Category Archives: oa.case.data

Grynoch | Show me the data! Data sharing practices demonstrated in published research at the University of Massachusetts Chan Medical School | Journal of eScience Librarianship

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Abstract:  Objective: In the interest of making data findable, accessible, interoperable, and reusable (FAIR), the National Institutes of Health (NIH) will institute a new Data Management and Sharing Policy in January 2023. This policy will require researchers applying for NIH funding to submit a Data Management and Sharing Plan. As 63% of grant dollars received by University of Massachusetts Chan Medical School (UMass Chan) researchers comes from the NIH, we explored whether UMass Chan researchers are currently sharing data associated with their published research and how they shared their data. 

Methods: PubMed was searched for articles published in 2019 with a UMass Chan researcher as either the first or last author. These articles were examined for evidence of original or reused data, the type of data, whether the article stated that data was available, and where and how to find that data. 

Results: Of the 361 articles with original data, 26% had a data availability statement. However, most articles (71%) did not mention where data could be accessed. The data storage location of the estimated 1551 original datasets was similarly not mentioned for 74% the datasets with the next largest category being available upon request (8.6%). Genomic data repositories such as the Gene Expression Omnibus were among the top repositories used by authors. Similar areas for improvement were noted for permanent identifier use (46% had a permanent identifier), using non-proprietary file formats (most popular format was Excel), and citing reused data. Authors who published open access were more likely to share their data. 

Conclusions: While some researchers at UMass Chan have embraced data sharing, particularly genomic data sharing, we expect there will be more data shared in the coming years with the implementation of the new NIH Data Management and Sharing Policy.

WorldFAIR: Global cooperation on FAIR data policy and practice – Kick-Off Meeting introduces major new initiative to advance implementation of the FAIR data principles – CODATA, The Committee on Data for Science and Technology

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“The WorldFAIR project held a successful kick-off meeting online on 9 June 2022, with representatives from the European Commission and all nineteen participating organisations from Europe and beyond.

The WorldFAIR project is a major new global collaboration between partners from thirteen countries across Africa, Australasia, Europe, and North and South America.  WorldFAIR will advance implementation of the FAIR data principles, in particular those for Interoperability, by developing a cross-domain interoperability framework and recommendations for FAIR assessment in a set of eleven disciplines or cross-disciplinary research areas….”

To protect and to serve: developing a road map for research data management services

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Abstract:  Research Data Management (RDM) has become a major issue for universities over the last decade. This case study outlines the review of RDM services carried out at the University of Oxford in partnership with external consultants between November 2019 and November 2020. It aims to describe and discuss the processes in undertaking a university-wide review of services supporting RDM and developing a future road map for them, with a strong emphasis on the design processes, methodological approaches and infographics used. The future road map developed is a live document, which the consulting team handed over to the University at the end of the consultation process. It provides a suggested RDM action plan for the University that will continue to evolve and be iterated in the light of additional internal costings, available resources and reprioritization in the budget cycle for each academic year. It is hoped that the contents of this case study will be useful to other research-intensive universities with an interest in developing and planning RDM services to support their researchers.

 

Bringing All the Stakeholders to the Table: A Collaborative Approach to Data Sharing

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Abstract: Objective: This paper examines a unique data set disclosure process at a medium sized, land grant, research university and the campus collaboration that led to its creation. Methods: The authors utilized a single case study methodology, reviewing relevant documents and workflows. As first-hand participants in the collaboration and disclosure process development, their own accounts and experiences also were utilized. Results: A collaborative approach to enhancing research data sharing is essential, considering the wide array of stakeholders involved across the life cycle of research data. A transparent, inclusive data set disclosure process is a viable route to ensuring research data can be appropriately shared. Conclusions: Successful sharing of research data impacts a range of university units and individuals. The establishment of productive working relationships and trust between these stakeholders is critical to expanding the sharing of research data and to establishing shared workflows. 

“A Collaborative Approach to Data Sharing” by Megan N. O’Donnell and Curtis Brundy

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Abstract:  Objective: This paper examines a unique data set disclosure process at a medium sized, land grant, research university and the campus collaboration that led to its creation.

Methods: The authors utilized a single case study methodology, reviewing relevant documents and workflows. As first-hand participants in the collaboration and disclosure process development, their own accounts and experiences also were utilized.

Results: A collaborative approach to enhancing research data sharing is essential, considering the wide array of stakeholders involved across the life cycle of research data. A transparent, inclusive data set disclosure process is a viable route to ensuring research data can be appropriately shared.

Conclusions: Successful sharing of research data impacts a range of university units and individuals. The establishment of productive working relationships and trust between these stakeholders is critical to expanding the sharing of research data and to establishing shared workflows.

Open Book: Kick-starting open data support | Research Information

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“There has been rapid growth in interest in the potential of open data in recent years, and at City, University of London, we quickly recognised that if the university was to become more research intensive, we had to provide a more proactive research data service to our researchers. 

One of the steps that we took to encourage data sharing was to create an institutional data repository for non-traditional publications, using Figshare for Institutions (https://city.figshare.com). Like many other research institutions, City doesn’t have a long history of providing data support and for political and historical reasons City’s data repository sits outside the library in the research & enterprise office. I’m very much an ‘accidental data manager’, rather than a data specialist. I knew nothing about research data management two years ago, and it is only one of many responsibilities I have at the university.

Unfortunately uptake of the institutional repository was lower than anticipated. We found that researchers often have little experience of sharing data, and unlike traditional forms of publication (such as research articles and book chapters) data is not typically a priority for researchers, as it doesn’t count in the UK’s Research Excellence Framework (REF)….

By the end of the support process it had been transformed with metadata, keywords, categories, and even the title of the final record, all being added by the research data team. The hope is that easing the submission of data will encourage researchers to use the repository in the near future, while improving the quality of the metadata will encourage use in the longer term, as the improved impact of the data begins to be seen.”

Data sharing from clinical trials: lessons from the YODA Project – STAT

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“This week, the National Academies of Science, Engineering, and Medicine are convening the workshop “Sharing Clinical Trial Data: Challenges and a Way Forward” just shy of five years after the Institute of Medicine released its seminal report, “Sharing Clinical Trial Data: Maximizing Benefits, Minimizing Risk.”

During this time, the scientific culture regarding data sharing has shifted. Just last week, the National Institutes of Health requested public comments on its draft “Policy for Data Management and Sharing.” In 2018, the International Committee of Medical Journal Editors began requiring data-sharing plans for clinical trials as a condition for publication in member journals. And platforms such as ClinicalStudyDataRequest.com, Project Data Sphere, and BioLINCC have emerged or grown. These platforms use a variety of different governance structures and models for data access, developed both with and without the support of industry or government….

The Yale Open Data Access (YODA) Project, which two of us (J.S.R. and H.M.K.) co-direct, launched in 2011 and formed a partnership with Johnson & Johnson in 2014. This five-year partnership offers an opportunity to reflect on some of the questions about sharing clinical trial data that may inform ongoing and future efforts….”

“Research Data Management Among Life Sciences Faculty” by Kelly A. Johnson and Vicky Steeves

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Abstract:  Objective: This paper aims to inform on opportunities for librarians to assist faculty with research data management by examining practices and attitudes among life sciences faculty at a tier one research university.

Methods: The authors issued a survey to estimate actual and perceived research data management needs of New York University (NYU) life sciences faculty in order to understand how the library could best contribute to the research life cycle.

Results: Survey responses indicate that over half of the respondents were aware of publisher and funder mandates, and most are willing to share their data, but many indicated they do not utilize data repositories. Respondents were largely unaware of data services available through the library, but the majority were open to considering such services. Survey results largely mimic those of similar studies, in that storing data (and the subsequent ability to share it) is the most easily recognized barrier to sound data management practices.

Conclusions: At NYU, as with other institutions, the library is not immediately recognized as a valuable partner in managing research output. This study suggests that faculty are largely unaware of, but are open to, existent library services, indicating that immediate outreach efforts should be aimed at promoting them.

“Research Data Management Among Life Sciences Faculty” by Kelly A. Johnson and Vicky Steeves

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Abstract:  Objective: This paper aims to inform on opportunities for librarians to assist faculty with research data management by examining practices and attitudes among life sciences faculty at a tier one research university.

Methods: The authors issued a survey to estimate actual and perceived research data management needs of New York University (NYU) life sciences faculty in order to understand how the library could best contribute to the research life cycle.

Results: Survey responses indicate that over half of the respondents were aware of publisher and funder mandates, and most are willing to share their data, but many indicated they do not utilize data repositories. Respondents were largely unaware of data services available through the library, but the majority were open to considering such services. Survey results largely mimic those of similar studies, in that storing data (and the subsequent ability to share it) is the most easily recognized barrier to sound data management practices.

Conclusions: At NYU, as with other institutions, the library is not immediately recognized as a valuable partner in managing research output. This study suggests that faculty are largely unaware of, but are open to, existent library services, indicating that immediate outreach efforts should be aimed at promoting them.

“Establishing an RDM Service on a Health Sciences Campus” by Kathryn Vela and Nancy Shin

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Abstract:  Objective: Given the increasing need for research data management support and education, the Spokane Academic Library at Washington State University (WSU) sought to determine the data management practices, perceptions, and needs of researchers on the WSU Spokane health sciences campus.

Methods: A 23-question online survey was distributed to WSU researchers and research support staff through the campus listserv. This online survey addressed data organization, documentation, storage & backup, security, preservation, and sharing, as well as challenges and desired support services.

Results: Survey results indicated that there was a clear need for more instruction with regard to data management planning, particularly as data management planning addresses the areas of metadata design, data sharing, data security, and data storage and backup.

Conclusions: This needs assessment will direct how RDM services are implemented on the WSU Spokane campus by the Spokane Academic Library (SAL). These services will influence both research data quality and integrity through improved data management practices.

“Establishing an RDM Service on a Health Sciences Campus” by Kathryn Vela and Nancy Shin

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Abstract:  Objective: Given the increasing need for research data management support and education, the Spokane Academic Library at Washington State University (WSU) sought to determine the data management practices, perceptions, and needs of researchers on the WSU Spokane health sciences campus.

Methods: A 23-question online survey was distributed to WSU researchers and research support staff through the campus listserv. This online survey addressed data organization, documentation, storage & backup, security, preservation, and sharing, as well as challenges and desired support services.

Results: Survey results indicated that there was a clear need for more instruction with regard to data management planning, particularly as data management planning addresses the areas of metadata design, data sharing, data security, and data storage and backup.

Conclusions: This needs assessment will direct how RDM services are implemented on the WSU Spokane campus by the Spokane Academic Library (SAL). These services will influence both research data quality and integrity through improved data management practices.

“Assessing Data Management Needs of Bioengineering and Biomedical Faculty” by Christie A. Wiley and Margaret H. Burnette

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Abstract:  Objectives: This study explores data management knowledge, attitudes, and practices of bioengineering and biomedical researchers in the context of the National Institutes of Health-funded research projects. Specifically, this study seeks to answer the following questions:

What is the nature of biomedical and bioengineering research on the Illinois campus and what kinds of data are being generated?
To what degree are biomedical and bioengineering researchers aware of best practices for data management and what are the actual data management behaviors?
What aspects of data management present the greatest challenges and frustrations?
To what degree are biomedical and bioengineering researchers aware of data sharing opportunities and data repositories, and what are their attitudes towards data sharing?
To what degree are researchers aware of campus services and support for data management planning, data sharing, and data deposit, and what is the level of interest in instruction in these areas?

 

Methods: Librarians on the University of Illinois at Urbana Champaign campus conducted semi-structured interviews with bioengineering and biomedical researchers to explore researchers’ knowledge of data management best practices, awareness of library campus services, data management behavior and challenges managing research data. The topics covered during the interviews were current research projects, data types, format, description, campus repository usage, data-sharing, awareness of library campus services, data reuse, the anticipated impact of health on public and challenges (interview questions are provided in the Appendix).

Results: This study revealed the majority of researchers explore broad research topics, various file storage solutions, generate numerous amounts of data and adhere to differing discipline-specific practices. Researchers expressed both familiarity and unfamiliarity with DMP Tool. Roughly half of the researchers interviewed reported having documented protocols for file names, file backup, and file storage. Findings also suggest that there is ambiguity about what it means to share research data and confusion about terminology such as “repository” and “data deposit”. Many researchers equate publication to data sharing.

Conclusions: The interviews reveal significant data literacy gaps that present opportunities for library instruction in the areas of file organization, project workflow and documentation, metadata standards, and data deposit options. The interviews also provide invaluable insight into biomedical and bioengineering research in general and contribute to the authors’ understanding of the challenges facing the researchers we strive to support.

“Assessing Data Management Needs of Bioengineering and Biomedical Faculty” by Christie A. Wiley and Margaret H. Burnette

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Abstract:  Objectives: This study explores data management knowledge, attitudes, and practices of bioengineering and biomedical researchers in the context of the National Institutes of Health-funded research projects. Specifically, this study seeks to answer the following questions:

What is the nature of biomedical and bioengineering research on the Illinois campus and what kinds of data are being generated?
To what degree are biomedical and bioengineering researchers aware of best practices for data management and what are the actual data management behaviors?
What aspects of data management present the greatest challenges and frustrations?
To what degree are biomedical and bioengineering researchers aware of data sharing opportunities and data repositories, and what are their attitudes towards data sharing?
To what degree are researchers aware of campus services and support for data management planning, data sharing, and data deposit, and what is the level of interest in instruction in these areas?

 

Methods: Librarians on the University of Illinois at Urbana Champaign campus conducted semi-structured interviews with bioengineering and biomedical researchers to explore researchers’ knowledge of data management best practices, awareness of library campus services, data management behavior and challenges managing research data. The topics covered during the interviews were current research projects, data types, format, description, campus repository usage, data-sharing, awareness of library campus services, data reuse, the anticipated impact of health on public and challenges (interview questions are provided in the Appendix).

Results: This study revealed the majority of researchers explore broad research topics, various file storage solutions, generate numerous amounts of data and adhere to differing discipline-specific practices. Researchers expressed both familiarity and unfamiliarity with DMP Tool. Roughly half of the researchers interviewed reported having documented protocols for file names, file backup, and file storage. Findings also suggest that there is ambiguity about what it means to share research data and confusion about terminology such as “repository” and “data deposit”. Many researchers equate publication to data sharing.

Conclusions: The interviews reveal significant data literacy gaps that present opportunities for library instruction in the areas of file organization, project workflow and documentation, metadata standards, and data deposit options. The interviews also provide invaluable insight into biomedical and bioengineering research in general and contribute to the authors’ understanding of the challenges facing the researchers we strive to support.

State of Open Data: Histories and Horizons

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“It’s been ten years since open data first broke onto the global stage. Over the past decade, thousands of programmes and projects around the world have worked to open data and use it to address a myriad of social and economic challenges. Meanwhile, issues related to data rights and privacy have moved to the centre of public and political discourse. As the open data movement enters a new phase in its evolution, shifting to target real-world problems and embed open data thinking into other existing or emerging communities of practice, big questions still remain. How will open data initiatives respond to new concerns about privacy, inclusion, and artificial intelligence? And what can we learn from the last decade in order to deliver impact where it is most needed? The State of Open Data brings together over 65 authors from around the world to address these questions and to take stock of the real progress made to date across sectors and around the world, uncovering the issues that will shape the future of open data in the years to come….

The main goal of this project is to learn in order to help shape the future of open data based on information and evidence gathered from the community. With over 65 authors, an Editorial Board, and a development methodology that allows for flexibility and community feedback, The State of Open Data – Histories and Horizons brings a myriad of perspectives to the task of reviewing the state of open data….”

OPEN DATA, GREY DATA, AND STEWARDSHIP: UNIVERSITIES AT THE PRIVACY FRONTIER

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Abstract:  As universities recognize the inherent value in the data they collect and hold, they encounter unforeseen challenges in stewarding those data in ways that balance accountability, transparency, and protection of privacy, academic freedom, and intellectual property. Two parallel developments in academic data collection are converging: (1) open access requirements, whereby researchers must provide access to their data as a condition of obtaining grant funding or publishing results in journals; and (2) the vast accumulation of “grey data” about individuals in their daily activities of research, teaching, learning, services, and administration. The boundaries between research and grey data are blurring, making it more difficult to assess the risks and responsibilities associated with any data collection. Many sets of data, both research and grey, fall outside privacy regulations such as HIPAA, FERPA, and PII. Universities are exploiting these data for research, learning analytics, faculty evaluation, strategic decisions, and other sensitive matters. Commercial entities are besieging universities with requests for access to data or for partnerships to mine them. The privacy frontier facing research universities spans open access practices, uses and misuses of data, public records requests, cyber risk, and curating data for privacy protection. This Article explores the competing values inherent in data stewardship and makes recommendations for practice by drawing on the pioneering work of the University of California in privacy and information security, data governance, and cyber risk.