Abstract
A cross‐disciplinary examination of the user behaviors involved in seeking and evaluating data is surprisingly absent from the research data discussion. This review explores the data retrieval literature to identify commonalities in how users search for and evaluate observational research data in selected disciplines. Two analytical frameworks, rooted in information retrieval and science and technology studies, are used to identify key similarities in practices as a first step toward developing a model describing data retrieval.
Highlights
Open research data are touted as having the potential to transform science and fast-track the development of new knowledge (Gray, 2009)
We identify major frames used in the literature to discuss data evaluation criteria, including trust, quality, necessary contextual information, and relevance
Shown that a framework based on interactive information retrieval (IR) is applicable to understanding the data retrieval literature
Summary
Open research data are touted as having the potential to transform science and fast-track the development of new knowledge (Gray, 2009). In order for data to fulfill this potential, users must first be able to find the data that they need. Facilitating data discovery relies on developing underlying infrastructures, support systems, and data supplies (Borgman, 2015). It is important to understand the behaviors involved in data retrieval, but a user-focused, cross-disciplinary analysis of data retrieval practices is lacking. This review explores the existing data retrieval literature and identifies commonalities in documented practices among users of observational data as a first step toward creating a model describing how users search for and evaluate research data
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