Providing Social Science Data Services: Strategies for Design and Operation
This five-day workshop is being offered to individuals who manage or support local services for ICPSR and other research data for quantitative analysis. Those who should attend include anyone who is new to providing social science data services or who is seeking to revitalize an existing service. We believe that this workshop will also be useful to those outside the social sciences who are responsible for providing access to research data in other domains.
Major recent changes in the global research environment are challenging governmental and higher educational institutions to look at how they plan and design appropriate levels of local data services. Driving this has been the widespread recognition of the increased value of research data and the push for organizations to manage data assets better. One clear institutional response has been to engage in activities associated with data curation, including data access, data preservation, data management, collections management, and user services.
This workshop is structured around a five-stage data lifecycle model focused on data production, dissemination, repositories, discovery, and repurposing. Data curation activities are presented for each stage of this model, using presentations to discuss local data service issues and computer exercises to demonstrate service activities. In this context, fundamental data topics are covered, including conducting a data reference interview, interpreting data documentation, understanding variables, coping with various dissemination formats, accessing different online services (e.g., SDA and Nesstar), searching for social science data, subsetting data using Web-based tools, selecting and downloading ICPSR data, and options for local data delivery. The final day of the workshop concludes with an exercise in designing a data service based on the dimensions of access/preservation and collections/services.
Note: This is not a course in statistical analysis and attendees are not expected to know how to use statistical software.
Fee: Members = $1500; Non-members = $3000