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Datasets

The Scholars Studio also gathers and curates data sets for study and analysis. These include a wide-variety of publicly available datasets, as well as data scraped from various media sources. Besides these born-digital datasets, we also curate collections as data.

Sci-Fi Literature

In collaboration with the Special Collections Research Center, the Scholars Studio has been working to digitize novels and magazines from the Paskow Science Fiction Collection. These image and text files are available for students and teachers to use for research and teaching purposes. 

Because these materials are under copyright, they can only be accessed through a visit to the Scholars Studio, where users will be required to sign an agreement form to only use these materials at the Scholars Studio for non-consumptive research.

Over two hundred titles have been ingestedinto the HathiTrust Digital Library, and they are now available to access on the Temple University page!

Temporary full-view access is available for Temple library account holders during the COVID-19 emergency. Non-consumptive, computational research can be conducted with the HTRC Analytics tool.

If you would like to learn more about ways this corpus can be used for text mining and image analysis, please visit our blog.

If you would like to access this corpus, please contact Alex Wermer-Colan at alex.wermer-colan@temple.edu.

Gen Con

The Gen Con Database includes searchable and downloadable data from all 50 programs of the Gen Con gaming convention. Covering 50 years and over a quarter million Gen Con events, the database offers an exciting glimpse into gaming history and trends. The data set is publicly available.

Canonical Literature

The Twentieth-Century English Literature Corpus contains plain text files of over 300 twentieth century canonical novels, as well as a set of science fiction novels.  Due to copyright, it is only available to Temple University affiliates. Contact the Scholars Studio to learn more about future projects aimed to increase access to the data set.