Workshop : Using CatMapper
- Long title
- Using CatMapper to translate and merge data by complex categories
- Starts at
- Sun, Oct 20, 2024, 14:00 EDT
- Finishes at
- Sun, Oct 20, 2024, 17:30 EDT
- Venue
- BL 313
- Moderator
- Inkyung Choi
Moderator
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Inkyung Choi
OCLC
Inkyung Choi received her MLIS at Syracuse University and PhD at the University of Wisconsin-Milwaukee. She served as a teaching assistant professor and taught metadata, linked data, information modeling, information organization at the School of Information Sciences at the University of Illinois Urbana-Champaign. She currently serves on DCMI education committee and actively engages with members of metadata community worldwide. Her research interests are knowledge organization, metadata, ontology, and linked data.
Using CatMapper to translate and merge data by complex categories
Explore how the CatMapper app (https://www.catmapper.org/js) can assist users in translating and merging data across diverse datasets by complex, dynamic, and hierarchically organized categories (e.g., ethnicity, religion, language, and subdistricts). In this workshop, we will engage in hands-on activities to introduce users to CatMapper’s key functions, including: (1) exploring details about specific categories (e.g., ethnicities) and where data is available on them, (2) translating categories across datasets, (3) merging data from diverse sources for novel analyses, and (4) sharing the details of these merges for others to re-use or replicate.
The workshop does not require any prior knowledge or expertise. Please bring a laptop so that we can walk through examples and hands-on activities together. If you will be attending, and would like to be given pre-workshop access to materials used in the hands-on activities, please email Dan Hruschka one week before the workshop ([email protected]).
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Daniel Hruschka
Arizona State University
Dr. Dan Hruschka is a Professor of Global Health and Anthropology at Arizona State University. Much of Dan’s research focuses on how social and economic inequalities produce health disparities worldwide. This research relies on bringing together data from diverse, international datasets by complex categories, such as ethnicity, languages, and religions. To help researchers tackle the thorny challenge of data synthesis by these complex categories, Dan is leading a team to develop user-friendly, web-based tools (CatMapper, https://www.catmapper.org/js) that enable researchers to search and translate categories across datasets and share these translations with others.
