The Significance of Time and Place: Preserving Virtual Worlds and Carmen Sandiego Rhiannon Bettivia, Doctoral Student  Preserving Virtual Worlds II: IMLS.

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Presentation transcript:

The Significance of Time and Place: Preserving Virtual Worlds and Carmen Sandiego Rhiannon Bettivia, Doctoral Student  Preserving Virtual Worlds II: IMLS Grant Partnership between University of Illinois, Stanford, Rochester Institute of Technology, and University of Maryland  Primary question: How do we determine what is significant about games and thus what about them needs to be preserved?  One end deliverable: Wiki questionnaire

Good vs. Good Enough vs. Perfection Emulation or Recreation? Old code versus new code? Unrealistic expectation of new technologies?

Carmen Sandiego Significant about the object itself Significance derived from interviews “Well the formula was really travelling around collecting stuff. Right? And the books were just used to cut the facts of whatever you collected.” “…Broderbund was very much involved and a real successful leader in the school market. So we were developing games very very much with the idea that it would be an acceptable product in a school setting… So we really did have to use a reference material that was you know a good hefty source of a lot of clues.” Players, fans, and even academics

How significant is Time? Place? US-centrism School setting of original media Gender? Carmen Good guys and bad guys Chiefs Race? Carmen Sandiego Junior Detective Carmen Sandiego Deluxe Edition

Where this research is headed… Documentation! How does significance not embodied in the object itself fit within existing typologies of data? The National Research Council (1999) defines data as “facts, numbers, letters, and symbols that describe an object, idea, condition, situation, or other factors” (p. 15). The National Science Board (2005) uses the term “data” to refer to “any information...including text, numbers, images, video or movies, audio, software, algorithms, equations, animations, models, simulations, etc.” (p. 13). The National Science Foundation classifies data into four types: (1) observational data (e.g., weather measurements and attitude surveys); (2) computational data (e.g., results from computer models and simulations); (3) experimental data (e.g., results from laboratory studies); and (4) records (e.g., from government, business, and public and private life) (Borgman, 2010, p. 19).