Content Curation for Research: A Framework for Building a “Data Museum”

  • San Cannon


In the current digital age, data are everywhere and are continually being created, collected and otherwise captured by a range of users for a variety of applications. Curating digital content is a growing concern both for business users and academic researchers. Selecting, collecting, preserving and archiving digital assets, especially research data sets, are important steps in the research life cycle and can help expand the boundaries of research by allowing data to be reused. Creating research data sets often starts with selecting input data sources; in this age of new or “big” data, that choice set keeps expanding, thereby making it more difficult and time consuming to discover and understand the vast data landscape when beginning an empirical research project.

This paper proposes an approach to make finding and learning about data easier and less time-consuming for researchers. While cognizant of the role of digital curation for research data sets, we focus on the traditional “museum” definition of curation to outline how data-oriented content curation can support research. The process of selecting, evaluating and presenting information about potential data inputs can help researchers more easily understand how certain data sets are used and better determine which data sources might be fit for their purposes. Although the paper draws on examples from economics citing U.S. data, the techniques could be used across disciplines and countries.

Author Biography

San Cannon

Associate Director, Center for the Advancement of Data and Research in Economics, Federal Reserve Bank of Kansas City

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