The document discusses data management plan requirements for proposals submitted to the U.S. Department of Energy Office of Science for research funding. It provides context on the history of data management policies, outlines the four main requirements for inclusion of a data management plan, and suggests elements that should be included in the plan such as data types/sources, content/format, sharing/preservation, and protection. It also discusses tools like the Public Access Gateway for Energy and Science that can help manage access to research publications and data.
February 18 2014 NISO Virtual Conference
Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Capacity Building: Leveraging existing library networks to take on research data
Heidi Imker, Director of the Research Data Service, University of Illinois at Urbana-Champaign
NISO Virtual Conference
Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Enabling transparency and efficiency in the research landscape
Dr. Melissa Haendel, Associate Professor, Ontology Development Group, OHSU Library, Department of Medical Informatics and Epidemiology, Oregon Health & Science University
Research Data Access and Preservation Summit, 2014
San Diego, CA
March 26-28, 2014
Jared Lyle, ICPSR
Jennifer Doty, Emory University
Joel Herndon, Duke University
Libbie Stephenson, University of California, Los Angeles
Feb 26 NISO Training Thursday
Crafting a Scientific Data Management Plan
About the Training
Addressing a data management plan for the first time can be an intimidating exercise. Join NISO for a hands-on workshop that will guide you through the elements of creating a data management plan, including gathering necessary information, identifying needed resources, and navigating potential pitfalls. Participants explore the important components of a data management plan and critique excerpts of sample plans provided by the instructors.
This session is meant to be a guided, step-by-step session that will follow the February 18 NISO Virtual Conference, Scientific Data Management: Caring for Your Institution and its Intellectual Wealth.
About the Instructors
Kiyomi D. Deards, MSLIS, Assistant Professor, University of Nebraska-Lincoln Libraries
Jennifer Thoegersen, Data Curation Librarian, University of Nebraska-Lincoln Libraries
February 18 2015 NISO Virtual Conference Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Learning to Curate Research Data
Jennifer Doty, Research Data Librarian, Emory Center for Digital Scholarship, Emory University, Robert W. Woodruff Library
This presentation was provided by Clara Llebot of Oregon State University, during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
This presentation was provided by Carly Strasser of the Chan Zuckerberg Initiative during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
February 18 2015 NISO Virtual Conference Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Using data management plans as a research tool: an introduction to the DART Project
Amanda L. Whitmire, Ph.D., Assistant Professor, Data Management Specialist, Oregon State University Libraries & Press
February 18 2014 NISO Virtual Conference
Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Capacity Building: Leveraging existing library networks to take on research data
Heidi Imker, Director of the Research Data Service, University of Illinois at Urbana-Champaign
NISO Virtual Conference
Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Enabling transparency and efficiency in the research landscape
Dr. Melissa Haendel, Associate Professor, Ontology Development Group, OHSU Library, Department of Medical Informatics and Epidemiology, Oregon Health & Science University
Research Data Access and Preservation Summit, 2014
San Diego, CA
March 26-28, 2014
Jared Lyle, ICPSR
Jennifer Doty, Emory University
Joel Herndon, Duke University
Libbie Stephenson, University of California, Los Angeles
Feb 26 NISO Training Thursday
Crafting a Scientific Data Management Plan
About the Training
Addressing a data management plan for the first time can be an intimidating exercise. Join NISO for a hands-on workshop that will guide you through the elements of creating a data management plan, including gathering necessary information, identifying needed resources, and navigating potential pitfalls. Participants explore the important components of a data management plan and critique excerpts of sample plans provided by the instructors.
This session is meant to be a guided, step-by-step session that will follow the February 18 NISO Virtual Conference, Scientific Data Management: Caring for Your Institution and its Intellectual Wealth.
About the Instructors
Kiyomi D. Deards, MSLIS, Assistant Professor, University of Nebraska-Lincoln Libraries
Jennifer Thoegersen, Data Curation Librarian, University of Nebraska-Lincoln Libraries
February 18 2015 NISO Virtual Conference Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Learning to Curate Research Data
Jennifer Doty, Research Data Librarian, Emory Center for Digital Scholarship, Emory University, Robert W. Woodruff Library
This presentation was provided by Clara Llebot of Oregon State University, during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
This presentation was provided by Carly Strasser of the Chan Zuckerberg Initiative during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
February 18 2015 NISO Virtual Conference Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Using data management plans as a research tool: an introduction to the DART Project
Amanda L. Whitmire, Ph.D., Assistant Professor, Data Management Specialist, Oregon State University Libraries & Press
February 18 2015 NISO Virtual Conference Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Building Best Practices in Research Data Management: Tisch Library’s Initiatives
Regina F. Raboin, Science Research and Instruction Librarian/ Data Management Services Group Coordinator, Tisch Library, Tufts University
This presentation was provided by Maria Praetzellis of California Digital Library, during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
February 18 2015 NISO Virtual Conference
Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Network Effects: RMap Project
Sheila M. Morrissey, Senior Researcher, ITHAKA
RDAP 15 EarthCollab: Connecting Scientific Information Sources using the Sema...ASIS&T
Research Data Access and Preservation Summit, 2015
Minneapolis, MN
April 22-23, 2015
Erica M. Johns, Jon Corson-Rikert, Huda J. Khan, Dean B. Krafft and Matthew S. Mayernik
RDAP14: Building a data management and curation program on a shoestring budgetASIS&T
Research Data Access and Preservation Summit, 2014
San Diego, CA
Margaret Henderson
Director, Research Data Management
Virginia Commonwealth University
Poster RDAP13: Data information literacy multiple paths to a single goalASIS&T
Jake Carlson, Jon Jeffryes, Brian Westra and Sarah Wright
Data Information Literacy: Multiple Paths to a Single Goal
Research Data Access & Preservation Summit 2013
Baltimore, MD April 4, 2013 #rdap13
RDAP 15 Local ICPSR Data Curation Workshop Pilot ProjectASIS&T
Research Data Access and Preservation Summit, 2015
Minneapolis, MN
April 22-23, 2015
Linda Detterman, Jennifer Doty, Jared Lyle, Amy Pienta, Lizzy Rolando and Mandy Swygart-Hobaugh
This document summarizes research data support services at Tufts University. It discusses the context at Tufts including relevant support organizations. It describes collaborations between the libraries, technology services, and research centers to provide data management resources like the Tufts Data Lab, a data management team, and Carpentries data workshops. Ongoing work includes developing guidance on data storage, a centralized support website, and expanding the use of the Dataverse sharing platform.
This presentation was provided by Joe Zucca of the University of Pennsylvania, during Session Five of the NISO event "Assessment Practices and Metrics for the 21st Century," held on November 22, 2019.
RDAP14: Collaboration and tension between institutions and units providing da...ASIS&T
Research Data Access and Preservation Summit, 2014
San Diego, CA
March 26-28, 2014
David Minor, University of California, San Diego
Amanda Whitmire, Oregon State University
Stephanie Wright, University of Washington
Lisa Zilinski, Purdue University
Poster RDAP13: Research Data in eCommons @ Cornell: Present and FutureASIS&T
Wendy A. Kozlowski, Dianne Dietrich, Gail Steinhart and Sarah Wright
Cornell University Library, Ithaca, NY
Research Data in eCommons @ Cornell: Present and Future
Research Data Access & Preservation Summit 2013
Baltimore, MD April 4, 2013 #rdap13
This presentation was provided by Kristi Holmes of Northwestern University during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
Poster RDAP13: A Workflow for Depositing to a Research Data Repository: A Cas...ASIS&T
Betsy Gunia, David Fearon, Benjamin Brosius, Tim DiLauro
JHU Data Management Services
Johns Hopkins University Sheridan Libraries
A Workflow for Depositing to a Research Data Repository: A Case Study for Archiving Publication Data
Research Data Access & Preservation Summit 2013
Baltimore, MD April 4, 2013 #rdap13
RDAP14: Policy Recommendations for Institutions to Serve as Trustworthy Stewa...ASIS&T
Research Data Access and Preservation Summit, 2014
San Diego, CA
March 26-28, 2014
J. Steven Hughes
NASA Jet Propulsion Laboratory
Robert R. Downs
Center for International Earth Science Information Network (CIESIN), Columbia University
David Giaretta
Alliance for Permanent Access
RDAP14: DataONE: Data Observation Network for EarthASIS&T
Research Data Access and Preservation Summit, 2014
San Diego, CA
March 26-28, 2014
Amber E. Budden, Director for Community Engagement and Outreach, DataONE, University of New Mexico
RDAP 16: DMPs and Public Access: Agency and Data Service ExperiencesASIS&T
Research Data Access and Preservation Summit, 2016
Atlanta, GA
May 4-7, 2016
Outline for Panel 5, "DMPs and Public Access: Agency and Data Service Experiences"
Panel Lead:
Margaret Henderson, Virginia Commonwealth University
The document discusses big data use cases and requirements. It provides 51 detailed use cases across various domains that generate many terabytes to petabytes of data. It also describes extracting 437 specific requirements from the use cases and analyzing trends. The next steps involve matching requirements to a reference architecture and prioritizing use cases for implementation.
February 18 2015 NISO Virtual Conference Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Building Best Practices in Research Data Management: Tisch Library’s Initiatives
Regina F. Raboin, Science Research and Instruction Librarian/ Data Management Services Group Coordinator, Tisch Library, Tufts University
This presentation was provided by Maria Praetzellis of California Digital Library, during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
February 18 2015 NISO Virtual Conference
Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Network Effects: RMap Project
Sheila M. Morrissey, Senior Researcher, ITHAKA
RDAP 15 EarthCollab: Connecting Scientific Information Sources using the Sema...ASIS&T
Research Data Access and Preservation Summit, 2015
Minneapolis, MN
April 22-23, 2015
Erica M. Johns, Jon Corson-Rikert, Huda J. Khan, Dean B. Krafft and Matthew S. Mayernik
RDAP14: Building a data management and curation program on a shoestring budgetASIS&T
Research Data Access and Preservation Summit, 2014
San Diego, CA
Margaret Henderson
Director, Research Data Management
Virginia Commonwealth University
Poster RDAP13: Data information literacy multiple paths to a single goalASIS&T
Jake Carlson, Jon Jeffryes, Brian Westra and Sarah Wright
Data Information Literacy: Multiple Paths to a Single Goal
Research Data Access & Preservation Summit 2013
Baltimore, MD April 4, 2013 #rdap13
RDAP 15 Local ICPSR Data Curation Workshop Pilot ProjectASIS&T
Research Data Access and Preservation Summit, 2015
Minneapolis, MN
April 22-23, 2015
Linda Detterman, Jennifer Doty, Jared Lyle, Amy Pienta, Lizzy Rolando and Mandy Swygart-Hobaugh
This document summarizes research data support services at Tufts University. It discusses the context at Tufts including relevant support organizations. It describes collaborations between the libraries, technology services, and research centers to provide data management resources like the Tufts Data Lab, a data management team, and Carpentries data workshops. Ongoing work includes developing guidance on data storage, a centralized support website, and expanding the use of the Dataverse sharing platform.
This presentation was provided by Joe Zucca of the University of Pennsylvania, during Session Five of the NISO event "Assessment Practices and Metrics for the 21st Century," held on November 22, 2019.
RDAP14: Collaboration and tension between institutions and units providing da...ASIS&T
Research Data Access and Preservation Summit, 2014
San Diego, CA
March 26-28, 2014
David Minor, University of California, San Diego
Amanda Whitmire, Oregon State University
Stephanie Wright, University of Washington
Lisa Zilinski, Purdue University
Poster RDAP13: Research Data in eCommons @ Cornell: Present and FutureASIS&T
Wendy A. Kozlowski, Dianne Dietrich, Gail Steinhart and Sarah Wright
Cornell University Library, Ithaca, NY
Research Data in eCommons @ Cornell: Present and Future
Research Data Access & Preservation Summit 2013
Baltimore, MD April 4, 2013 #rdap13
This presentation was provided by Kristi Holmes of Northwestern University during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
Poster RDAP13: A Workflow for Depositing to a Research Data Repository: A Cas...ASIS&T
Betsy Gunia, David Fearon, Benjamin Brosius, Tim DiLauro
JHU Data Management Services
Johns Hopkins University Sheridan Libraries
A Workflow for Depositing to a Research Data Repository: A Case Study for Archiving Publication Data
Research Data Access & Preservation Summit 2013
Baltimore, MD April 4, 2013 #rdap13
RDAP14: Policy Recommendations for Institutions to Serve as Trustworthy Stewa...ASIS&T
Research Data Access and Preservation Summit, 2014
San Diego, CA
March 26-28, 2014
J. Steven Hughes
NASA Jet Propulsion Laboratory
Robert R. Downs
Center for International Earth Science Information Network (CIESIN), Columbia University
David Giaretta
Alliance for Permanent Access
RDAP14: DataONE: Data Observation Network for EarthASIS&T
Research Data Access and Preservation Summit, 2014
San Diego, CA
March 26-28, 2014
Amber E. Budden, Director for Community Engagement and Outreach, DataONE, University of New Mexico
RDAP 16: DMPs and Public Access: Agency and Data Service ExperiencesASIS&T
Research Data Access and Preservation Summit, 2016
Atlanta, GA
May 4-7, 2016
Outline for Panel 5, "DMPs and Public Access: Agency and Data Service Experiences"
Panel Lead:
Margaret Henderson, Virginia Commonwealth University
The document discusses big data use cases and requirements. It provides 51 detailed use cases across various domains that generate many terabytes to petabytes of data. It also describes extracting 437 specific requirements from the use cases and analyzing trends. The next steps involve matching requirements to a reference architecture and prioritizing use cases for implementation.
This document discusses data publishing and management. It introduces the advantages of publishing research data, including increasing citations, recognition and meeting grant requirements. It outlines best practices for data management planning and provides examples of data publishing platforms like SHaRED. The document advises that major journals and funding bodies now require data publication in open repositories to promote open access and data sharing in science.
Funder requirements for Data Management PlansSherry Lake
This document discusses funder requirements for data management and sharing. It notes that major funders like the National Science Foundation (NSF) and National Institutes of Health (NIH) require applicants to submit a data management plan. These plans describe how research data will be organized, preserved, and shared. The document provides details on what funders expect to see in a data management plan, including a description of the data, metadata standards, data access and sharing policies, and plans for long-term data preservation. It also lists other funders that require applicants to have a data management or sharing plan.
The Department of Energy's Integrated Research Infrastructure (IRI)Globus
We will provide an overview of DOE’s IRI initiative as it moves into early implementation, what drives the IRI vision, and the role of DOE in the larger national research ecosystem.
Data management planning in the Australian funding landscape by Sarah OlesenMarta Ribeiro
Data management planning in the Australian funding landscape by Sarah Olesen at eResearch Australasia Conference
1.Australian Code for the Responsible Conduct of Research (2007)
2. National Statement on Ethical Conductin Human Research (2007 – updated 2014)
Supporting Research Data Management at the University of StirlingLisa Haddow
The Digital Curation Centre (DCC) provides support to universities to help them manage research data. This includes tools to assess data needs and risks, plan data management, and develop policies. The DCC can help universities develop data management strategies, provide training to researchers, and pilot tools. Its goal is to build research data management capacity across UK higher education. The DCC is working intensively with 18 universities to increase capabilities in these areas over the next year.
A presentation by Dr Lesley Thompson, Director of Science & Engineering, EPSRC - given at the Open Science Showcase held by the Royal Society of Chemistry on 26 February 2014.
Data sharing promotes many goals of the NIH research endeavor. It is particularly important for unique data that cannot be readily replicated. Data sharing allows scientists to expedite the translation of research results into knowledge, products, and procedures to improve human health. Do you know what a data sharing plan should include? Are you aware of common practices and standards for data sharing? Do you know what services are available to help share your data responsibly? This workshop will begin to address these questions. Q&A will follow the presentation. Anyone interested in or planning to apply for NIH funding should attend. Note: The NIH data-sharing policy applies to applicants seeking $500,000 or more in direct costs in any year of the proposed research.
Survey of research data management practices up2010digschol2011heila1
An analysis of data management practices at a large South African university was conducted through interviews with researchers and students to identify needs and challenges. The findings showed that while data collection methods vary, data storage is often ad hoc with no centralized support or resources. Researchers expressed a need for a central university server or repository for secure data storage and assistance with time constraints. It was concluded that a formal research data management program and staff support are needed to improve current practices.
The document provides logistics for a webinar on data curation profiles and the DMPTool. It includes instructions for calling into the audio, asking questions in the chat, and finding recordings and slides. The webinar will discuss the history of data curation profiles, comparing them to data management plans, and a case study of using data curation profiles. Data curation profiles involve interviewing researchers about their data practices and needs in order to understand how to support them, while data management plans focus on requirements for funding. Both tools can help librarians engage with researchers, though data curation profiles provide a more in-depth understanding of researchers' full data lifecycles.
This document discusses open access to research data. It states that open access can produce higher quality data, publications, and usage of data. It also notes that open access can lead to higher recognition for researchers and more transparency. While some scientists view data as proprietary, open access is meant to have a positive impact by allowing other researchers to reproduce and build upon published work. The document advocates for establishing institutional policies and providing support for open access in order to improve scientific quality and maximize the benefits of research.
How to Comply with Grants: Writing Data Management Plans and Providing Public...Margaret Henderson
This document provides an overview of federal data management plan and public access requirements. It discusses what constitutes research data and outlines what must be included in a data management plan. It then reviews policies from agencies such as NIH, NSF, DOD and others regarding submitting publications to public repositories and making data publicly available. The policies generally require making peer-reviewed publications open access within 12 months of publication and providing a plan for sharing and preserving research data. Noncompliance may result in withholding of funds.
This document discusses licensing research data for reuse. It begins by providing a scenario where a user has downloaded a dataset but is unsure what they can do with the data due to licensing. It then discusses that licensing is critical to enabling data reuse and citation. It provides information on AusGOAL, the Australian open access and licensing framework, and notes it is recommended for data publishing by ANDS partners. It also includes links to licensing guides and FAQs. In summary, the document emphasizes the importance of data licensing for enabling reuse and outlines Australia's recommended licensing system.
This document summarizes a JISC webinar on meeting the research data challenge. It discusses:
1) JISC's role in providing national research infrastructure and supporting universities to make effective use of technology in research and data management.
2) The challenges of increasing data volumes, diversity, and lack of understanding around data management best practices.
3) Key drivers to improve data management including research integrity, funder policies, freedom of information regulations, and preparing for the Research Excellence Framework.
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NISO Virtual Conference Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
1. Data Management Plan Requirements
Laura Biven, PhD
Senior Science and Technology Advisor
Office of the Deputy Director for Science Programs (SC-2)
U.S. Department of Energy
Laura.Biven@science.doe.gov
NISO: Scientific Data Management
February18, 2015
2. Outline
• DOE Office of Science 101
• Context and History for DMP requirements
• DOE Public Access Plan
• Office of Science Statement on Digital Data
Management
2
3. Office of Science
By the numbers
Shown is a portion of SLAC's two-mile-long linear accelerator (or linac), which
prov ides the electron beam f or the new Linac Coherent Light Source (LCLS) – the
world’s f irst hard x-ray , f ree-electron laser. For nearly 50 y ears, SLAC's linac had
produced high-energy electrons f or phy sics experiments. Now researchers use
the v ery intense X-ray pulses (more than a billion times brighter than the most
powerf ul existing sources) much like a high-speed camera to take stop-motion
pictures of atoms and molecules in motion, examining f undamental processes on
f emtosecond timescales.
Support for basic
research in the physical
sciences by agency.
Source: NSF Science
and Engineering
Indicators 2012
SC’s mission is to deliver scientific discoveries
and major scientific tools to transform our under-
standing of nature and advance the energy,
economic, and national security of the U.S.
Research
SC supports 47% of the U.S. Federal support of basic
research in the physical sciences;
~22,000 Ph.D. scientists, grad students, engineers, and
support staff at >300 institutions, including all 17 DOE labs;
U.S. and world leadership in high-performance computing
and computational sciences;
Major U.S. supporter of physics, chemistry, materials
sciences, and biology for discovery science and for energy
sciences;
Scientific User Facilities
The world’s largest collection of scientific user facilities (aka
research infrastructure) operated by a single organization in
the world, used by 31,000 researchers eachyear.
3
4. Quick-Facts about the DOE Office of Science
4
Advanced Scientific Computing
Research
Basic Energy Sciences
Biologicaland Environmental
Research
Fusion EnergySciences
High Energy Physics
Nuclear Physics
5. 5
Office of Science User Facilities 2013
SSRL
ALS
APS
NSLS
LCLS
HFIR
Lujan
SNS
CNM
Foundry
CNMS
CINT
CFN
NERSC
OLCF
ACLF
Tevatron
FACET
B-Factory
RHIC
TJNAF
ATLAS
EMSL
JGI
ARM
DIII-D
C-Mod
NSTX
FES
SSRL
ALS
APS
NSLS
HFIR
Lujan
SNS
NSRCs
NERSC
OLCF
ALCF
Fermilab
Accelerator
Complex
B-Factory
RHIC
TJNAF
ATLAS
EMSL
JGI
ARM
DIII-D
Alcator
Light Sources
Neutron
Sources
Nano
Centers
Computing
Facilities
High energyphysics
facilities
Nuclear physics
facilities
Bio & Enviro
Facilities
LCLS
Does not include LHC; HEP supports
about 1,700 scientists, technicians, and
engineers at the LHC.
Basic Energy Sciences
Advanced Scientific
Research Computing
High Energy Physics
Nuclear Physics
Biological & Environmental
Research
Fusion Energy Sciences
8. Data-Intensive Science Drives Exponential Network Growth
8
Science Data Transferred
Each Month, in PB
20182004 2006 2008 2010 2012 2014 2016
100
0.01
0.1
1
10
Year
Internet Growth:
(30 – 40%/y ear)
ESnet Growth:
~70%/y ear
9. • COMPETES2010 “Interagency Public Access Committee”
• Office of Science Working Group on Digital Data
• Office of Science FACAReports (2011)
• OSTP Requestfor Information (2012)
• Office of Science User Facility Input (2013)
• OSTP Memo“Increasing Access to the Results of Federally Funded
Scientific Research” (Feb.,2013)
• DOE Public Access Plan and
Office of Science Statementon Digital Data Management(July,2014)
Brief History – Data
9
Data
Management
Policies of other
Agencies
Global
Policy
Context
10. OSTP Memo and the DOE Response
10
Increasing Access to the Resultsof Federally Funded
ScientificResearch
http://www.whitehouse.gov/sites/default/files/microsites/ostp/ostp_public_access_memo_2013.pdf
DOE PublicAccess Plan is
available on the DOE Open
Government website
http://energy.gov/downloads/doe-public-access-plan
11. DOE Public Access Plan: A Department-wide policy
The Office of Science intends to publish its data management
plan requirements on July 28, 2014. Starting October 1, 2014,
the requirements will be included in all invitations and
solicitationsfor research funding issued by the Office of
Science.
Other DOE Offices and elements will implement data
management plan requirements no later than October 1, 2015.
The result will be a Department-wide policy. Should it be
necessary, additional supplementary guidance and
requirements addressing specific needs would be issued by
each Office or element and coordinated centrally.
11For Internal Use Only
13. Principles
• Effective data management has the potential to increase the pace of scientific
discoveryand promote more efficientand effective use of government funding
and resources.Data management planning should be an integral part of
research planning.
• Sharing and preserving data are central to protecting the integrity of science
by facilitating validation of results and to advancing science by broadening the
value of research data to disciplines other than the originating one and to
society at large. To the greatest extent and with the fewestconstraints
possible,and consistentwith the requirements and other principles of this
Statement, data sharing should make digital research data available to and
useful for the scientific community, industry, and the public.
• Not all data need to be shared or preserved.The costs and benefits of doing
so should be considered in data management planning.
Office of Science Statement on Digital Data Management
http://science.energy.gov/funding-opportunities/digital-data-management/
13
14. Office of Science Statement on Digital Data Management
• Requirements apply to proposals for research funding
• Requirements apply to proposals submitted for new,
renewal, and some supplemental research funding
• Requirements apply to proposals regardless of the PI’s
institution
• Requirements apply to proposals submitted in response to
solicitationsand invitations issued after Oct. 1, 2014
• Requirements do not apply to applications to use Office of
Science user facilities.
14
15. Requirements
All proposals submitted to the Office of Science for research funding must
include a Data ManagementPlan (DMP)that addresses the following
requirements:
1. DMPs should describe whether and how data generated in the course of the
proposedresearchwill be shared and preserved.If the plan is not to share
and/or preserve certain data, then the plan must explain the basis of the
decision(for example, cost/benefitconsiderations,other parameters of
feasibility, scientific appropriateness,or limitations discussed in Requirement
#4).At a minimum, DMPs must describe howdata sharing and preservation
will enable validation of results, or how results could be validated if data are
not shared or preserved.
Office of Science Statement on Digital Data Management
15
16. Requirement 2 of 4
2. DMPs should provide a plan for making all research data displayed in
publications resulting from the proposed researchopen, machine-readable,
and digitally accessible to the public at the time of publication. This includes
data that are displayed in charts, figures, images, etc. In addition, the
underlying digital research data used to generate the displayed data should
be made as accessible as possible to the public in accordance with the
principles stated above. This requirement could be met by including the data
as supplementary information to the published article, or through other
means. The published article should indicate how these data can be
accessed.
Office of Science Statement on Digital Data Management
16
17. Requirement 3 of 4
3. DMPs should consult and reference available information about data
management resources to be used in the course of the proposed research.In
particular, DMPs that explicitly or implicitly commit data management
resources at a facility beyond what is conventionally made available to
approved users should be accompanied by written approval from that facility.
In determining the resources available for data management at Office of
Science User Facilities, researchers should consult the published description
of data management resources and practices at that facility and reference it in
the DMP. Information about other Office of Science facilities can be found in
the additional guidance from the sponsoring program.
Office of Science Statement on Digital Data Management
17
19. Requirement 4 of 4
4. DMPs must protect confidentiality, personal privacy, Personally Identifiable
Information, and U.S. national, homeland, and economic security; recognize
proprietary interests, business confidential information, and intellectual
property rights; avoid significant negative impact on innovation, and U.S.
competitiveness;and otherwise be consistentwith all applicable laws,
regulations, and DOE orders and policies.There is no requirement to share
proprietary data.
• DMPs will be reviewed as part of the overall Office of Scienceresearch proposal merit
review process.
• Additional requirements and review criteriafor the DMP may be identified by the
sponsoring program or sub-program, or in the solicitation.
Office of Science Statement on Digital Data Management
19
20. Digital Research Data:
The term digital data encompasses a wide variety of information stored in digital form
including: experimental, observational, and simulation data; codes, software and
algorithms; text; numeric information; images; video; audio; and associated metadata. It
also encompasses information in a variety of different forms including raw, processed, and
analyzed data, published and archived data.
This statement focuses on digital research data, which are researchdata that can be
stored digitally and accessed electronically. OMB Circular A110 defines research data as
follows:
“Research data is defined as the recorded factual material commonly accepted in the scientific
community as necessary to validate research findings, but not any of the following: preliminary
analyses, drafts of scientific papers, plans for future research, peer reviews, or communications
with colleagues. This 'recorded' material excludes physical objects (e.g., laboratory samples).
Research data also do not include:
(A) Trade secrets, commercial information, materials necessary to be held confidential by a
researcher until they are published, or similar information which is protected under law; and
(B) Personnel and medical information and similar information the disclosure of which would
constitute a clearly unwarranted invasion of personal privacy, such as information that could be
used to identify a particular person in a research study.”
Definitions
20
21. Data Preservation:
Data preservationmeans providing for the usability of data beyond the lifetime of
the research activity that generated them.
Data Sharing:
Data sharingmeans making data available to people other than those who have
generated them. Examples of data sharing range from bilateral communications
with colleagues,to providing free,unrestricted access to the public through, for
example, a web-based platform.
Validate:
In the context of this statement, validatemeans to support, corroborate,verify, or
otherwise determine the legitimacy of the research findings. Validation of
research findings could be accomplished by reproducing the original experiment
or analyses; comparing and contrasting the results against those of a new
experiment or analyses; or by some other means.
Definitions
21
22. Suggested Elements for a Data Management Plan
22
• Data Types and Sources
• Content and Format
• Sharing and Preservation
• Protection
• Rationale
23. • Data Types and Sources.Abrief, high-level descriptionof the data to be
generated or used through the course of the proposedresearchand which of
these are considered digital research data necessary to validate the research
findings.
• Contentand Format.Astatement of plans for data and metadata content
and format including, where applicable, a descriptionof documentation plans,
annotation of relevant software, and the rationale for the selectionof
appropriate standards. (Existing, accepted community standards should be
used where possible.Where community standards are missing or inadequate,
the DMP could propose alternate strategies that facilitate sharing, and should
advise the sponsoring program of any need to develop or generalize
standards.)
Suggested Elements
23
24. • Sharing and Preservation. A description of the plans for data sharing and
preservation. This should include, when appropriate:
• the anticipated means for sharing and the rationale for any restrictions on who may access the
data and under what conditions;
• a timeline for sharing and preservation that addresses both the minimum length of time the data
will be available and any anticipated delay to data access after research findings are published;
• any special requirements for data sharing, for example, proprietary software needed to access
or interpret data, applicable policies, provisions, and licenses for re-use and re-distribution, and
for the production of derivatives, including guidance for how data and data products should be
cited;
• any resources and capabilities (equipment, connections, systems, software, expertise, etc.)
requested in the research proposal that are needed to meet the stated goals for sharing and
preservation. (This could reference the relevant section of the associated research proposal
and budget request);
• cost/benefit considerations to support whether/where the data will be preserved after direct
project funding ends and any plans for the transfer of responsibilities for sharing and
preservation;
• whether, when, or under what conditions the management responsibility for the research data
will be transferred to a third party (e.g. institutional, or community repository);
• any other future decision points regarding the management of the research data including plans
to reevaluate the costs and benefits of data sharing and preservation.
Suggested Elements
24
25. • Protection.Astatement of plans, where appropriate and necessary,to
protect confidentiality, personal privacy, Personally Identifiable Information,
and U.S. national, homeland, and economic security; recognize proprietary
interests, business confidential information, and intellectual property rights;
and avoid significant negative impact on innovation, and U.S.
competitiveness.
• Rationale.A discussionof the rationale or justification for the proposed data
management plan including, for example, the potential impact of the data
within the immediate field and in other fields,and any broader societalimpact.
Suggested Elements
25
29. Public Access Gateway for Energy and Science (PAGESBeta)
• Full text versions of peer-reviewed articles resulting from DOE
supported research are publicly accessible through PAGESBeta
• DOE-supported researchers are required to submit metadata for peer-
reviewed publications and full text or links to accepted manuscripts
starting in FY 2015
• PAGESBeta will link to full-text accepted manuscripts or articles after a
12-month post-publication administrative interval.
• Researchers should acknowledge DOE funding appropriately
http://science.energy.gov/funding-opportunities/acknowledgements/
29
http://www.osti.gov/pages/