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Beagrie, N., Houghton J., Palaiologk A., & Williams P.
(2012). Economic Evaluation of Research Data Infrastructure.
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Investigated the economic benefits of investments of the Economic and Social Research Council (ESRC) in the Economic and Social Data Service (ESDS), a service that promotes use of research data and teaching in social sciences to ensure data availability. |
Performed analysis of existing evaluation literature and reports, looking at both methods and findings; examined results of KRDS and other studies; examined management and internal data collected by ESRC and ESDS such as user statistics, internal reports, and the ESDS Mid-Term Review; performed semi-structured interviews, case studies, and an online survey of ESDS users and depositors |
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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Belter, C. W.
(2014). Measuring the Value of Research Data: A Citation Analysis of Oceanographic Data Sets.
PLoS ONE. 9(3), e92590. |
Investigated the value of data curation as evidenced by the bibliometric impact of curated and openly accessible data sets at the National Oceanographic Data Center |
Compiled citation counts for three highly-used datasets in Web of Science, several journal publisher websites, and Google Scholar; performed a more detailed investigation into citations counts in the same sources of all versions of one dataset in particular |
Measurement, Targeted |
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K. Fear, M.
(2013). Measuring and Anticipating the Impact of Data Reuse.
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Identified citation patterns among data reusers; developed and demonstrated a suite of data reuse impact metrics; and explored factors that influence whether or not a dataset is reused, as well as what impact its reuse has. |
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Measurement, Metrics, Targeted |
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Federer, L., Lu Y-L., Joubert D., Welsh J., & Brandys B.
(2015). Biomedical Data Sharing and Reuse: Attitudes and Practices of Clinical and Scientific Research Staff.
PLoS ONE. 10(6), |
Investigated differences in experiences with and perceptions about sharing data, as well as barriers to sharing among clinical and basic science researchers |
Distributed a survey to Clinical and basic science researchers in the Intramural Research Program at the National Institutes of Health. The survey was publicized through various NIH email lists, including NIH library and NIH special interest groups. Of 190 respondents, 135 who identified as clinical or basic science researchers were included in analysis.
Asked: Reuse (how relevant was their work and level of expertise); Relevance and expertise regarding depositing data in a repository; uploading data to a repository; sharing practices (metadata, codebook, processing); acknowledgement for sharing; reasons for not sharing |
Measurement, Targeted |
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Fry, J., Lockyer S.., Oppenheim C.., Houghton J.W.., & Rasmussen B..
(2008). Identifying benefits arising from the curation and open sharing of research data produced within UK Higher Education and research institutes: exploring costs and benefits.
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Investigated the benefits of the curation and open sharing of research data and the development of a methodology and model for estimating the benefits of data curation and sharing in UK higher education |
Performed a literature review to provide illustrative examples of reuse and the views of stakeholders in various disciplines towards data curation and sharing; conducted two case studies to identify and illustrate benefits and costs in these areas |
Measurement, Metrics, Wider |
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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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Kejser, U. Bøgvad, Johansen K. Hougaard E., Thirifays A., Nielsen A. Bo, Wang D., Strodl S., et al.
(2014). 4C Project: Evaluation of Cost Models and Needs & Gaps Analysis.
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4C Project: Analyzed research related to the economics of digital curation and cost and benefit modelling; investigated how well current models and tools meet stakeholders’ needs for calculating and comparing financial information; pointed out gaps to be bridged to increase the uptake of cost & benefit modelling and practices that will enable costing and comparison of the costs of alternative scenarios |
Evaluated and compared ten current and emerging cost and benefit models; performed consultations (in the form of a questionnaire) with 4C project stakeholders; 296 contacts were made and 164 responded (55% response rate) |
Measurement, Targeted |
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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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McLure, M., Level A., Cranston C., Oehlerts B., & Culbertson M.
(2014). Data Curation: A Study of Researcher Practices and Needs.
portal: Libraries and the Academy. 14(2), 139 - 164. |
Investigated (1) the nature of data sets that researchers create or maintain; (2) How participants manage their data; (3) Needs for support that the participants identify in relation to sharing, curating, and preserving their data; and (4) The feasibility of adapting the Purdue University Libraries’ Data Curation Profiles Toolkit1 interview protocol for use in focus groups with researchers |
Conducted five focus groups with 31 faculty, research scientists, and research associates |
Measurement, Wider |
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Piwowar, H. A., Vision T. J., & Whitlock M. C.
(2011). Data archiving is a good investment.
Nature. 473(7347), 285. |
Estimated the cost of archiving data using Dryad; estimated reuse of data |
Cost: method not given; Reuse: searched the full text of articles in PubMed Central for mention of datasets in the Gene Expression Omnibus (GEO) database |
Measurement, Targeted |
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Piwowar, H. A., & Vision T. J.
(2013). Data reuse and the open data citation advantage.
PeerJ. 1, e175. |
Investigated the extent to which the article citation is affected by the availability of research data. |
Performed multi-variate regression on 10,555 studies that produced gene expression microarray data using date of publication, journal impact factor, open access status, number of authors, first and last author publication history, corresponding author country, institution citation history, and study topic as covariates; examined patterns of reuse of data in the GEO database based on mentions in articles in PubMed Central; extrapolated from patterns of reuse of data in the GEO database in PubMed Central to estimate GEO data reuse in all of PubMed between 2000 and 2010 |
Measurement, Targeted |
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Read, K. B., Sheehan J. R., Huerta M. F., Knecht L. S., Mork J. G., Humphreys B. L., et al.
(2015). Sizing the Problem of Improving Discovery and Access to NIH-Funded Data: A Preliminary Study.
PLoS ONE. 10(7), e0132735. |
Investigated the discovery of and access to biomedical datasets to provide a preliminary estimate of the number and type of datasets generated annually by research funded by the U.S. National Institutes of Health (NIH); specifically those that are “invisible” or not deposited in a known repository |
Analyzed NIH-funded journal articles that were published in 2011, cited in PubMed and deposited in PubMed Central (PMC) to identify articles where data were submitted to a known repository; excluded these and analyzed a random sample of the remaining articles to estimate how many and what types of invisible datasets were used in each article |
Measurement, Targeted |
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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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Science Staff
(2011). Challenges and Opportunities.
Science. 331(6018), 692 - 693. |
Investigated issues surrounding the growing amounts of research data that exist |
Performed a survey of Science peer reviewers, receiving 1,700 responses; asked about frequency of use of datasets from published literature and archival databases, the size of the largest dataset used or generated, where most of the data they generate is archived, whether they have asked colleagues for research data, whether the data were provided, whether there is adequate expertise in their lab or group to analyze their data in the way desired, and whether there is sufficient funding for data curation in their group |
Measurement, Targeted |
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Sunlight Foundation, & Keserű J.
(2015). We're still looking for open data social impact stories!.
Sunlight Foundation. |
Built a list of examples of how open data and transparency projects are having an impact on society |
Gathered approximately 150 stories through an open Google spreadsheet. |
Measurement, Targeted |
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The Governance Lab New York University
(0). Open Data 500.
Open Data 500. |
An ongoing study of U.S. companies that use open government data to generate new business and develop new products and services (http://www.opendata500.com/us/about/) |
Compiles a list of companies through outreach, research and advice; gathers information about companies’ use of open data via an online survey; conducts roundtables that bring together federal agencies and businesses with organizations that use their data to help identify and facilitate access to high value data |
Measurement, Targeted |
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Vickery, G.
(2011). Review of Recent Studies on PSI Re-use and Related Market Developments.
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Investigated the value of Public Sector Information (PSI) reuse in Europe |
Conducted a review of the findings of studies on PSI reuse and assess and changes or development since 2006 |
Measurement, Targeted |
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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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Wynholds, L. A., Wallis J. C., Borgman C. L., Sands A., & Traweek S.
(2012). Data, Data Use, and Scientific Inquiry: Two Case Studies of Data Practices.
19 - 22. |
Investigated the characteristics of data use and reuse within specific research communities, and how characteristics of data use and reuse vary within and between those communities |
Conducted semi-structured interviews and field observations in environmental sciences, marine biology, ecology, seismology, computer science, engineering, and astronomy |
Measurement, Targeted |
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Bigagli, L., Sveinsdottir T., Wessels B., Smallwood R., Linde P., Tsoukala V., et al.
(2014). Infrastructural and technological challenges and potential solutions.
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Investigated infrastructural and technological barriers to Open Access and preservation of research data in Europe. This work was conducted within the EU FP7 funded project RECODE, which focuses on developing policy recommendations for Open Access to Research Data in Europe. In particular, this work is coordinated by RECODE Work Package 2 (WP2), Infrastructure and technology. It distinguishes between different categories of stakeholders in terms of how the experience and respond to these challenges |
Conducted desk research, an online survey, interviews, and a validation workshop |
Measurement, Metrics, Wider |
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Noorman, M., Kalaitzi V., Angelaki M., Tsoukala V., Linde P., Sveinsdottir T., et al.
(2014). Institutional barriers and good practice solutions.
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Investigated challenges faced by institutions, such as archives, libraries, universities, data centres and funding bodies, in making open access to research data possible. This work was conducted within the EU FP7 funded project RECODE, which focuses on developing policy recommendations for Open Access to Research Data in Europe. |
Conducted desk research, case study interviews, and a validation workshop |
Measurement, Wider |
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Sveinsdottir, T., Wessels B., Smallwood R., Linde P., Kala V., Tsoukala V., et al.
(2013). Stakeholder values and relationships within open access and data dissemination and preservation ecosystems.
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Identify and map the diverse range of stakeholder values in Open Access data and data dissemination and preservation; map stakeholder values on to research ecosystems using case studies from different disciplinary perspectives; conduct a workshop to evaluate and identify good practice in addressing conflicting value chains and stakeholder fragmentation. This work was conducted within the EU FP7 funded project RECODE, which focuses on developing policy recommendations for Open Access to Research Data in Europe. |
Conducted desk research, case study interviews, and a validation workshop |
Measurement, Metrics, 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 |
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Yakel, E., & Faniel I.
(2013). Dissemination Information Packages for Information Reuse.
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Studied "data reuse in three academic disciplines to identify how contextual information about the data that supports reuse can best be created and preserved. The project focuses on research data produced and used by quantitative social scientists, archaeologists, and zoologists." (http://www.oclc.org/research/themes/user-studies/dipir.html) |
Used a variety of methods including a survey, analysis of online behavior, and user observations |
Measurement, Targeted |
