
* [http://www.digitalstudies.org/ojs/index.php/digital_studies Digital Studies website]<br />
* [http://digitalhumanities.org/dhq/ DHQ website]<br />
* [http://digitalhumanities.org/centernet/ centerNet website]</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:ADHOCIRCA:ADHO2011-09-26T19:50:02Z<p>Recharti: </p>
<hr />
<div>== ADHO - Alliance of Digital Humanities Organizations==<br />
<br />
The Alliance of Digital Humanities Organizations (ADHO) is an umbrella organization that acts to promote digital research and teaching across its constitution organizations. The ADHO was officially formed in 2005 with it's two founding members the ALLC and the ACH.[http://digitalhumanities.org/]<br />
<br />
ADHO is currently comprised of four main organizations: <br />
* Association for Literary and Linguistic Computing (ALLC)<br />
* Association for Computer and the Humanities (ACH)<br />
* The Society for Digital for Digital Humanities/La Société pour l'étude des Média Interactif (SDH-SEMI)<br />
* centerNet (joining in 2012)<br />
<br />
The main purpose of the ADHO is to manage the Conferences and Publications common to all it's constituent organizations.<br />
<br />
=== Conference ===<br />
<br />
The Digital Humanities Conference (DH) is the main conference in Humanities Computing held annually by the ADHO in the summer. The conference is held in universities alternating each year between North America and Europe. The DH is a combined conference originally created by merging independent conferences held by the ALLC and the ACH in 1989.[http://digitalhumanities.org/conference]<br />
<br />
=== Publication ===<br />
<br />
The main publication on ADHO is "Literary & Linguist Computing - The Journal of Digital Scholarship in the Humanities" (LLC). It is a scholarly journal published quarterly at Oxford originally on behalf of the ALLC, but has since become the flagship publication of the ADHO. The journal is an international journal that covers all aspects of computing and information technology and their applications to the humanities. <br />
<br />
[http://www.allc.org/publications/llc-journal-digital-scholarship-humanities]<br />
<br />
=== Award ===<br />
<br />
ADHO oversees 4 awards for outstanding contributions. These awards are shared by the ADHO constituent.<br />
* The Roberto Busa Prize for lifetime/career achievement;<br />
* The Antonio Zampolli Prize for a singular project or accomplishment;<br />
* Conference Bursary Awards to assist students or young scholars to present at the annual conference;<br />
* The Paul Fortier Prize for the best young scholar paper of the conference.<br />
<br />
== ALLC - Association for Literary and Linguistic Computing ==<br />
<br />
The Association for Literary and Linguistic Computing was founded in 1973 and is also a founding member of the ADHO. It was created to support the application of computing in the study of language and literature. This goal has since been broadened to encompass all of the all techniques used in the Digital Humanities. Including: text analysis, language corpora, history, art history, music, manuscript studies, image processing and electronic editions. [http://www.allc.org/]<br />
<br />
The ALLC is mainly based out of Europe and supports many workshops, projects and publication in Humanities Computing studies. The ALLC's main publication the LLC was choose to be the flagship publication of the ADHO.<br />
<br />
== ACH - Association for Computer and the Humanities==<br />
<br />
The Association for Computers and the Humanities (ACH) founded in 1978 is a founding member of the ADHO. It was created to support research and to cultivate a vibrant professional community in the humanities computing. ACH is based out of the US, but also boasts an international membership.[http://www.ach.org/about-ach]<br />
<br />
ACH also provides sponsorships for students to go to conferences as well as providing funding for some projects, development, and research.<br />
=== Publication ===<br />
<br />
Digital Humanities Quarterly is an open-access journal of digital humanities published under a creative commons license, supported by ACH and the ADHO.[http://digitalhumanities.org/dhq/]<br />
<br />
== SDH-SEMI -The Society for Digital for Digital Humanities/La Société pour l'étude des Média Interactif ==<br />
<br />
The Society for Digital Humanities / Société pour l'étude des médias interactifs founded in 1986 is a the Canadian based member of the ADHO. It was originally called the Consortium for Computers in the Humanities / Consortium pour ordinateurs en sciences humaines. Its objective is to draw together humanists who are engaged in digital and computer-assisted research, teaching, and creation.<br />
<br />
The society supports interaction between scholers in both of Canada's official language(French and English), as well as providing opprotunities for publication presentation and collaboration among its members. It also supports a number of educational venues and international initiatives as well as acting as an advisory and lobbying force to local, national, and international research and research-funding bodies. SDH become a member of ADHO in 2007. [http://www.sdh-semi.org/indexE.php?page=Index-EN]<br />
<br />
=== Conference ===<br />
<br />
SDH-SEMI holds an annual Canadian conference in Humanities Computing. It began on 1997 under the name of COCH-COSH (Consortium for Computers in the Humanities/Consortium pur Ordinateurs en Sciences Humaines). Since 2006, the conference has been run under the name SDH-SEMI. The conference is hosted in the summer. <br />
<br />
=== Publication ===<br />
<br />
Digital Studies(DS) / Le champ numérique(CN) is a refereed academic open access journal published under a creative commons license. DS/CN was founded for SDH-SEMI at the Electronic Textual Cultures Lab in the University of Victoria in 2008.[http://www.digitalstudies.org/ojs/index.php/digital_studies]<br />
<br />
== centerNet ==<br />
<br />
centerNet is an international network of digital humanities centers formed for cooperative and collaborative action to benefit digital humanities and allied fields in general, and centers as humanities cyberinfrastructure in particular. It developed from a meeting hosted by the U.S. National Endowment for the Humanities and the University of Maryland, College Park, April 12-13, 2007 in Washington, D.C., and is a response to the American Council of Learned Societies report on Cyberinfrastructure for the Humanities and Social Sciences, published in 2006. Since its inception in April 2007, centerNet has added over 200 members from about 100 centers in 19 countries.[http://digitalhumanities.org/centernet/about/]<br />
<br />
centerNet will become a constituent member of the ADHO in 2012.<br />
<br />
== External Links ==<br />
<br />
* [http://digitalhumanities.org/ ADHO website]<br />
* [http://www.allc.org/ ALLC website]<br />
* [http://www.ach.org/ ACH website]<br />
* [http://digitalhumanities.org/dhq/ DHQ website]<br />
* [http://www.sdh-semi.org/ SDH-SEMI website]<br />
* [http://digitalhumanities.org/centernet/ centerNet website]</div>Rechartihttps://circa.cs.ualberta.ca/index.php/CIRCA:ADHOCIRCA:ADHO2011-09-26T19:09:03Z<p>Recharti: </p>
<hr />
<div>== ADHO - Alliance of Digital Humanities Organizations==<br />
<br />
The Alliance of Digital Humanities Organizations (ADHO) is an umbrella organization that acts to promote digital research and teaching across its constitution organizations.[http://digitalhumanities.org/]<br />
<br />
ADHO was founded in 2005 and is comprised of four main organizations: <br />
Association for Literary and Linguistic Computing (ALLC), Association for Computer and the Humanities (ACH), The Society for Digital for Digital Humanities/La Société pour l'étude des Média Interactif (SDH-SEMI), and centerNet (joining in 2012). <br />
<br />
The main purpose of the ADHO is to manage the Conferences and Publications common to all it's constituent organizations.<br />
<br />
=== Conference ===<br />
<br />
The Digital Humanities Conference (DH) is the main conference in Humanities Computing held annually by the ADHO in the summer. The conference is held in universities alternating each year between North America and Europe. The DH is a combined conference originally created by merging independent conferences held by the ALLC and the ACH in 1989.[http://digitalhumanities.org/conference]<br />
<br />
=== Publication ===<br />
<br />
The main publication on ADHO is "Literary & Linguist Computing - The Journal of Digital Scholarship in the Humanities" (LLC). It is a published quarterly in Oxford on behalf of the Association for Literary and Linguistic Computing and the Association for Computers and the Humanities. Literary and Linguistic Computing become the flagship publication of ADHO. It is an international journal which publishes material on all aspects of computing and information technology applied to literature and language research and teaching. [http://www.allc.org/publications/llc-journal-digital-scholarship-humanities]<br />
<br />
=== Award ===<br />
<br />
ADHO oversees 4 awards for outstanding contributions. These awards are shared by the ADHO constituent.<br />
* The Roberto Busa Prize for lifetime/career achievement;<br />
* The Antonio Zampolli Prize for a singular project or accomplishment;<br />
* Conference Bursary Awards to assist students or young scholars to present at the annual conference;<br />
* The Paul Fortier Prize for the best young scholar paper of the conference.<br />
<br />
<br />
== ALLC - Association for Literary and Linguistic Computing ==<br />
<br />
The Association for Literary and Linguistic Computing was founded in 1973 with the purpose of supporting the application of computing in the study of language and literature. As the range of available and relevant computing techniques in the humanities has increased, the interests of the Association's members have necessarily broadened, to encompass not only text analysis and language corpora, but also history, art history, music, manuscript studies, image processing and electronic editions. [http://www.allc.org/]<br />
<br />
The ALLC is based in Europe and supports many workshops, projects and publication in Humanities Computing studies. Since it is a found member of ADHO in 2005, their main publication, LLC, was choose to be the flagship publication of the ADHO.<br />
<br />
<br />
== ACH - Association for Computer and the Humanities==<br />
<br />
The Association for Computers and the Humanities (ACH) is a major professional society for the digital humanities. Its support and disseminate research and cultivate a vibrant professional community through conferences, publications, and outreach activities. ACH is based in the US, but boasts an international membership. It is also a founding member of ADHO.[http://www.ach.org/about-ach]<br />
<br />
ACH sponsor students to go to conferences and other activities and also provide funding and grants for small projects development and research.<br />
<br />
=== Publication ===<br />
<br />
Digital Humanities Quarterly is an open-access journal of digital humanities, supported by ACH and ADHO.<br />
<br />
<br />
== SDH-SEMI -The Society for Digital for Digital Humanities/La Société pour l'étude des Média Interactif ==<br />
<br />
The Society for Digital Humanities / Société pour l'étude des médias interactifs is a Canada-wide association of representatives from Canadian colleges and universities that began in 1986, founded as the Consortium for Computers in the Humanities / Consortium pour ordinateurs en sciences humaines. Its objective is to draw together humanists who are engaged in digital and computer-assisted research, teaching, and creation.<br />
<br />
The society fosters work in the digital humanities in Canada's two official languages, and champions interaction between Canada's anglophone and francophone communities, in all areas reflected by its diverse membership: providing opportunities for publication, presentation, and collaboration; supporting a number of educational venues and international initiatives; acting as an advisory and lobbying force to local, national, and international research and research-funding bodies; working with allied organisations; and beyond. SDH become a member of ADHO in 2007. [http://www.sdh-semi.org/indexE.php?page=Index-EN]<br />
<br />
=== Conference ===<br />
<br />
SDH-SEMI held a canadian annual conference. in Humanities Computing. It began on 1997 under the name of COCH-COSH (Consortium for Computers in the Humanities/Consortium pur Ordinateurs en Sciences Humaines). Since 2006, the conference change the name to SDH-SEMI. The conference is hosted in the summer. <br />
<br />
=== Publication ===<br />
<br />
Digital Studies(DS) / Le champ numérique(CN) is a refereed academic journal serving as a formal arena for scholarly activity and as an academic resource for researchers in the digital humanities. DS/CN was founded for SDH-SEMI at the Electronic Textual Cultures Lab, University of Victoria, in 2008.[http://www.digitalstudies.org/ojs/index.php/digital_studies]<br />
<br />
<br />
== centerNet ==<br />
<br />
centerNet is an international network of digital humanities centers formed for cooperative and collaborative action to benefit digital humanities and allied fields in general, and centers as humanities cyberinfrastructure in particular. It developed from a meeting hosted by the U.S. National Endowment for the Humanities and the University of Maryland, College Park, April 12-13, 2007 in Washington, D.C., and is a response to the American Council of Learned Societies report on Cyberinfrastructure for the Humanities and Social Sciences, published in 2006. Since its inception in April 2007, centerNet has added over 200 members from about 100 centers in 19 countries.[http://digitalhumanities.org/centernet/about/]<br />
<br />
centerNet will become a constituent member of the ADHO in 2012.<br />
<br />
== External Links ==<br />
<br />
* [http://digitalhumanities.org/ ADHO website]<br />
* [http://www.allc.org/ ALLC website]<br />
* [http://www.ach.org/ ACH website]<br />
* [http://www.sdh-semi.org/ SDH-SEMI website]<br />
* [http://digitalhumanities.org/centernet/ centerNet website]</div>Recharti