New Landscapes on the Road of Open Science: 6 key issues to address for research data management in the Netherlands | Open Working

“The road to Open Science is not a short one. As the chairman of the Executive Board of the European Open Science Cloud, Karel Luyben, is keen to point out, it will take at least 10 or 15 years of travel until we reach a point where Open Science is simply absorbed into ordinary, everyday science.

Within the Netherlands, and for research data in particular, we have made many strides towards that final point. We have knowledge networks such as LCRDM, a suite of archives covered by the Research Data Netherlands umbrella, and the groundbreaking work done by the Dutch Techcentre for Life Sciences.

But there is still much travel to be done; many new landscapes to be traversed. Data sharing is still far from being the norm (see here for a visualisation of these results).

The authors of this blog post have put together six areas that, in their opinion, deserve attention on our Open Science journey….”

Case study: Doing more with ORCID – UK ORCID Support

“The University of Cambridge research repository (Apollo), uses ORCID IDs as a unique identifier for researchers.  When a researcher submits a dataset to Apollo, a DOI is minted for the dataset through the DataCite service.   By including the ORCID in the metadata submitted to DataCite, DataCite then populates the ORCID registry entry for the researcher (with their permission) with information about the dataset, using an ‘auto-update’ feature. 

The result is that a link is created between the researcher and their data, through the ORCID ID identifying the researcher, and the DOI for the data assigned by DataCite. The persistent identifiers are used to connect researchers and their achievements, improving visibility and discoverability across different systems.  The workflow reduces duplication of effort in entering information and avoids input or identification errors….”

NIH Requests Public Comment on a Draft Policy for Data Management and Sharing and Supplemental Draft Guidance | SEA Currents

“Yesterday, NIH released a Draft NIH Policy for Data Management and Sharing and supplemental draft guidance for public comment. The purpose of this draft policy and supplemental draft guidance is to promote effective and efficient data management and sharing that furthers NIH’s commitment to making the results and accomplishments of the research it funds and conducts available to the public. Complete information about the draft Policy and draft supplemental guidance can be found on the NIH OSP website.

Stakeholder feedback is essential to ensure that any future policy maximizes responsible data sharing, minimizes burden on researchers, and protects the privacy of research participants.  Stakeholders are invited to comment on any aspect of the draft policy, the supplemental draft guidance, or any other considerations relevant to NIH’s data management and sharing policy efforts that NIH should consider.

To facilitate commenting, NIH has established a web portal that can be accessed here. To ensure consideration, comments must be received no later than January 10, 2020….”

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

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

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.

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

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

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.

“Baseball and Research Data Management (RDM) Planning” by Regina Fisher Raboin

Abstract:  As any lover of the game of baseball knows, at this time of year it’s all about depth – what you built in the farm system and on the bench matters; the data crunched before and during the season comes into play when managing a team to the World Series. Gut feelings and hunches matter too.

Since being affected by the Federal government’s open data requirements, libraries and their institutions have been building research data management services and opportunities for researchers. There were libraries and institutions ready to jump into the fray of an ever-evolving RDM landscape, and currently, these services are being assessed in order to expand the depth and breadth of their RDM offerings.

“Baseball and Research Data Management (RDM) Planning” by Regina Fisher Raboin

Abstract:  As any lover of the game of baseball knows, at this time of year it’s all about depth – what you built in the farm system and on the bench matters; the data crunched before and during the season comes into play when managing a team to the World Series. Gut feelings and hunches matter too.

Since being affected by the Federal government’s open data requirements, libraries and their institutions have been building research data management services and opportunities for researchers. There were libraries and institutions ready to jump into the fray of an ever-evolving RDM landscape, and currently, these services are being assessed in order to expand the depth and breadth of their RDM offerings.

Mapping the Scholarly Literature Found in Scopus on “Research Data Management”: A Bibliometric and Data Visualization Approach

Abstract:  INTRODUCTION Since the 2000s, interest in research data management (RDM) has grown considerably. As a result, a large body of literature has discussed a broad variety of aspects related to data management. But, few studies have examined and also interpreted from visual perception the intellectual structure and progressive development of the existing literature on RDM. METHODS Guided by five research questions, this study employed bibliometric techniques and a visualization tool (CiteSpace) to identify and analyze the patterns of the scholarly publications about RDM. RESULTS Through CiteSpace’s modeling and computing, the knowledge (or network) structures, significant studies, notable topics, and development trends in the literature of RDM were revealed. DISCUSSION The majority of the literature pertinent to RDM was published after 2002. Major research clusters within this interdisciplinary field include “scientific collaboration,” “research support service,” and “data literacy,” while the “scientific collaboration” research cluster was the most active. Topics such as “digital curation” and “information processing” appeared most frequently in the RDM literature. Additionally, there was a sharp increase in several specific topics, such as “digital library,” “big data,” and “data sharing.” CONCLUSION By looking into the “profile” of the literature on RDM, in terms of knowledge structure, evolving trends, and important topics in the domain, this work will add new information to current discussions about RDM, new service development, and future research focuses in this area.