|
Addis, M.
(2015). Estimating Research Data Volumes in UK HEI.
|
Investigated amount of data in UK Higher Education Institutions (HEI) |
Used existing surveys about research data to estimate an average per researcher data size in terabytes, then used data on the number of researchers at each HEI institution to estimate an overall amount |
Measurement, Targeted |
|
Akers, K., & Doty J.
(2013). Disciplinary differences in faculty research data management practices and perspectives.
International Journal of Digital Curation. 8(2), 5 - 26. |
Investigated disciplinary differences in research data management needs at Emory University |
Sent email invitation to participate in online survey to all employees at Emory University with faculty status. 456 out of 5,590 (8%) initiated survey. 330 responded that conduct research that generates some kind of data and filled out one question |
Measurement, Wider |
|
Ayris, P., Wheatley P., Aitken B., Hole B., McCann P., Peach C., et al.
(2010). The LIFE3 Project: Bringing digital preservation to LIFE.
|
Investigated the development of a life cycle-based cost model for digital preservation |
Performed comprehensive review of life cycle models and digital preservation; broke a digital object’s lifecycle into six main lifecycle stages and identified the costs of elements in these stages over a specified time; performed case studies to identify costs for each stage of the life cycle; LIFE2 added cases studies for two institutional repositories and an analog collection; LIFE3 included a survey of digital preservation repositories and additional case studies |
Measurement, Metrics, Targeted |
|
Ayris, P., Wheatley P., Davies R., Shenton H., Miao R., & McLeod R.
(2008). The LIFE2 Final Project Report.
|
Investigated the development of a life cycle-based cost model for digital preservation |
Performed comprehensive review of life cycle models and digital preservation; broke a digital object’s lifecycle into six main lifecycle stages and identified the costs of elements in these stages over a specified time; performed case studies to identify costs for each stage of the life cycle; LIFE2 added cases studies for two institutional repositories and an analog collection; LIFE3 included a survey of digital preservation repositories and additional case studies |
Measurement, Metrics, Targeted |
|
Ball, A., & Duke M.
(2015). How to Track the Impact of Research Data with Metrics.
DCC How-to Guides.. |
Investigated and discussed a wide range of means of determining the impact of research data using a variety of different metrics and measurement services |
Performed an extensive literature review |
Metrics, Targeted |
|
Beagrie, N., Chruszcz J., & Lavoie B.
(2008). Keeping Research Data Safe: A Cost Model and Guidance for UK Universities.
|
Investigated the medium to long term costs to Higher Education Institutions (HEIs) of the preservation of research data and developed guidance on these issues, including a framework for determining costs |
Mapped the OAIS reference model against the LIFE cost model and NASA’s Cost Estimation Toolkit; evaluated transferable practice and relative strengths and weaknesses for each; aligned the resulting model with the TRAC model; researched literature on preservation costs and reports and documentation from UK data services and funders; conducted 12 interviews to supplement and validate researched information; conducted three case studies to validate the developed methodology and illustrate the variety of costs and community and service requirements for research data. |
Measurement, Metrics, Targeted |
|
Beagrie, N., Houghton J., Palaiologk A., & Williams P.
(2012). Economic Evaluation of Research Data Infrastructure.
|
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 |
|
Beagrie, N., & Houghton J.
(2013). The Value and Impact of the Archaeology Data Service: A Study and Methods for Enhancing Sustainability.
|
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 |
|
Beagrie, N., & Houghton J.
(2013). The Value and Impact of the British Atmospheric Data Centre.
|
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 |
|
Beagrie, N., Lavoie B., & Woollard M.
(2010). Keeping Research Data Safe 2.
|
Continued the work of Beagrie et al. 2008 to develop a cost model for digital preservation |
Updated the previous literature review; conducted a cost survey; developed a taxonomy of the benefits of digital preservation; analyzed national and disciplinary digital archives that have existing historic cost information for preservation of digital research data collections and interacted with additional digital archives and research universities to determine the validity of developed cost model and how the cost model might be used |
Measurement, Metrics, Targeted |
|
Beagrie, N., Semple N., Williams P., & Wright R.
(2008). Digital Preservation Study Policies.
|
Studied digital preservation policies to provide a model for policy development in Higher and Further Education Institutions; analyzed the role that digital preservation can play in supporting and delivering key strategies for these institutions |
Examined preservation policies, case studies, strategies and resources from a variety of sources; examined a sample of policies for research, teaching, and learning, and other relevant digital preservation literature and resources |
Measurement, Metrics, Targeted |
|
Beile, P.
(2014). The UCF Research Data Management Survey: A report of faculty practices and needs.
|
Investigated faculty data management needs and practices at the University of Central Florida |
Conducted an online survey containing 33 questions. There were 534 valid recipients and 97 who partially or fully completed the survey. |
Measurement, Wider |
|
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 |
|
Bergin, M. Banach
(2013). Sabbatical Report: Summary of Survey Results on Digital Preservation Practices at 148 Institutions.
|
Investigate how digital preservation programs were implemented in institutions with established programs |
Conducted an online survey and follow-up interviews with 12 librarians and archivists from various institutions. The survey received 148 responses [from libraries and archives]. 100 people finished the survey.
"...I received responses from all types of institutions including national libraries, state libraries, academic libraries, public libraries, church and corporate archives, national parks archives, historical societies, research data centers, and presidential libraries. Roughly a third of the respondents were from large academic institutions with more than 20,000 students, another third were from smaller academic institutions with less than 20,000 students, and the remaining third were from non-academic institutions." |
Measurement, Wider |
|
Berman, F., Lavoie B., Ayris P., G. Choudhury S., Cohen E., Courant P., et al.
(2010). Sustainable Economics for a Digital Planet: Ensuring Long-Term Access to Digital Information.
110. |
Developed an economic framework for analyzing digital preservation as an economic problem. Employed the framework to analyze the "economic conditions and implications intrinsic to four key digital preservation contexts: scholarly discourse, research data, collectively produced Web content, and commercially owned cultural content." |
Drew on findings reported in the interim Blue Ribbon Task Force report: Sustaining the Digital Investment: Issues and Challenges of Economically Sustainable Digital Preservation |
Metrics, Targeted |
|
Bohn, R. E., & Short J. E.
(2010). How Much Information? 2009 Report on American Consumers.
|
Investigated amount of information consumed and rates of increase in consumption in the US from 1980 to 2008 |
Analyzed 20 sources of data flows (such as video, television, radio, internet browsing) consumed by people |
Measurement, Metrics, Targeted |
|
Digital Curation Centre
(2014). Five steps to decide what data to keep: a checklist for appraising research data v.1.
|
A guide written by the DCC |
|
Metrics, Targeted |
|
Fearon, D., Gunia B., Pralle B., Lake S., & Sallans A.
(2013). ARL Spec Kit 334: Research data management services.
|
To assess early endeavors in research data services and benchmark future growth in ARL member libraries. |
Conducted a survey of ARL member libraries. 73 of 125 responded. |
Measurement, Wider |
|
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.
|
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 |
|
Gantz, J. F., McArthur J., Minton S., Reinsel D., Chute C., Schlichting W., et al.
(2007). The Expanding Digital Universe [White Paper].
|
Investigated size and rate of expansion of the digital universe worldwide in 2006 and 2007 |
Estimated how much data was created in a year by a base of 49 classes of devices or applications that could capture or store information; estimated number of times the data is replicated |
Measurement, Metrics, Targeted |
|
Gantz, J. F., Minton S., Reinsel D., Chute C., Schlichting W., Toncheva A., et al.
(2008). The Diverse and Exploding Digital Universe [White Paper].
|
Investigated size and rate of expansion of the digital universe worldwide in 2006 and 2007 |
Estimated how much data was created in a year by a base of 49 classes of devices or applications that could capture or store information; estimated number of times the data is replicated |
Measurement, Targeted |
|
Gibbs, H.
(2009). Southampton Data Survey: Our Experience and Lessons Learned.
|
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 |
|
Hendley, T.
(1998). Comparison of Methods & Costs of Digital Preservation.
|
Developed a matrix of data types and categories of digital resources, a decision model to assess these categories and determine the most appropriate preservation strategy, and a cost model for comparing costs of preferred preservation methods |
Conducted an extensive review of literature and work to develop cost models; visited a number of digital libraries and data centres |
Metrics, Targeted |
|
Hilbert, M., & López P.
(2011). The World’s Technological Capacity to Store, Communicate, and Compute Information.
Science. 332(6025), 60 - 65. |
Investigated amounts of total information (not unique) stored, communicated, and computed from 1986 to 2007 |
Used worldwide estimates in 1,120 sources for data in 60 categories (analog and digital) |
Measurement, Metrics, Targeted |
|
Houghton, J., & Gruen N.
(2014). Open Research Data Report.
Report to the Australian National Data Service (ANDS). |
Estimated the value and benefits to Australia of making publicly-funded research data freely available; examined the role and contribution of data repositories and associated infrastructure; explored the policy settings required to optimize research data sharing, and thereby increase the return on public investment in research |
Used and modified Solow-Swan model and extrapolated from results of other studies, primarily in the UK, to estimate the implied value of increased access to Australian public research data |
Measurement, Targeted |
|
Jerrome, N., & Breeze J.
(2009). Imperial College Data Audit Framework Implementation: Final Report.
|
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 |
|
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.
|
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 |
|
Kejser, U. Bøgvad, Nielsen A. Bo, & Thirifays A.
(2011). Cost Model for Digital Preservation: Cost of Digital Migration.
International Journal of Digital Curation. 6(1), |
Investigated the development of a framework for costing digital preservation, including a methodology with sufficient detail to outline required resources, a set of equations to transform the resources into cost data, and a description of the accounting principles applied
|
Performed a literature review; used the OAIS reference model to structure the functional breakdown of costs, initially for preservation planning and migration; examined two case studies dealing with migrations of data |
Measurement, Metrics, Targeted |
|
Kroll, S., & Forsman R.
(2010). A Slice of Research Life: Information Support for Research in the United States.
|
Investigated use of tools and services that support of all stages of the research life cycle in institutions of higher education in the U.S. |
Conducted a literature review and interviews with researchers, research assistants, graduate students, grant and other research administration specialists, and university administrators at four prominent US research institutions |
Measurement, Wider |
|
Kuipers, T., & van der Hoeven J.
(2009). PARSE.Insight: Insight into Digital Preservation of Research Output in Europe: Survey Report.
|
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 |
|
Lesk, M.
(1997). How Much Information Is There In the World?.
|
Investigated amount of information in the world in 1997 |
Estimated size based on extrapolations from select examples of data storage |
Measurement, Targeted |
|
Lyman, P., & Varian H. R.
(2000). How Much Information?.
Journal of Electronic Publishing. 6(2), |
Investigated amount of new information created each year in the US and world in 1999 |
Estimated size based on research into the production of data stored on four storage media: print, film, magnetic, optical |
Measurement, Metrics, Targeted |
|
Lyman, P., & Varian H. R.
(2003). How Much Information? 2003.
|
Investigated amount of new information created each year in the US and world in 2002 |
Estimated size based on research into the production of data stored on four storage media: print, film, magnetic, optical |
Measurement, Metrics, Targeted |
|
Manyika, J., Byers A. Hung, Chui M., Brown B., Bughin J., Dobbs R., et al.
(2011). Big data: The next frontier for innovation, competition, and productivity.
156. |
Examined the potential value that big data can create for organizations and sectors of the economy; sought to illustrate and quantify that value; explored what leaders of organizations and policy makers need to do to capture it; investigated amount of data stored by enterprises and consumers in 2010 |
Examined types and amounts of data generated, compute resources, and trends that will drive data growth in different sectors and regions throughout the world; examined the impact of IT on labor productivity, techniques and technologies for analyzing big data, and the transformative potential of big data in terms of efficiency, productivity, trust, profit, and other factors in five domains: Healthcare, Public Sector, Retail, Manufacturing, and Telecommunications; also examined the changes necessary (investments, incentives, skills development, policy development and others) to attain these benefits; specific methodologies to gather supporting data are listed in the paper |
Measurement, Targeted |
|
Manyika, J., Chui M., Groves P., Farrell D., Van Kuiken S., Doshi E. Almasi, et al.
(2013). Open data: Unlocking innovation and performance with liquid information.
103. |
Identified ways open data can create economic value in terms of revenue and savings and economic surplus (e.g., time savings that commuters gain when they avoid congestion); estimated potential annual value that use of open data could bring in seven domains: education, transportation, consumer products, electric power, oil and gas, health care, and consumer finance |
Quantified (in monetary terms) the potential value of using open data in seven “domains” of the global economy: education, transportation, consumer products, electricity, oil and gas, health care, and consumer finance; identified “levers” through which open data can create economic value and explored the barriers to adoption and “enablers” for capturing value by making data more open; provided examples of uses of open data that have a significant impact |
Measurement, Metrics, Targeted |
|
Martinez-Uribe, L.
(2009). Using the Data Audit Framework: An Oxford Case Study.
|
Piloted the Digital Asset Framework methodology in work to scope digital repository services for research data management |
Adapted the Digital Asset Framework methodology |
Measurement, Wider |
|
Mayer, R., Rauber A., Neumann M. Alexander, Thomson J., & Antunes G.
(2012). Preserving Scientific Processes from Design to Publications.
Theory and Practice of Digital Libraries. 7489, 113 - 124. |
Provides a model for capturing contextual details (including provenance) for scientific processes (e.g., software and surrounding processes) |
|
Metrics, Targeted |
|
McLeod, R., Wheatley P., Ayris P., & Girling H.
(2006). The LIFE Project: Bringing digital preservation to LIFE - A summary from the LIFE project Report Produced for the LIFE conference 20 April 2006.
|
Investigated the development of a life cycle-based cost model for digital preservation |
Performed comprehensive review of life cycle models and digital preservation; broke a digital object’s lifecycle into six main lifecycle stages and identified the costs of elements in these stages over a specified time; performed case studies to identify costs for each stage of the life cycle; LIFE2 added cases studies for two institutional repositories and an analog collection; LIFE3 included a survey of digital preservation repositories and additional case studies |
Measurement, Metrics, Targeted |
|
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 |
|
Open Exeter Project Team
(2012). Summary Findings of the Open Exeter Data Asset Framework Survey.
|
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 |
|
Pampel, H., Vierkant P., Scholze F., Bertelmann R., Kindling M., Klump J., et al.
(2013). Making Research Data Repositories Visible: The re3data.org Registry.
PLoS ONE. 8(11), e78080. |
Investigated the global landscape of research data repositories; presented a typology of institutional, disciplinary; outlined the features of re3data.org, and showed how this registry helps to identify appropriate repositories for storage and search of research data
|
Analyzed 400 research data repositories and requested comments on a project website and various email lists on an appropriate vocabulary to describe and present information (such as policies, responsibilities, and technical and quality standards for different repositories); analyzed criteria for repository certification and audit and developed a low barrier of entry to inclusion in in the repository registry. |
Measurement, Targeted |
|
Parsons, T., Grimshaw S., & Williamson L.
(2013). Research Data Management Survey.
|
Sought to understand the baseline of RDM practices, gather researcher requirements for RDM, and raise awareness of and gauge interest in a proposed service |
After testing on a smaller population, conducted an online survey of career researchers and post-doctoral researchers at the University of Nottingham using targeted email |
Measurement, Wider |
|
Perry, C.
(2008). Archiving of publicly funded research data: A survey of Canadian researchers..
Government Information Quarterly. 25(1), 133 - 148. |
To assess researchers’ attitudes and behaviours in relation to archiving research data and to determine researchers’ views about policies relating to data archiving. Investigated how much of the data being produced in the course of SSHRC-funded research is being archived. Surveyed social sciences and humanities researchers from universities across Canada. |
A questionnaire comprising 15 questions was mailed to 175 researchers randomly sampled from a publicly available list of 5,821 individuals who had received grants and awards from the Social Sciences and Humanities Research Council of Canada (SSHRC). From this sample, 75 (43.4%) responded within the five week time-frame stipulated. The questionnaire was constructed using four existing surveys and asked researchers for information about: geographical location, years of research experience, research funding sources, current plans to archive research data, awareness of archiving policies, attitude to mandated research data archiving, effect of mandatory data archiving policies on grant-seeking, attitude to making archived research data accessible, and use of research data collected by others. The questionnaire also included space for respondents to make comments. |
Measurement, Wider |
|
Peters, C., & Dryden A.
(2011). Assessing the Academic Library's Role in Campus-Wide Research Data Management: A First Step at the University of Houston.
Science & Technology Libraries. 30(4), 387 - 403. |
Interviewed PIs of significant grants, to assess individuals in as many science and engineering departments as possible, and to obtain information on data management practices from both individual and group-based projects |
Conducted interviews with PIs of 10 projects (14 contacted), as well as one Co-PI, one post-doctorate and one graduate student associated with one of the projects) |
Measurement, Wider |
|
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 |
|
Ramapriyan, H.., Moses J. F., & Duerr R..
(2012). Preservation of data for Earth system science - Towards a content standard.
5304 - 5307. |
Presents the need for a preservation content specification for earth science data, and proposes content items to be captured |
|
Metrics, Targeted |
|
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 |
|
Science and Technology Council
(2007). The Digital Dilemma: Strategic Issues in Archiving and Accessing Digital Motion Picture Materials.
Academy of Motion Picture Arts and Sciences. |
Investigated size of picture and sound elements created during production and post production for two motion pictures in 2006 or 2007 |
Conducted case studies where motion picture studios provided information about the amounts of data for a pre-determined list of materials |
Measurement, Metrics, Targeted |
|
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 |
|
Berman, F., Lavoie B., Ayris P., G. Choudhury S., Cohen E., Courant P. N., et al.
(2008). Sustaining the Digital Investment: Issues and Challenges of Economically Sustainable Digital Preservation.
72. |
"To sample and understand best and current practices for digital preservation and access, and to begin to synthesize major themes and identify systemic challenges." Focused on two questions: How much does it cost? and Who should pay? |
Conducted a literature review and invited 16 speakers "representing a variety of domains and areas of expertise" to address five questions: 1) What is the nature of the materials being preserved; 2) Who are the stakeholders for these materials?; 3) What is the "value proposition" for this preservation effort?; 4) What are the key features of long-term preservation for these materials?; 5) What are the "economic aspects" of digital preservation? |
Measurement, Targeted |
|
Thornhill, K., & Palmer L.
(2014). An Assessment of Doctoral Biomedical Student Research Data Management Needs.
|
Explored institutional repository data management needs at the University of Massachusetts Medical School |
Conducted literature review; sent a data needs assessment survey based on the DCC lifecycle model and NSF requirements for data management to 470 students on an email discussion list.
|
Measurement, Targeted |
|
Turner, V., Reinsel D., Gantz J. F., & Minton S.
(2014). The Digital Universe of Opportunities: Rich Data and the Increasing Value of the Internet of Things.
|
Investigated size and rate of expansion of the digital universe worldwide in 2013; investigated business opportunities to use data in new ways and extract value from the digital universe |
Analyzed 60 streams of data comprising the digital universe (11 streams were added to the 49 in the 2007 study); analyzed ways in particular that the Internet of Things is creating business opportunities; developed 5 criteria to identify “target rich” or valuable data in the digital universe; identified information technology prerequisites to being able to take advantage of the value of data; identified business steps enterprises must take to leverage data value |
Measurement, Metrics, Targeted |
|
UNC-CH
(2012). Research Data Stewardship at UNC: Recommendations for Scholarly Practice and Leadership.
|
Sought to identify policy options for digital research data stewardship at UNC; further understanding of the full-breadth of activities, concerns, and opinions surrounding research data stewardship among researchers at UNC-CH |
Conducted semi-structured interviews with 23 faculty researchers representing several disciplines at UNC-CH; conducted an online survey of all faculty members, graduate students, and staff assigned to departments that engage in research |
Measurement, Wider |
|
Vickery, G.
(2011). Review of Recent Studies on PSI Re-use and Related Market Developments.
|
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 |
|
Waller, M., & Sharpe R.
(2006). Mind the Gap: Assessing Digital Preservation Needs in the UK.
|
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.
|
Measurement, Wider |
|
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 |
|
Bigagli, L., Sveinsdottir T., Wessels B., Smallwood R., Linde P., Tsoukala V., et al.
(2014). Infrastructural and technological challenges and potential solutions.
|
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 |
|
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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Kaur, K., Darby R., Herterich P., Schmitt K., Schrimpf S., Tjalsma H., et al.
(2013). Report on Testing of Cost Models and Further Analysis of Cost Parameters.
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Test existing cost models and cost/benefit analyses for digital preservation against real-world examples; analyzed cost models in relation to ISO 16363 to identify gap areas not covered by the models |
Tested the cost models with data that had already been collected (e.g., as part of the development of the DANS cost model) |
Measurement, Targeted |
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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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Russell, K., & Weinberger E.
(2000). Cost elements of digital preservation.
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"Provides an introduction and overview of some of the general issues associated with the costs of digital preservation and...a detailed breakdown of specific cost elements" |
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Metrics, Targeted |
