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Akmon, D.
(2014). The Role of Conceptions of Value in Data Practices: A Multi-Case Study of Three Small Teams of Ecological Scientists.
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Investigated how scientists conceive of the value of their data, and how they enact conceptions of value in their data practices |
Conducted interviews and engaged in participant observation of three teams of scientists performing ecological research at a U.S. university-sponsored field station |
Measurement, Targeted |
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Beagrie, N., & Houghton J.
(2013). The Value and Impact of the Archaeology Data Service: A Study and Methods for Enhancing Sustainability.
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Investigated and attempted to measure the value and impact of the Archaeology Data Service (ADS) |
Reviewed value and impact evaluation literature; analyzed ADS reports and documentation; conducted 15 interviews with ADS stakeholders; conducted 2 online surveys, one of ADS data depositors and one of ADS users
Note: This study and the similar study of the British Atmospheric Data Centre (Node 34) both use the same value metrics framework |
Measurement, Metrics, Targeted |
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Beagrie, N., & Houghton J.
(2013). The Value and Impact of the British Atmospheric Data Centre.
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Surveyed and analyzed perceptions of the value of the digital collections held by the British Atmospheric Data Centre (BADC), and quantified the value and impact of those collections for BADC’s user community using a range of economic approaches; investigated the extension of the methodology used in Beagrie et al. 2012 and Beagrie and Houghton 2013a to the BADC.
Note: The results of Beagrie et al. 2012, Beagrie and Houghton 2013a and Beagrie and Houghton 2013b were summarized and collated in Beagrie and Houghton 2014. |
Similar to Beagrie et al. 2012 and Beagrie and Houghton 2013, methods included a combination of literature and documentation review, review of reports from BADC, 13 interviews of BADC users and depositors, and two online surveys, one of BADC data depositors and one of BADC users.
Note: This study and the similar study of the Archaeology Data Service (Node 33) both use the same value metrics framework |
Measurement, Targeted |
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Gibbs, H.
(2009). Southampton Data Survey: Our Experience and Lessons Learned.
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To pilot the Digital Asset Framework (or Digital Audit Framework) methodology |
Used a modified version of the Digital Asset Framework; modified mainly due to time considerations; distributed an online questionnaire and follow-up interviews with researchers at the University of Southampton |
Measurement, Wider |
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Jerrome, N., & Breeze J.
(2009). Imperial College Data Audit Framework Implementation: Final Report.
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To pilot the Digital Asset Framework Methodology; evaluate the scale and scope of research data; and make recommendations accordingly |
Used a modified form of the Digital Asset Framework in multiple departments: used the audit framework in a first phase of investigation, then conducted an online survey and follow up interviews. |
Measurement, Wider |
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Kuipers, T., & van der Hoeven J.
(2009). PARSE.Insight: Insight into Digital Preservation of Research Output in Europe: Survey Report.
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Sought to gain insight into issues surrounding the preservation of digital research data; investigated amount of data stored by researchers in Europe in 2008 or 2009 and amounts projected two and five years into the future |
Data was obtained from a question in a larger survey designed to gain insight into infrastructure needed for digital preservation |
Measurement, Wider |
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Open Exeter Project Team
(2012). Summary Findings of the Open Exeter Data Asset Framework Survey.
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Investigated how researchers at the University of Exeter created data, where they stored their data, whether they backed up their data and what happened to their data when the project was finished |
Adapted from the Data Curation Centre’s Data Asset Framework methodology, an online survey was created and follow up interviews were conducted with respondents. |
Measurement, Wider |
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Scaramozzino, J., Ramírez M., & McGaughey K.
(2012). A Study of Faculty Data Curation Behaviors and Attitudes at a Teaching-Centered University.
College & Research Libraries. 73(4), 349 - 365. |
Investigated science researchers’ data curation awareness, behaviors, and attitudes, as well as what needs they exhibited for services and education regarding maintenance and management of data |
Distributed survey via email to 331 College of Science and Mathematics faculty at California Polytechnic State University, San Luis Obispo (Cal Poly), a master’s-granting, teaching-centered institution. Filtered results to include only science faculty from the Biology, Chemistry, Kinesiology, Mathematics, Physics, and Statistics departments who engaged in data collection in the course of their research (131 tenure-track faculty; 82 responded (62.6%) |
Measurement, Wider |
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Waller, M., & Sharpe R.
(2006). Mind the Gap: Assessing Digital Preservation Needs in the UK.
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A study carried out for the Digital Preservation Coalition (DPC) to reveal the extent of the risk of loss or degradation to digital material held in the UK's public and private sectors |
Surveyed 900 individuals from a wide range of organisations in different sectors. The selected individuals all had an assumed interest in digital preservation as part of their professional responsibilities, and included a range of roles including records managers, archivists, librarians, but also IT managers and data producers. 104 responses were received, giving a good response rate of over 10%. These included respondents from education, libraries, archives, museums, local and central government bodies, scientific research institutions, and from organisations in the pharmaceutical, financial, manufacturing and engineering, media, energy and chemical, and publishing sectors.
Note: Discusses duration for keeping data.
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Measurement, Wider |
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Wynholds, L., Fearon, Jr. D. S., Borgman C. L., & Traweek S.
(2011). When Use Cases Are Not Useful: Data Practices, Astronomy, and Digital Libraries.
383 - 386. |
Sought to understand issues in developing the institutions and practices needed to provide access to research data |
Conducted interviews of users of the SDSS dataset covering their type of research, participation in sky survey projects, data challenges, conceptions of data, data sources, data analysis tools, walk-throughs, end of project curation, and funding structures for data |
Measurement, Wider |
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Beagrie, N., & Houghton J.
(2012). Economic Impact Evaluation of the Economic and Social Data Service.
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Sought to (i) evaluate the economic benefits and impact of ESDS; and (ii) contribute to the further development of impact evaluation methods that can provide ESRC with robust estimates of the economic benefits of its data service infrastructure investments |
Conducted (i) desk-based analysis of existing evaluation literature and reports, looking at both methods and findings; (ii) existing data from KRDS and other studies; (iii) existing management and internal data collected by ESRC and ESDS such as user statistics, internal reports, and the ESDS Mid-Term Review; and (iv) original data collection in the form of semi-structured interviews, case studies, and an online survey of ESDS users and depositors |
Measurement, Metrics, Targeted |
