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Assessing the Scientific Benefits of Interdisciplinary Use of Social Science Data through Citation Analysis

Presenter 1
Robert S. Chen
Presenter 2
Joe Schumacher
Presenter 3
Bob Downs
Presenter 4
Chris Lenhardt

Those operating data center activities are often called upon to justify the value of their work in terms of the scientific impact of the data they manage. Although anecdotal evidence of the use and importance of such data is often available, providing quantitative measures of such benefits is difficult. The increased availability of full-text search tools of scientific literature opens up the possibility of more systematic citation analysis to characterize data use by the broader scientific community. We report here on our exploratory efforts to compare alternative search strategies for selected socioeconomic datasets and examine possible citation metrics that could form the basis for assessing usage and impacts over time. These efforts also suggest some possible avenues for encouraging scientists to improve their citation of data, for improving literature databases and search tools, and for developing unique identifiers for datasets. The ability to track and quantify citations to digital content is also likely to be important for other uses such as career advancement and assessment of data quality.

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