Content curation for research: a framework for building a "data museum".

Cannon, San

Abstract

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 datasets, are important steps in the research life cycle and can help expand the boundaries of research by allowing data to be reused. Creating research datasets 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 datasets, 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 datasets are used, and better determine which data sources might be fit for their purposes. Although the paper draws on examples from economics citing US data, the techniques could be used across disciplines and countries.

Citation

CANNON, S. 2015. Content curation for research: a framework for building a "data museum". International journal of digital curation [online], 10(2), pages 58-68. Available from: https://doi.org/10.2218/ijdc.v10i2.355

• Journal Article Type: Article
• Acceptance Date: Apr 30, 2015
• Online Publication Date: Jul 28, 2015
• Publication Date: Dec 31, 2015
• Deposit Date: Aug 22, 2023
• Publicly Available Date: Oct 27, 2023
• Journal: International journal of digital curation
• Electronic ISSN: 1746-8256
• Publisher: Digital Curation Centre
• Peer Reviewed: Peer Reviewed
• Volume: 10
• Issue: 2
• Pages: 58-68
• DOI: https://doi.org/10.2218/ijdc.v10i2.355
• Keywords: Open data; Data repositories; Data selection; Data preservation; Datasets
• Public URL: https://rgu-repository.worktribe.com/output/2048689