| Autor: |
Hruschka, Daniel1 dhruschk@asu.edu, Cheng, Yi‐Yun2 yiyun.cheng@rutgers.edu, Hsiao, I‐Han3 ihsiao@scu.edu, Bischoff, Robert1 bischrob@gmail.com, Peeples, Matthew1 Matthew.Peeples@asu.edu, Kasi, Harsha3 hkasi@scu.edu, Huang, Cindy1 CindyHYHuang@asu.edu |
| Předmět: |
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| Zdroj: |
Proceedings of the Association for Information Science & Technology. Oct2024, Vol. 61 Issue 1, p934-936. 3p. |
| Abstrakt: |
A key challenge in conducting comparative analyses across social units, such as religions, ethnicities, or cultures, is that data on these units is often encoded in distinct and incompatible formats across diverse datasets. This can involve simple differences in the variables and values used to encode these units (e.g., Roman Catholic is V130 = 1 vs. Q98A = 2 in two different datasets) or differences in the resolutions at which units are encoded (Maya vs. Kaqchikel Maya). These disparate encodings can create substantial challenges for the efficiency and transparency of data syntheses across diverse datasets. We introduce a user‐friendly set of tools to help users translate four kinds of categories (religion, ethnicity, language, and subdistrict) across multiple, external datasets. We outline the platform's key functions and current progress, as well as long‐range goals for the platform. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Library, Information Science & Technology Abstracts |
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