Abstract
This paper develops and tests a lifecycle model for the preservation of research data by investigating the research practices of scientists. This research is based on a mixed-method approach. An initial study was conducted using case study analytical techniques; insights from these case studies were combined with grounded theory in order to develop a novel model of the Digital Research Data Lifecycle. A broad-based quantitative survey was then constructed to test and extend the components of the model. The major contribution of these research initiatives are the creation of the Digital Research Data Lifecycle, a data lifecycle that provides a generalized model of the research process to better describe and explain both the antecedents and barriers to preservation. The antecedents and barriers to preservation are data management, contextual metadata, file formats, and preservation technologies. The availability of data management support and preservation technologies, the ability to create and manage contextual metadata, and the choices of file formats all significantly effect the preservability of research data.
Highlights
Computer-based technology has greatly increased the quantity of research data. This data deluge is becoming an important area of study in computer science, information science, and domain sciences
Data is highly dependent on the research methodologies; methodologies have a major impact on the Digital Research Data Lifecycle
The Digital Research Data Lifecycle is a complex interaction of content, formats, context, quality control, data collections, and the technical infrastructure of the researcher’s home institution
Summary
Computer-based technology has greatly increased the quantity of research data. This data deluge is becoming an important area of study in computer science, information science, and domain sciences. One of the primary areas of study in this emerging field is data preservation; that is, the ability to provide long term access to the data for reuse. Multiple reasons justify this growing interest in digital data preservation: the data itself has significant scientific value; it can be reused to fuel new ideas and insights (Association of Research Libraries [ARL], 2006; National Science Board [NSB], 2005; Tibbo, 2014); it is an integral part of the scientific record as evidence of the rhetorical structure of scholarly communication (Rusbridge, 2007; Swan and Brown, 2008); it is necessary for replication and validation of scientific results (Swan and Brown, 2008); the data has significant economic value as intellectual capital, an important and invaluable resource that can be used repeatedly (ARL, 2006; Rumsey, 2006); and scientific digital data is a generalized good in that society benefits both directly and indirectly when this data is available for citizen scientists, for teaching, for commercial reuse, and for policy development (Lord and Macdonald, 2003; Rumsey, 2010). New research is needed to describe, measure, and mitigate the “obstacles to the longevity of digital materials” (Ross, 2007)
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