Data accessibility; open research; transparency; replication; knowledge accumulation
National Science Foundation
Library and Information Science | Other Social and Behavioral Sciences | Political Science
This chapter argues that these benefits will accrue more quickly, and will be more significant and more enduring, if researchers make their data “meaningfully accessible.” Data are meaningfully accessible when they can be interpreted and analyzed by scholars far beyond those who generated them. Making data meaningfully accessible requires that scholars take the appropriate steps to prepare their data for sharing, and avail themselves of the increasingly sophisticated infrastructure for publishing and preserving research data. The better other researchers can understand shared data and the more researchers who can access them, the more those data will be re-used for secondary analysis, producing knowledge. Likewise, the richer an understanding an instructor and her students can gain of the shared data being used to teach and learn a particular research method, the more useful those data are for that pedagogical purpose. And the more a scholar who is evaluating the work of another can learn about the evidence that underpins its claims and conclusions, the better their ability to identify problems and biases in data generation and analysis, and the better informed and thus stronger an endorsement of the work they can offer.
Kapiszewski, Diana, and Sebastian Karcher. 2020. “Making Research Data Accessible.” In The Production of Knowledge: Enhancing Progress in Social Science, edited by Colin Elman, James Mahoney, and John Gerring, 197–220. Strategies for Social Inquiry. Cambridge: Cambridge University Press. https://doi.org/10.1017/9781108762519.008.
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