“Garbage Bags Full of Files”: Exploring Sociotechnical Perceptions of Formats within the Recovery and Reuse of Scientific Data

Author:

Wagner Travis L.1,Fenlon Katrina1,Sorensen Amanda1

Affiliation:

1. University of Maryland USA

Abstract

ABSTRACTThis paper explores the social and technical perceptions of physical and digital formats as they relate to work in the recovery and reuse of scientific data, specifically historical, archival, and defunct data sources. Proprietary and obsolete formats, or formats that need significant transformation work, stand out as central challenges for scientists and data curators who are recovering reusable data from archival or legacy data sources. The challenges confronting data sharing and reuse of contemporary scientific data are already known to be myriad; formats often pose a major, compounding challenge to retrospective data curation research and practice. Based on 23 qualitative interviews with practitioners conducting data recovery and reuse, ranging from marine biologists to data librarians, we study how they understand, engage with, and utilize formats within their data curation work. This paper enumerates the formats deployed throughout the scientific data curation process and explores how practitioners creating and curating scientific data based on historical and archival materials encounter, make sense of, and utilize formats. The paper focuses on practitioner perceptions of formats around the following themes: how practitioners' historical relationships to certain challenging formats inform their ongoing curation practices; the importance of contexts in prioritizing or ignoring formats within scientific curation work; and how formats reveal larger sociotechnical issues. The paper concludes by with practical and theoretical implications of navigating formats within the recovery and reuse of scientific data and offers suggestions for reconfiguring formats within broader data curation lifecycles.

Publisher

Wiley

Subject

Library and Information Sciences,General Computer Science

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