In preparing for the 2016 eDesiderata Forum , CRL has consulted various articles and reports to understand the current practices and major challenges in selecting, licensing, and providing access to “big data” eResources in academic environments. The following provide some insights into the circumstances and processes involved in providing scholars access to big data.
- Cooley, Savannah; Lafia, Sara; Medrano, Antonio; Stephens, Denise; Kuhn, Werner. Spatial Discovery Expert Meeting, Final Report. (2015) Center for Spatial Studies University of California Library.
Summary of the two-day 2015 expert meeting on “Spatial Discovery”; 24 participants explored the challenges, best practices, and potential strategies associated with the cross-platform discovery of spatial data in the context of modern libraries.
- Kanous, Alex; Brock, Elaine. Contractual Limitations on Data Sharing (2015) Inter-university Consortium for Political and Social Research (ICPSR), University of Michigan.
An in-depth review of exemplar data sharing, data license, non-disclosure, and other forms of agreements under which data are made available for research use.
- Kanous, Alex. Brock, Elaine. Model Data Sharing Agreement. (2015) Inter-university Consortium for Political and Social Research (ICPSR), University of Michigan. George Alter (Principal Investigator), Alfred P. Sloan Foundation Grant Number 2012-6-11. DOI: 10.3886/Model Data Sharing Agreement
Customizable data sharing model created as part of the "Building Community Engagement for Open Access to Data" project at ICPSR.
- Ruggles, Steven. “Big Microdata for Population Research,” Demography, 51: 287-297 (2013) .
Describes the expansion of individual-level population data for academic research, including: the original development of microdata by the U.S. Census Bureau; new microdata from international statistical agencies and historical sources; and the emergence of restricted-access microdata.
- Trimble, Leanne; Woods, Cheryl; Berish, Francine; Jakubek, Daniel; and Simpkin, Sarah, Collaborative Approaches to the Management of Geospatial Data Collections in Canadian Academic Libraries: A Historical Case Study (2015).Western Libraries Publications. Paper 47.
Report on the collaborative efforts and projects of the Ontario Council of University Libraries (OCUL) in meeting the evolving requirements for managing geospatial data collections. The OCUL projects have resulted in the creation of new technical infrastructures and strategies for sharing the workload of data management tasks. The paper offers some suggestions for others considering embarking on collaborative geospatial data management projects.
- Capitalizing on Big Data: Toward a Policy Framework for Advancing Digital Scholarship in Canada. The Social Sciences and Humanities Research Council, The Canadian Institutes of Health Research, The Natural Sciences and Engineering Research Council, The Canada Foundation for Innovation (2013).
Proposal from Canadian research funding agencies for implementing policy changes for data management in response to the growing importance of big data in academic research.
See also posts from Common Knowledge, the CRL blog
Big Data: Uncharted Territory.
“What distinguishes Big Data resources from other scholarly resources, aside from the sheer volume of content involved, is that libraries are a relatively small sector of the market for such information.” Exploration of common issues and recent accomplishments in providing access to big data resources for scholarly research, with particular attention to population and census data.