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Discovery and Evaluation of Social Science Data Sources
February 10, 2021 @ 2:00 pm - 3:00 pm
Governments, non-governmental organizations, and social scientists have amassed vast collections of data about the social world. Learn how to discover, evaluate, and access sources available for new analyses and visualizations.
Registration is required. You will receive a confirmation once you are accepted into the workshop and a communication with the workshop materials and Zoom links. This workshop is open to all members of the UC community. UC Davis DataLab Affiliates receive priority registration.
Social Scientists use data and statistics to trace, understand, and make predictions about the social world. These sources, historical and contemporary, have been both gathered regularly by governments and NGO’s, and intermittently or singularly by social scientists. In this session, we will explore different methods for locating and evaluating data sources, across institutions, in dataset libraries and repositories, and in the scholarly record. We will also look at possibilities for the discovery relevant data in unexpected sources.
By the end of this workshop attendees will be able to:
- navigate and extract data from government and NGO data sources on the international, federal, and state level.
- explore and evaluate social science data repositories, such as ICPSR and Dataverse.
- discover and search the growing collection of licensed data collections at UC Libraries, including primary sources, and indexes to data sources.
- find and track down data sources from the scholarly record and other unexpected sources.
None! Researchers from all domains are welcome to attend.
David Michalski is a Librarian in the UC Davis Library Research Services Department. He specializes in assisting faculty and graduate students across the social and cultural studies.
- February 10, 2021
2:00 pm - 3:00 pm
- Event Categories:
- Events_Sidebar, Workshop
- Event Tags:
- Data Visualization, DataLab Event, Workshop
- DataLab: Data Science and Informatics (DSI)