| NSF Org: |
OAC Office of Advanced Cyberinfrastructure (OAC) |
| Recipient: |
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| Initial Amendment Date: | September 8, 2016 |
| Latest Amendment Date: | September 8, 2016 |
| Award Number: | 1649555 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Beth Plale
OAC Office of Advanced Cyberinfrastructure (OAC) CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | September 1, 2016 |
| End Date: | August 31, 2018 (Estimated) |
| Total Intended Award Amount: | $59,991.00 |
| Total Awarded Amount to Date: | $59,991.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
506 S WRIGHT ST URBANA IL US 61801-3620 (217)333-2187 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
1901 S. First, Suite A Champaign IL US 61820-7473 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | NSF Public Access Initiative |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
This EAGER project addresses the urgent need to better understand the research community's Data Management Plan (DMP) requirements and, based on this understanding, provides an open software tool that helps investigators generate structured and machine-readable Data Management Plans that fulfill both the researcher's need to easily deliver a standardized set of information to the funder, and the funder's need to analyze the information contained in DMPs. This allows funders to identify trends in data and software submission, repository use patterns, and carry out other analyses that can assist in understanding community use patterns and needs. The Principal Investigators (PIs) will leverage an existing DMP Tool built for the geosciences community by initially assessing the DMPs not only of the geosciences, but also the biological and social, behavioral, and economic sciences and upgrading the DMP Tool to serve those communities as well. Ultimately, the team will work to determine if this upgraded DMP Tool is extendable and scalable to all science, engineering, and educational research funded by the National Science Foundation. If successful, this will ultimately enhance the reproducibility and reuse of scientific research and help improve public access to supplementary scholarly products from federally funded research.
The National Science Foundation has required Data Management Plans (DMPs) for all grant proposals submitted for review since 2011. The DMPs submitted thus far are mostly free text and do not follow any specified format or structure and because of this limitation, current DMPs are not easy to compare or analyze. Consistent and comprehensive structured and machine-readable DMPs may substantially advance understanding of the data management landscape and address gaps that will improve data access which will lead to enhanced re-use and more reproducible science. The PIs propose to modify and upgrade the DMP Tool that has been developed and operated by IEDA (Interdisciplinary Earth Data Alliance) to serve the broadest research communities possible. This DMP Tool gathers relevant data management planning information from investigators in a structured manner into a relational database that can be mined and analyzed. As part of this project, they will analyze the information from the more than 1,350 DMPs that have already been generated with the IEDA DMP Tool to understand gaps, successes, and patterns of use. They will initially focus on the DMP requirements of science communities funded by the National Science Foundation's GEO, BIO, and SBE directorates, and use the results of this research to guide the development and prototyping of the extended version of the IEDA DMP Tool. They will subsequently focus on other directorates.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
This project has produced an online prototype Data Management Plan generation tool, called ezDMP, for researchers creating funding proposals. A Data Management Plan has been a required component of proposals for National Science Foundation funding since 2011. The tool was implemented after information gathering that sought to understand community and funding agency needs. ezDMP creates a machine readable Data Management Plan, suitable for inclusion in NSF proposals, with minimal burden to the researcher that allows the information in the Data Management Plan to be analyzed and understood. This is important since the Data Management Plan contains important information on community sharing and archiving practices for data and other research products. A machine readable structure serves two purposes. Firstly, it permits the extraction of this information by funding agencies and proposal submitting institutions, thereby allowing them to answer questions such as: How does the community use, produce, and share research artifacts? What repositories are being used for which artifacts? Where are there gaps in sharing and repository use? What types of artifacts are being produced? How are they being licensed and shared? Are some communities developing different practices than other communities and why? How do different DMP policies affects the types and structure of shared artifacts? Secondly, a machine readable DMP provides information to the researcher regarding shareable research artifacts, community sharing standards and practices, and available repositories and archiving options. The project engaged in outreach and sought community feedback on ezDMP.
The sharing of the artifacts that underlie research findings is an important step in ensuring transparency in how the findings were arrived at, and enabling reproducibility of the findings. In addition reuse of shared research artifacts, such as software and data, can accelerate scientific discovery, allow for the comparison of results, and shape future research questions. Reproducibility and reuse are key components of reliable and efficient research progress and society’s trust in the results of scientific research. Consistent and comprehensive structured and machine-readable DMPs is part of advancing understanding of the data management landscape and addressing gaps to improve public access to research artifacts, leading to enhanced re-use and more reproducible research.
Last Modified: 02/17/2019
Modified by: Victoria Stodden
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