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'''Keywords''': research data management, RDM, data sharing, open data, open science | '''Keywords''': research data management, RDM, data sharing, open data, open science | ||
==Introduction== | |||
Research data management (RDM), a term that encompasses activities related to the storage, organization, documentation, and dissemination of data{{efn|For the purposes of this report we are using the term “data” broadly to refer to the inputs or outputs required to evaluate, reproduce, or built upon the analyses or conclusions of a given research project. This includes, but is not limited to, raw data, processed data, research-related code, and documentation pertaining to study parameters and procedures.}}, is central to efforts aimed at maximizing the value of scientific investment (e.g., the Holdren memorandum<ref name="HoldrenIncreasing13">{{cite web |url=https://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/ostp_public_access_memo_2013.pdf |title=Increasing Access to the Results of Federally Funded Scientific Research |author=Holdren, J.P. |publisher=Office of Science and Technology Policy |date=22 February 2013}}</ref>) and addressing concerns related to the integrity of the research process (e.g., Collins and Tabak's discussion on reproducibility<ref name="CollinsPolicy14">{{cite journal |title=Policy: NIH plans to enhance reproducibility |journal=Nature |author=Collins, F.S.; Tabak, L.A. |volume=505 |issue=7485 |pages=612–13 |year=2014 |doi=10.1038/505612a}}</ref>). Unfortunately, when surveyed directly, researchers often acknowledge that they lack the skills and experience needed to manage and share their data effectively.<ref name="BaroneUnmet17">{{cite journal |title=Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators |journal=PLOS Computational Biology |author=Barone, L.; Williams, J.; Micklos, D. |volume=13 |issue=11 |pages=e1005858 |year=2017 |doi=10.1371/journal.pcbi.1005755 |pmid=29049281 |pmc=PMC5654259}}</ref><ref name="FedererBiomedical15">{{cite journal |title=Biomedical Data Sharing and Reuse: Attitudes and Practices of Clinical and Scientific Research Staff |journal=PLoS One |author=Federer, L.M.; Lu, Y.L.; Joubert, D.J. et al. |volume=10 |issue=6 |pages=e0129506 |year=2015 |doi=10.1371/journal.pone.0129506 |pmid=26107811 |pmc=PMC4481309}}</ref><ref name="TenopirResearch14">{{cite journal |title=Research data management services in academic research libraries and perceptions of librarians |journal=Library & Information Science Research |author=Tenopir, C.; Sandusky, R.J.; Allard, S.; Birch, B. |volume=36 |issue=2 |pages=84–90 |year=2014 |doi=10.1016/j.lisr.2013.11.003}}</ref> This disconnect demonstrates the need for tools that bridge the communication gap that exists between the research community, data service providers, and other local, national, and international data stakeholder groups. The development of one such tool, which we are tentatively referring to as “Support Your Data,” is the subject of this project report. | |||
==Footnotes== | |||
{{reflist|group=lower-alpha}} | |||
==References== | ==References== | ||
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==Notes== | ==Notes== | ||
This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added. | This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added. Footnotes were originally numbered but have been converted to lowercase alpha for this version. The original article lists references alphabetically, but this version—by design—lists them in order of appearance. | ||
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| Full article title | Support your data: A research data management guide for researchers |
|---|---|
| Journal | Research Ideas and Outcomes |
| Author(s) | Borghi, John A.; Abrams, Stephen; Lowenberg, Daniella; Simms, Stephanie; Chodacki, John |
| Author affiliation(s) | University of California Curation Center |
| Primary contact | Email: john dot borghi at ucop dot edu |
| Year published | 2018 |
| Volume and issue | 4 |
| Page(s) | e26439 |
| DOI | 10.3897/rio.4.e26439 |
| ISSN | 2367-7163 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | https://riojournal.com/articles.php?id=26439 |
| Download | https://riojournal.com/article/26439/download/pdf/ (PDF) |
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Abstract
Researchers are faced with rapidly evolving expectations about how they should manage and share their data, code, and other research materials. To help them meet these expectations and generally manage and share their data more effectively, we are developing a suite of tools which we are currently referring to as "Support Your Data." These tools— which include a rubric designed to enable researchers to self-assess their current data management practices and a series of short guides which provide actionable information about how to advance practices as necessary or desired—are intended to be easily customizable to meet the needs of researchers working in a variety of institutional and disciplinary contexts.
Keywords: research data management, RDM, data sharing, open data, open science
Introduction
Research data management (RDM), a term that encompasses activities related to the storage, organization, documentation, and dissemination of data[a], is central to efforts aimed at maximizing the value of scientific investment (e.g., the Holdren memorandum[1]) and addressing concerns related to the integrity of the research process (e.g., Collins and Tabak's discussion on reproducibility[2]). Unfortunately, when surveyed directly, researchers often acknowledge that they lack the skills and experience needed to manage and share their data effectively.[3][4][5] This disconnect demonstrates the need for tools that bridge the communication gap that exists between the research community, data service providers, and other local, national, and international data stakeholder groups. The development of one such tool, which we are tentatively referring to as “Support Your Data,” is the subject of this project report.
Footnotes
- ↑ For the purposes of this report we are using the term “data” broadly to refer to the inputs or outputs required to evaluate, reproduce, or built upon the analyses or conclusions of a given research project. This includes, but is not limited to, raw data, processed data, research-related code, and documentation pertaining to study parameters and procedures.
References
- ↑ Holdren, J.P. (22 February 2013). "Increasing Access to the Results of Federally Funded Scientific Research". Office of Science and Technology Policy. https://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/ostp_public_access_memo_2013.pdf.
- ↑ Collins, F.S.; Tabak, L.A. (2014). "Policy: NIH plans to enhance reproducibility". Nature 505 (7485): 612–13. doi:10.1038/505612a.
- ↑ Barone, L.; Williams, J.; Micklos, D. (2017). "Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators". PLOS Computational Biology 13 (11): e1005858. doi:10.1371/journal.pcbi.1005755. PMC PMC5654259. PMID 29049281. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5654259.
- ↑ Federer, L.M.; Lu, Y.L.; Joubert, D.J. et al. (2015). "Biomedical Data Sharing and Reuse: Attitudes and Practices of Clinical and Scientific Research Staff". PLoS One 10 (6): e0129506. doi:10.1371/journal.pone.0129506. PMC PMC4481309. PMID 26107811. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4481309.
- ↑ Tenopir, C.; Sandusky, R.J.; Allard, S.; Birch, B. (2014). "Research data management services in academic research libraries and perceptions of librarians". Library & Information Science Research 36 (2): 84–90. doi:10.1016/j.lisr.2013.11.003.
Notes
This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added. Footnotes were originally numbered but have been converted to lowercase alpha for this version. The original article lists references alphabetically, but this version—by design—lists them in order of appearance.
