The NIH public access policy did not harm biomedical journals

Abstract:  The United States National Institutes of Health (NIH) imposed a public access policy on all publications for which the research was supported by their grants; the policy was drafted in 2004 and took effect in 2008. The policy is now 11 years old, yet no analysis has been presented to assess whether in fact this largest-scale US-based public access policy affected the vitality of the scholarly publishing enterprise, as manifested in changed mortality or natality rates of biomedical journals. We show here that implementation of the NIH policy was associated with slightly elevated mortality rates and mildly depressed natality rates of biomedical journals, but that birth rates so exceeded death rates that numbers of biomedical journals continued to rise, even in the face of the implementation of such a sweeping public access policy.

 

“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.

A Great Development on the GREAT Act – SPARC

“Yesterday, the U.S. Senate unanimously passed the Grant Reporting Efficiency and Agreements Transparency (GREAT) Act (S. 1829). The GREAT Act aims to simplify and harmonize federal grant recipient reporting obligations. Specifically, it requires the creation of a comprehensive and standardized data structure covering all data elements reported by recipients of federal awards — including grant and cooperative agreements. It standardizes how the government reports its grants data much in the same way the 2014 DATA Act did for agency spending.

By replacing outdated documents with open data, the GREAT Act will deliver transparency for grantmaking agencies and the public and allow grantees to automate their reporting processes, reducing compliance costs. The bill fosters increased federal oversight and transparency into the distribution of federal funding and facilitates the adoption of modern technologies….”

A Great Development on the GREAT Act – SPARC

“Yesterday, the U.S. Senate unanimously passed the Grant Reporting Efficiency and Agreements Transparency (GREAT) Act (S. 1829). The GREAT Act aims to simplify and harmonize federal grant recipient reporting obligations. Specifically, it requires the creation of a comprehensive and standardized data structure covering all data elements reported by recipients of federal awards — including grant and cooperative agreements. It standardizes how the government reports its grants data much in the same way the 2014 DATA Act did for agency spending.

By replacing outdated documents with open data, the GREAT Act will deliver transparency for grantmaking agencies and the public and allow grantees to automate their reporting processes, reducing compliance costs. The bill fosters increased federal oversight and transparency into the distribution of federal funding and facilitates the adoption of modern technologies….”

MIT Framework for Publisher Contracts | Scholarly Publishing – MIT Libraries

“The core principles of an MIT Framework for publisher contracts are:

No author will be required to waive any institutional or funder open access policy to publish in any of the publisher’s journals.
No author will be required to relinquish copyright, but instead will be provided with options that enable publication while also providing authors with generous reuse rights.
Publishers will directly deposit scholarly articles in institutional repositories immediately upon publication or will provide tools/mechanisms that facilitate immediate deposit.
Publishers will provide computational access to subscribed content as a standard part of all contracts, with no restrictions on non-consumptive, computational analysis of the corpus of subscribed content.
Publishers will ensure the long-term digital preservation and accessibility of their content through participation in trusted digital archives.
Institutions will pay a fair and sustainable price to publishers for value-added services, based on transparent and cost-based pricing models….”