SlideShare une entreprise Scribd logo
1  sur  29
Guidelines and
Resources for OSTP
Data Access Plans
ICPSR
September 2013
www.icpsr.umich.edu/datamanagement
The OSTP Memo
Guidelines for Response
• Released February 2013, this memo directs funding
agencies with an annual R&D budget over $100 million to
develop a public access plan for disseminating the results
of their research
• ICPSR stresses that standards and guidelines for many of
the requirements currently exist
• The slides to follow provide an overview of the access
plan elements including guidelines and resources on how
to respond to meet digital data requirements in the
memo
The OSTP Memo – A Review
• Released February 22, 2013
• A concern for investment: “Policies that mobilize these
publications and data for re-use through preservation and
broader public access also maximize the impact and
accountability of the Federal research investment.”
• Federal agencies with over $100 M annually in R&D
expenditures to develop plans to support increased public
access to the results of research funded by the Federal
Government
• Plans to contain eight points
The Eight Points of the Plan
1. Strategy for leveraging existing archives
2. Strategy to improve the public’s ability to locate and access digital
data
3. Approach to optimize search, archival, and dissemination features
that encourage innovation in accessibility & interoperability and
ensure long-term stewardship
4. A plan to notify awardees & researchers of their obligations
5. Strategy for measuring and enforcing compliance with the plan
6. Identification of resources within the existing agency budget to
implement plan
7. Timeline for implementation
8. Identification of special circumstances that prevent the agency from
meeting memo objectives
Data Portion of Memo - 13 Elements
• The portion of the memo describing objectives
for public access to data stresses 13 elements
for a public access plan
• The elements are also summarized online
within ICPSR’s Web site:
http://icpsr.umich.edu/content/datamanagement/ostp.html
Maximize Access
"Maximize access, by the general public and without charge, to digitally
formatted scientific data created with Federal funds“
• Increasing access to research data prevents the duplication of
effort, provides accountability and verification of research results, and
increases opportunities for innovation and collaboration.
• Finding and accessing data in repositories requires descriptive metadata
("data about data") in standard, machine-actionable form. Metadata
help search engines find data, and help researchers understand the
context of data collections.
• Standards already exist: see Data Documentation Initiative
– http://www.ddialliance.org/
Maximize Access cont.
• Access also involves knowing how to interpret the data. Incomplete data
limit reuse. Obsolete data formats can be unreadable.
– Repositories 'curate' or enhance data to make it complete, self-
explanatory, and usable for future researchers. This includes adding
descriptive labels, correcting coding errors, gathering documentation, and
standardizing the final versions of files. This is called “data curation.”
– Like museums that curate art or artifacts for study and understanding now
and in the future, data archives curate data with the same goals.
• Data curation is crucial to maximizing access. Resources for curating
data:
– ICPSR's Guide to Social Science Data Preparation and Archiving
– UK Data Archive's Managing and Sharing Data guide.
Protect Confidentiality and Privacy
• It is critically important to protect the
identities of research subjects.
• Disclosure risk is a term that is often used
for the possibility that a data record from a
study could be linked to a specific person.
• Concerns about disclosure risk have grown
as more datasets have become available
online, and it has become easier to link
research datasets with publicly available
external databases.
Protect Confidentiality and Privacy cont.
Protecting confidentiality of research subjects is not a viable
argument for not sharing data. Infrastructure, including virtual
and physical data enclaves, already exists:
• Restricted-Use Data are made available for research
purposes for use by investigators who agree to stringent
conditions for the use of the data and its physical
safekeeping.
• Enclave Data are those datasets which present especially
acute disclosure risks. They can be accessed only on-site in
ICPSR's physical data enclave in Ann Arbor. Investigators
must be approved. Their notes and analytic output are
reviewed by ICPSR staff.
Preserve Intellectual Property Rights
and Commercial Interests
Original research may be both
commercially valuable and proprietary.
There are several approaches to
managing these interests, including:
– Tailor copyright and patent licenses, such
as through Creative Commons licenses
– Establish an embargo period or delayed
dissemination on distribution.
Balance Demands of Long-term
Preservation and Access
• Preserving digital data requires much more than
storing files on a server, desktop, or in the cloud!
• Digital preservation is the active and ongoing
management of digital content to lengthen the
lifespan and mitigate against loss, including physical
deterioration, format obsolescence, and hardware and
software failure.
Balance Demands of Long-term
Preservation and Access cont.
• Not all data are worth preserving
indefinitely; less valuable or easily
producible data may be preserved for
shorter periods.
• Establish selection and appraisal guidelines
that make it clear what to save or discard.
– Selection criteria consider factors like
availability, confidentiality, copyright, quality, f
ile format, and financial commitment.
Use of Data Management Plans
• Data management plans describe how researchers
will provide for long-term preservation of, and
access to, scientific data in digital formats.
• Data management plans provide opportunities for
researchers to manage and curate their data more
actively from project inception to completion.
• See ICPSR's resource: Guidelines for Effective Data
Management Plans
Include Cost of Data Management in Funding
Proposals
• Data management services carry real costs, ranging from
personnel to storage to software.
• Maintenance costs are routinely built into physical
infrastructure development, so too should data management
costs be built into data development.
• Long-term access to data requires durable institutions that plan
on a scale of decades and even generations.
• Cost resources:
– DataONE's Provide budget information for your data
management plan
– UK Data Archive's Costing Tool: Data Management Planning.
Evaluate Data Management Plans &
Ensure Compliance
• Plans help researchers prepare for working with
and preserving data, repositories get ready to
accession and provide access, and agencies to
understand the community needs for archiving
and access. Evaluation helps refine plans so they
are realistic and attainable.
• If data management plans are to be a standard
component of funding applications, funding
recipients should be held accountable for
diversions from the originally stated plans.
Promote Public Deposit of Data
• Public deposit of data helps to ensure the long-term
accessibility and preservation of the data.
• It removes the burden of ongoing maintenance and care (and
user support) from the researcher and provides a stable system
to which data can be entrusted.
• Many sustainable online repositories are already available to
host and archive research data. These may include discipline-
specific repositories, archives administered by funding
agencies, or institutional repositories.
• Databib, a searchable directory of over 500 research data
repositories, can help locate relevant repositories by subject
area.
Private-sector Cooperation to Improve
Access
Encourage cooperation with the private sector
to improve data access and compatibility.
Issues to consider:
• What funding structures will be in place to ensure that both
organizations involved are benefiting from the partnership?
• Will the partnership require any rights to be transferred to the
private organization?
• How does private-sector cooperation affect
access restrictions and intellectual property
concerns?
Mechanisms for Identification &
Attribution of Data
• Properly citing data encourages the replication of
scientific results, improves research standards, guarantees
persistent reference, and gives proper credit to data
producers.
• Citing data is straightforward. Each citation must include
the basic elements that allow a unique dataset to be
identified over time: title, author, date, version, and
persistent identifier.
• Resources: ICPSR's Data Citations page , IASSIST's Quick
Guide to Data Citation, DataCite.
Data Stewardship Workforce Development
In coordination with other agencies and the private
sector, support training, education, and workforce
development related to scientific data
management, analysis, storage, preservation, and
stewardship. Recent data stewardship workforce
development in the United States has included:
• Digital Preservation Outreach and Education, from the Library of
Congress
• Digital Preservation Management tutorial, from Cornell
University, ICPSR, and MIT
• DigCCurr, from the University of North Carolina
Data Stewardship Workforce
Development cont.
ICPSR hosts data stewardship courses as part of
its Summer Program in Quantitative Methods of
Social Research. These include:
• Curating and Managing Research Data for Re-Use
• Assessing and Mitigating Disclosure Risk: Essentials for
Social Science
• Providing Social Science Data Services: Strategies for
Design and Operation
Long-term Support for Repository
Development
• ICPSR advocates long-term funding for specialized, long-
lived, trustworthy, and sustainable repositories that can
mediate between the needs of scientific disciplines and data
preservation requirements.
• As digital data management becomes an increasingly important
part of scientific research, funding agencies must contribute to
the developing ecosystem of services and technologies that
support access to and preservation of data.
• For more information, including various long-term funding
models, see ICPSR’s 2013 position paper – “The Price of
Keeping Knowledge”
Visit ICPSR Archives/Repositories already Meeting
Public Access Requirements
ICPSR’s Data Management & Curation Site
http://www.icpsr.umich.edu/datamanagement/
http://icpsr.umich.edu/datamanagement/ostp.html
ICPSR’s Guidelines for OSTP Data
Access Plan Page
ICPSR – a 50-Year History of Providing Access to
Research Data
Established in 1962, ICPSR maintains and shares
over 8,600 research datasets and hosts 16 public-
access specialized collections of data funded by
various government agencies and foundations. Our
mission:
ICPSR advances and expands social and behavioral
research, acting as a global leader in data
stewardship and providing rich data resources and
responsive educational opportunities for present
and future generations.
The Concept of Data Curation
• Curation, from the Latin "to care," is the process that ICPSR uses to add
value to data, maximize access, and ensure long-term preservation.
• Data curation is akin to work performed by an art or museum curator.
– Data are organized, described, cleaned, enhanced, and preserved for
public use, much like the work done on paintings or rare books to make
the works accessible to the public now and in the future.
• Through curation, ICPSR provides meaningful and enduring access to
data.
ICPSR’s Data Management & Curation Goals
• Quality - Data at ICSPR are
enhanced with meaningful
information to make it
complete, self-explanatory, and
usable for future researchers
• Access – Sought by over 730
member institutions an indexed by
all the major search engines, ICPSR
data are easily discoverable and
widely accessible to the public.
• Citation - By providing
standardized and well-recognized
data citations, ICPSR ensures that
data producers receive credit for
their archived data
• Preservation – For over 50
years, ICPSR has preserved its data
resources for the long-
term, guarding against
deterioration, accidental loss, and
digital obsolescence
• Confidentiality - Stringent
protections are in place for securing
and distributing sensitive data
• Educational Support –
ICPSR has a long tradition of
supporting training in quantitative
methods, scientific data
management, and resources for
instruction
Copies of these Slides & Use
• Feel free to share it; present
it; cite it!
• Find copies of these slides
on Slideshare.net
Get More information
• Visit ICPSR’s Data Management &
Curation site:
http://www.icpsr.umich.edu/datamanage
ment/index.jsp
• Contact us:
– netmail@icpsr.umich.edu
– (734) 647-2200

Contenu connexe

Tendances

Data as a Library Aquisition
Data as a Library AquisitionData as a Library Aquisition
Data as a Library Aquisitionaaroncollie
 
RDM and DMP intro
RDM and DMP introRDM and DMP intro
RDM and DMP introSarah Jones
 
Data Management Planning for Engineers
Data Management Planning for EngineersData Management Planning for Engineers
Data Management Planning for EngineersSherry Lake
 
Introduction to Data Management Planning
Introduction to Data Management PlanningIntroduction to Data Management Planning
Introduction to Data Management PlanningSarah Jones
 
Data Services presentation for Psychology
Data Services presentation for PsychologyData Services presentation for Psychology
Data Services presentation for PsychologyLynda Kellam
 
Managing and sharing data
Managing and sharing dataManaging and sharing data
Managing and sharing dataSarah Jones
 
EPSRC research data expectations and PURE for datasets
EPSRC research data expectations and PURE for datasetsEPSRC research data expectations and PURE for datasets
EPSRC research data expectations and PURE for datasetsEDINA, University of Edinburgh
 
Data management for TA's
Data management for TA'sData management for TA's
Data management for TA'saaroncollie
 
ICPSR Workshop Template - 2012/13
ICPSR Workshop Template - 2012/13ICPSR Workshop Template - 2012/13
ICPSR Workshop Template - 2012/13ICPSR
 
RDAP 15 EarthCollab: Connecting Scientific Information Sources using the Sema...
RDAP 15 EarthCollab: Connecting Scientific Information Sources using the Sema...RDAP 15 EarthCollab: Connecting Scientific Information Sources using the Sema...
RDAP 15 EarthCollab: Connecting Scientific Information Sources using the Sema...ASIS&T
 
RDAP 15 Local ICPSR Data Curation Workshop Pilot Project
RDAP 15 Local ICPSR Data Curation Workshop Pilot ProjectRDAP 15 Local ICPSR Data Curation Workshop Pilot Project
RDAP 15 Local ICPSR Data Curation Workshop Pilot ProjectASIS&T
 
Data Services/ICPSR presentation for School of Education
Data Services/ICPSR presentation for School of EducationData Services/ICPSR presentation for School of Education
Data Services/ICPSR presentation for School of EducationLynda Kellam
 
DMP health sciences
DMP health sciencesDMP health sciences
DMP health sciencesSarah Jones
 
Practical and Conceptual Considerations of Research Object Preservation
Practical and Conceptual Considerations of Research Object PreservationPractical and Conceptual Considerations of Research Object Preservation
Practical and Conceptual Considerations of Research Object PreservationSEAD
 
RDAP14: Policy Recommendations for Institutions to Serve as Trustworthy Stewa...
RDAP14: Policy Recommendations for Institutions to Serve as Trustworthy Stewa...RDAP14: Policy Recommendations for Institutions to Serve as Trustworthy Stewa...
RDAP14: Policy Recommendations for Institutions to Serve as Trustworthy Stewa...ASIS&T
 
Presentation to the UM Library Emergent Research Series
Presentation to the UM Library Emergent Research SeriesPresentation to the UM Library Emergent Research Series
Presentation to the UM Library Emergent Research SeriesSEAD
 
RDAP14: Learning to Curate Panel
RDAP14: Learning to Curate Panel RDAP14: Learning to Curate Panel
RDAP14: Learning to Curate Panel ASIS&T
 
Why Data Citation Currently Misses the Point
Why Data Citation Currently Misses the PointWhy Data Citation Currently Misses the Point
Why Data Citation Currently Misses the PointMark Parsons
 

Tendances (20)

Data as a Library Aquisition
Data as a Library AquisitionData as a Library Aquisition
Data as a Library Aquisition
 
RDM and DMP intro
RDM and DMP introRDM and DMP intro
RDM and DMP intro
 
Data Management Planning for Engineers
Data Management Planning for EngineersData Management Planning for Engineers
Data Management Planning for Engineers
 
Introduction to Data Management Planning
Introduction to Data Management PlanningIntroduction to Data Management Planning
Introduction to Data Management Planning
 
Data Policy for Open Science
Data Policy for Open ScienceData Policy for Open Science
Data Policy for Open Science
 
Data Services presentation for Psychology
Data Services presentation for PsychologyData Services presentation for Psychology
Data Services presentation for Psychology
 
Managing and sharing data
Managing and sharing dataManaging and sharing data
Managing and sharing data
 
EPSRC research data expectations and PURE for datasets
EPSRC research data expectations and PURE for datasetsEPSRC research data expectations and PURE for datasets
EPSRC research data expectations and PURE for datasets
 
Data management for TA's
Data management for TA'sData management for TA's
Data management for TA's
 
ICPSR Workshop Template - 2012/13
ICPSR Workshop Template - 2012/13ICPSR Workshop Template - 2012/13
ICPSR Workshop Template - 2012/13
 
RDAP 15 EarthCollab: Connecting Scientific Information Sources using the Sema...
RDAP 15 EarthCollab: Connecting Scientific Information Sources using the Sema...RDAP 15 EarthCollab: Connecting Scientific Information Sources using the Sema...
RDAP 15 EarthCollab: Connecting Scientific Information Sources using the Sema...
 
RDAP 15 Local ICPSR Data Curation Workshop Pilot Project
RDAP 15 Local ICPSR Data Curation Workshop Pilot ProjectRDAP 15 Local ICPSR Data Curation Workshop Pilot Project
RDAP 15 Local ICPSR Data Curation Workshop Pilot Project
 
Data Services/ICPSR presentation for School of Education
Data Services/ICPSR presentation for School of EducationData Services/ICPSR presentation for School of Education
Data Services/ICPSR presentation for School of Education
 
What is-rdm
What is-rdmWhat is-rdm
What is-rdm
 
DMP health sciences
DMP health sciencesDMP health sciences
DMP health sciences
 
Practical and Conceptual Considerations of Research Object Preservation
Practical and Conceptual Considerations of Research Object PreservationPractical and Conceptual Considerations of Research Object Preservation
Practical and Conceptual Considerations of Research Object Preservation
 
RDAP14: Policy Recommendations for Institutions to Serve as Trustworthy Stewa...
RDAP14: Policy Recommendations for Institutions to Serve as Trustworthy Stewa...RDAP14: Policy Recommendations for Institutions to Serve as Trustworthy Stewa...
RDAP14: Policy Recommendations for Institutions to Serve as Trustworthy Stewa...
 
Presentation to the UM Library Emergent Research Series
Presentation to the UM Library Emergent Research SeriesPresentation to the UM Library Emergent Research Series
Presentation to the UM Library Emergent Research Series
 
RDAP14: Learning to Curate Panel
RDAP14: Learning to Curate Panel RDAP14: Learning to Curate Panel
RDAP14: Learning to Curate Panel
 
Why Data Citation Currently Misses the Point
Why Data Citation Currently Misses the PointWhy Data Citation Currently Misses the Point
Why Data Citation Currently Misses the Point
 

Similaire à Guidelines for OSTP Data Access Plans

Creating a Data Management Plan for your Grant Application
Creating a Data Management Plan for your Grant ApplicationCreating a Data Management Plan for your Grant Application
Creating a Data Management Plan for your Grant ApplicationHistoric Environment Scotland
 
Creating a Data Management Plan for your Grant Application
Creating a Data Management Plan for your Grant ApplicationCreating a Data Management Plan for your Grant Application
Creating a Data Management Plan for your Grant ApplicationEDINA, University of Edinburgh
 
RDM LIASA webinar
RDM LIASA webinarRDM LIASA webinar
RDM LIASA webinarSarah Jones
 
Winter school in research data science research data management - final
Winter school in research data science research data management - finalWinter school in research data science research data management - final
Winter school in research data science research data management - finalARDC
 
Data Management Planning
Data Management PlanningData Management Planning
Data Management PlanningMarieke Guy
 
Survey of research data management practices up2010digschol2011
Survey of research data management practices up2010digschol2011Survey of research data management practices up2010digschol2011
Survey of research data management practices up2010digschol2011heila1
 
RDM in higher education
RDM in higher educationRDM in higher education
RDM in higher educationSarah Jones
 
Birgit Plietzsch “RDM within research computing support” SALCTG June 2013
Birgit Plietzsch “RDM within research computing support” SALCTG June 2013Birgit Plietzsch “RDM within research computing support” SALCTG June 2013
Birgit Plietzsch “RDM within research computing support” SALCTG June 2013SALCTG
 
Creating a Data Management Plan for your Research
Creating a Data Management Plan for your ResearchCreating a Data Management Plan for your Research
Creating a Data Management Plan for your ResearchRobin Rice
 
Data accessibilityandchallenges
Data accessibilityandchallengesData accessibilityandchallenges
Data accessibilityandchallengesjyotikhadake
 
Research support-challenges
Research support-challengesResearch support-challenges
Research support-challengesSarah Jones
 
Challenges for research support - Sarah Jones, University of Glasgow, Digital...
Challenges for research support - Sarah Jones, University of Glasgow, Digital...Challenges for research support - Sarah Jones, University of Glasgow, Digital...
Challenges for research support - Sarah Jones, University of Glasgow, Digital...Mari Tinnemans
 
Overview of Emerging Requirements for Data Management of Federally Funded Res...
Overview of Emerging Requirements for Data Management of Federally Funded Res...Overview of Emerging Requirements for Data Management of Federally Funded Res...
Overview of Emerging Requirements for Data Management of Federally Funded Res...Richard Huffine
 
Addressing Institutional Research Data Management - University of Edinburgh R...
Addressing Institutional Research Data Management - University of Edinburgh R...Addressing Institutional Research Data Management - University of Edinburgh R...
Addressing Institutional Research Data Management - University of Edinburgh R...EDINA, University of Edinburgh
 

Similaire à Guidelines for OSTP Data Access Plans (20)

Creating a Data Management Plan for your Grant Application
Creating a Data Management Plan for your Grant ApplicationCreating a Data Management Plan for your Grant Application
Creating a Data Management Plan for your Grant Application
 
Creating a Data Management Plan for your Grant Application
Creating a Data Management Plan for your Grant ApplicationCreating a Data Management Plan for your Grant Application
Creating a Data Management Plan for your Grant Application
 
RDM@Edinburgh
RDM@EdinburghRDM@Edinburgh
RDM@Edinburgh
 
RDM@Edinburgh
RDM@EdinburghRDM@Edinburgh
RDM@Edinburgh
 
Research Data Management: Why is it important?
Research Data Management: Why is it  important?Research Data Management: Why is it  important?
Research Data Management: Why is it important?
 
Digital Curation 101 - Taster
Digital Curation 101 - TasterDigital Curation 101 - Taster
Digital Curation 101 - Taster
 
Praetzellis "Data Management Planning and Tools"
Praetzellis "Data Management Planning and Tools"Praetzellis "Data Management Planning and Tools"
Praetzellis "Data Management Planning and Tools"
 
RDM LIASA webinar
RDM LIASA webinarRDM LIASA webinar
RDM LIASA webinar
 
Winter school in research data science research data management - final
Winter school in research data science research data management - finalWinter school in research data science research data management - final
Winter school in research data science research data management - final
 
Data Management Planning
Data Management PlanningData Management Planning
Data Management Planning
 
Survey of research data management practices up2010digschol2011
Survey of research data management practices up2010digschol2011Survey of research data management practices up2010digschol2011
Survey of research data management practices up2010digschol2011
 
RDM in higher education
RDM in higher educationRDM in higher education
RDM in higher education
 
Birgit Plietzsch “RDM within research computing support” SALCTG June 2013
Birgit Plietzsch “RDM within research computing support” SALCTG June 2013Birgit Plietzsch “RDM within research computing support” SALCTG June 2013
Birgit Plietzsch “RDM within research computing support” SALCTG June 2013
 
Creating a Data Management Plan for your Research
Creating a Data Management Plan for your ResearchCreating a Data Management Plan for your Research
Creating a Data Management Plan for your Research
 
Data accessibilityandchallenges
Data accessibilityandchallengesData accessibilityandchallenges
Data accessibilityandchallenges
 
Research support-challenges
Research support-challengesResearch support-challenges
Research support-challenges
 
Challenges for research support - Sarah Jones, University of Glasgow, Digital...
Challenges for research support - Sarah Jones, University of Glasgow, Digital...Challenges for research support - Sarah Jones, University of Glasgow, Digital...
Challenges for research support - Sarah Jones, University of Glasgow, Digital...
 
LSHTM Research Data Management Policy: An Overview
LSHTM Research Data Management Policy: An OverviewLSHTM Research Data Management Policy: An Overview
LSHTM Research Data Management Policy: An Overview
 
Overview of Emerging Requirements for Data Management of Federally Funded Res...
Overview of Emerging Requirements for Data Management of Federally Funded Res...Overview of Emerging Requirements for Data Management of Federally Funded Res...
Overview of Emerging Requirements for Data Management of Federally Funded Res...
 
Addressing Institutional Research Data Management - University of Edinburgh R...
Addressing Institutional Research Data Management - University of Edinburgh R...Addressing Institutional Research Data Management - University of Edinburgh R...
Addressing Institutional Research Data Management - University of Edinburgh R...
 

Plus de ICPSR

Asa integrating data 2 19-2014 with cites
Asa integrating data 2 19-2014 with citesAsa integrating data 2 19-2014 with cites
Asa integrating data 2 19-2014 with citesICPSR
 
Data in the HS Classroom: When, Why, and How?
Data in the HS Classroom: When, Why, and How?Data in the HS Classroom: When, Why, and How?
Data in the HS Classroom: When, Why, and How?ICPSR
 
ICPSR Secure Data Service: Broadening Access. Reducing Risk.
ICPSR Secure Data Service: Broadening Access. Reducing Risk.ICPSR Secure Data Service: Broadening Access. Reducing Risk.
ICPSR Secure Data Service: Broadening Access. Reducing Risk.ICPSR
 
Data in The Classroom: It's Not Just for Nerds Anymore!
Data in The Classroom:  It's Not Just for Nerds Anymore!Data in The Classroom:  It's Not Just for Nerds Anymore!
Data in The Classroom: It's Not Just for Nerds Anymore!ICPSR
 
Quantitative Literacy: Don't be afraid of data (in the classroom)!
Quantitative Literacy:  Don't be afraid of data (in the classroom)!Quantitative Literacy:  Don't be afraid of data (in the classroom)!
Quantitative Literacy: Don't be afraid of data (in the classroom)!ICPSR
 
ICPSR Data Services
ICPSR Data ServicesICPSR Data Services
ICPSR Data ServicesICPSR
 
TeachingWithData.org Outreach Presentation
TeachingWithData.org Outreach Presentation TeachingWithData.org Outreach Presentation
TeachingWithData.org Outreach Presentation ICPSR
 
ICPSR Data Managment
ICPSR Data ManagmentICPSR Data Managment
ICPSR Data ManagmentICPSR
 
ICPSR Data Sharing
ICPSR Data SharingICPSR Data Sharing
ICPSR Data SharingICPSR
 
ICPSR Data Exploration Tools
ICPSR Data Exploration ToolsICPSR Data Exploration Tools
ICPSR Data Exploration ToolsICPSR
 
Spice up your lecture with Inquiry-based Learning
Spice up your lecture with Inquiry-based LearningSpice up your lecture with Inquiry-based Learning
Spice up your lecture with Inquiry-based LearningICPSR
 
Guidance on Data Management Plans
Guidance on Data Management PlansGuidance on Data Management Plans
Guidance on Data Management PlansICPSR
 
TeachingWithData.org ASA Presentation 2010
TeachingWithData.org ASA Presentation 2010TeachingWithData.org ASA Presentation 2010
TeachingWithData.org ASA Presentation 2010ICPSR
 
TeachingWithData.org -- Faculty Presentation
TeachingWithData.org -- Faculty PresentationTeachingWithData.org -- Faculty Presentation
TeachingWithData.org -- Faculty PresentationICPSR
 
Bulletinspring2010final
Bulletinspring2010finalBulletinspring2010final
Bulletinspring2010finalICPSR
 
ICPSR: Resources for Use in Undergraduate Instruction
ICPSR: Resources for Use in Undergraduate InstructionICPSR: Resources for Use in Undergraduate Instruction
ICPSR: Resources for Use in Undergraduate InstructionICPSR
 
Using Quantitative Data in Teaching: ICPSR Resources
Using Quantitative Data in Teaching: ICPSR ResourcesUsing Quantitative Data in Teaching: ICPSR Resources
Using Quantitative Data in Teaching: ICPSR ResourcesICPSR
 
What Is A Virtual Meeting?
What Is A Virtual Meeting?What Is A Virtual Meeting?
What Is A Virtual Meeting?ICPSR
 

Plus de ICPSR (18)

Asa integrating data 2 19-2014 with cites
Asa integrating data 2 19-2014 with citesAsa integrating data 2 19-2014 with cites
Asa integrating data 2 19-2014 with cites
 
Data in the HS Classroom: When, Why, and How?
Data in the HS Classroom: When, Why, and How?Data in the HS Classroom: When, Why, and How?
Data in the HS Classroom: When, Why, and How?
 
ICPSR Secure Data Service: Broadening Access. Reducing Risk.
ICPSR Secure Data Service: Broadening Access. Reducing Risk.ICPSR Secure Data Service: Broadening Access. Reducing Risk.
ICPSR Secure Data Service: Broadening Access. Reducing Risk.
 
Data in The Classroom: It's Not Just for Nerds Anymore!
Data in The Classroom:  It's Not Just for Nerds Anymore!Data in The Classroom:  It's Not Just for Nerds Anymore!
Data in The Classroom: It's Not Just for Nerds Anymore!
 
Quantitative Literacy: Don't be afraid of data (in the classroom)!
Quantitative Literacy:  Don't be afraid of data (in the classroom)!Quantitative Literacy:  Don't be afraid of data (in the classroom)!
Quantitative Literacy: Don't be afraid of data (in the classroom)!
 
ICPSR Data Services
ICPSR Data ServicesICPSR Data Services
ICPSR Data Services
 
TeachingWithData.org Outreach Presentation
TeachingWithData.org Outreach Presentation TeachingWithData.org Outreach Presentation
TeachingWithData.org Outreach Presentation
 
ICPSR Data Managment
ICPSR Data ManagmentICPSR Data Managment
ICPSR Data Managment
 
ICPSR Data Sharing
ICPSR Data SharingICPSR Data Sharing
ICPSR Data Sharing
 
ICPSR Data Exploration Tools
ICPSR Data Exploration ToolsICPSR Data Exploration Tools
ICPSR Data Exploration Tools
 
Spice up your lecture with Inquiry-based Learning
Spice up your lecture with Inquiry-based LearningSpice up your lecture with Inquiry-based Learning
Spice up your lecture with Inquiry-based Learning
 
Guidance on Data Management Plans
Guidance on Data Management PlansGuidance on Data Management Plans
Guidance on Data Management Plans
 
TeachingWithData.org ASA Presentation 2010
TeachingWithData.org ASA Presentation 2010TeachingWithData.org ASA Presentation 2010
TeachingWithData.org ASA Presentation 2010
 
TeachingWithData.org -- Faculty Presentation
TeachingWithData.org -- Faculty PresentationTeachingWithData.org -- Faculty Presentation
TeachingWithData.org -- Faculty Presentation
 
Bulletinspring2010final
Bulletinspring2010finalBulletinspring2010final
Bulletinspring2010final
 
ICPSR: Resources for Use in Undergraduate Instruction
ICPSR: Resources for Use in Undergraduate InstructionICPSR: Resources for Use in Undergraduate Instruction
ICPSR: Resources for Use in Undergraduate Instruction
 
Using Quantitative Data in Teaching: ICPSR Resources
Using Quantitative Data in Teaching: ICPSR ResourcesUsing Quantitative Data in Teaching: ICPSR Resources
Using Quantitative Data in Teaching: ICPSR Resources
 
What Is A Virtual Meeting?
What Is A Virtual Meeting?What Is A Virtual Meeting?
What Is A Virtual Meeting?
 

Dernier

GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTSGRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTSJoshuaGantuangco2
 
EMBODO Lesson Plan Grade 9 Law of Sines.docx
EMBODO Lesson Plan Grade 9 Law of Sines.docxEMBODO Lesson Plan Grade 9 Law of Sines.docx
EMBODO Lesson Plan Grade 9 Law of Sines.docxElton John Embodo
 
Oppenheimer Film Discussion for Philosophy and Film
Oppenheimer Film Discussion for Philosophy and FilmOppenheimer Film Discussion for Philosophy and Film
Oppenheimer Film Discussion for Philosophy and FilmStan Meyer
 
Q4-PPT-Music9_Lesson-1-Romantic-Opera.pptx
Q4-PPT-Music9_Lesson-1-Romantic-Opera.pptxQ4-PPT-Music9_Lesson-1-Romantic-Opera.pptx
Q4-PPT-Music9_Lesson-1-Romantic-Opera.pptxlancelewisportillo
 
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptxMULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptxAnupkumar Sharma
 
Millenials and Fillennials (Ethical Challenge and Responses).pptx
Millenials and Fillennials (Ethical Challenge and Responses).pptxMillenials and Fillennials (Ethical Challenge and Responses).pptx
Millenials and Fillennials (Ethical Challenge and Responses).pptxJanEmmanBrigoli
 
How to do quick user assign in kanban in Odoo 17 ERP
How to do quick user assign in kanban in Odoo 17 ERPHow to do quick user assign in kanban in Odoo 17 ERP
How to do quick user assign in kanban in Odoo 17 ERPCeline George
 
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17Celine George
 
ROLES IN A STAGE PRODUCTION in arts.pptx
ROLES IN A STAGE PRODUCTION in arts.pptxROLES IN A STAGE PRODUCTION in arts.pptx
ROLES IN A STAGE PRODUCTION in arts.pptxVanesaIglesias10
 
ICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdfICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdfVanessa Camilleri
 
Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)
Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)
Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)lakshayb543
 
How to Add Barcode on PDF Report in Odoo 17
How to Add Barcode on PDF Report in Odoo 17How to Add Barcode on PDF Report in Odoo 17
How to Add Barcode on PDF Report in Odoo 17Celine George
 
Virtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdf
Virtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdfVirtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdf
Virtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdfErwinPantujan2
 
The Contemporary World: The Globalization of World Politics
The Contemporary World: The Globalization of World PoliticsThe Contemporary World: The Globalization of World Politics
The Contemporary World: The Globalization of World PoliticsRommel Regala
 
Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...Seán Kennedy
 
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...Nguyen Thanh Tu Collection
 
Activity 2-unit 2-update 2024. English translation
Activity 2-unit 2-update 2024. English translationActivity 2-unit 2-update 2024. English translation
Activity 2-unit 2-update 2024. English translationRosabel UA
 

Dernier (20)

GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTSGRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
 
EMBODO Lesson Plan Grade 9 Law of Sines.docx
EMBODO Lesson Plan Grade 9 Law of Sines.docxEMBODO Lesson Plan Grade 9 Law of Sines.docx
EMBODO Lesson Plan Grade 9 Law of Sines.docx
 
Oppenheimer Film Discussion for Philosophy and Film
Oppenheimer Film Discussion for Philosophy and FilmOppenheimer Film Discussion for Philosophy and Film
Oppenheimer Film Discussion for Philosophy and Film
 
Q4-PPT-Music9_Lesson-1-Romantic-Opera.pptx
Q4-PPT-Music9_Lesson-1-Romantic-Opera.pptxQ4-PPT-Music9_Lesson-1-Romantic-Opera.pptx
Q4-PPT-Music9_Lesson-1-Romantic-Opera.pptx
 
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptxMULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
 
Paradigm shift in nursing research by RS MEHTA
Paradigm shift in nursing research by RS MEHTAParadigm shift in nursing research by RS MEHTA
Paradigm shift in nursing research by RS MEHTA
 
Millenials and Fillennials (Ethical Challenge and Responses).pptx
Millenials and Fillennials (Ethical Challenge and Responses).pptxMillenials and Fillennials (Ethical Challenge and Responses).pptx
Millenials and Fillennials (Ethical Challenge and Responses).pptx
 
How to do quick user assign in kanban in Odoo 17 ERP
How to do quick user assign in kanban in Odoo 17 ERPHow to do quick user assign in kanban in Odoo 17 ERP
How to do quick user assign in kanban in Odoo 17 ERP
 
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
 
ROLES IN A STAGE PRODUCTION in arts.pptx
ROLES IN A STAGE PRODUCTION in arts.pptxROLES IN A STAGE PRODUCTION in arts.pptx
ROLES IN A STAGE PRODUCTION in arts.pptx
 
ICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdfICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdf
 
Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)
Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)
Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)
 
How to Add Barcode on PDF Report in Odoo 17
How to Add Barcode on PDF Report in Odoo 17How to Add Barcode on PDF Report in Odoo 17
How to Add Barcode on PDF Report in Odoo 17
 
Virtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdf
Virtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdfVirtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdf
Virtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdf
 
YOUVE_GOT_EMAIL_PRELIMS_EL_DORADO_2024.pptx
YOUVE_GOT_EMAIL_PRELIMS_EL_DORADO_2024.pptxYOUVE_GOT_EMAIL_PRELIMS_EL_DORADO_2024.pptx
YOUVE_GOT_EMAIL_PRELIMS_EL_DORADO_2024.pptx
 
The Contemporary World: The Globalization of World Politics
The Contemporary World: The Globalization of World PoliticsThe Contemporary World: The Globalization of World Politics
The Contemporary World: The Globalization of World Politics
 
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptxYOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
 
Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...
 
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
 
Activity 2-unit 2-update 2024. English translation
Activity 2-unit 2-update 2024. English translationActivity 2-unit 2-update 2024. English translation
Activity 2-unit 2-update 2024. English translation
 

Guidelines for OSTP Data Access Plans

  • 1. Guidelines and Resources for OSTP Data Access Plans ICPSR September 2013 www.icpsr.umich.edu/datamanagement
  • 2. The OSTP Memo Guidelines for Response • Released February 2013, this memo directs funding agencies with an annual R&D budget over $100 million to develop a public access plan for disseminating the results of their research • ICPSR stresses that standards and guidelines for many of the requirements currently exist • The slides to follow provide an overview of the access plan elements including guidelines and resources on how to respond to meet digital data requirements in the memo
  • 3. The OSTP Memo – A Review • Released February 22, 2013 • A concern for investment: “Policies that mobilize these publications and data for re-use through preservation and broader public access also maximize the impact and accountability of the Federal research investment.” • Federal agencies with over $100 M annually in R&D expenditures to develop plans to support increased public access to the results of research funded by the Federal Government • Plans to contain eight points
  • 4. The Eight Points of the Plan 1. Strategy for leveraging existing archives 2. Strategy to improve the public’s ability to locate and access digital data 3. Approach to optimize search, archival, and dissemination features that encourage innovation in accessibility & interoperability and ensure long-term stewardship 4. A plan to notify awardees & researchers of their obligations 5. Strategy for measuring and enforcing compliance with the plan 6. Identification of resources within the existing agency budget to implement plan 7. Timeline for implementation 8. Identification of special circumstances that prevent the agency from meeting memo objectives
  • 5. Data Portion of Memo - 13 Elements • The portion of the memo describing objectives for public access to data stresses 13 elements for a public access plan • The elements are also summarized online within ICPSR’s Web site: http://icpsr.umich.edu/content/datamanagement/ostp.html
  • 6. Maximize Access "Maximize access, by the general public and without charge, to digitally formatted scientific data created with Federal funds“ • Increasing access to research data prevents the duplication of effort, provides accountability and verification of research results, and increases opportunities for innovation and collaboration. • Finding and accessing data in repositories requires descriptive metadata ("data about data") in standard, machine-actionable form. Metadata help search engines find data, and help researchers understand the context of data collections. • Standards already exist: see Data Documentation Initiative – http://www.ddialliance.org/
  • 7. Maximize Access cont. • Access also involves knowing how to interpret the data. Incomplete data limit reuse. Obsolete data formats can be unreadable. – Repositories 'curate' or enhance data to make it complete, self- explanatory, and usable for future researchers. This includes adding descriptive labels, correcting coding errors, gathering documentation, and standardizing the final versions of files. This is called “data curation.” – Like museums that curate art or artifacts for study and understanding now and in the future, data archives curate data with the same goals. • Data curation is crucial to maximizing access. Resources for curating data: – ICPSR's Guide to Social Science Data Preparation and Archiving – UK Data Archive's Managing and Sharing Data guide.
  • 8. Protect Confidentiality and Privacy • It is critically important to protect the identities of research subjects. • Disclosure risk is a term that is often used for the possibility that a data record from a study could be linked to a specific person. • Concerns about disclosure risk have grown as more datasets have become available online, and it has become easier to link research datasets with publicly available external databases.
  • 9. Protect Confidentiality and Privacy cont. Protecting confidentiality of research subjects is not a viable argument for not sharing data. Infrastructure, including virtual and physical data enclaves, already exists: • Restricted-Use Data are made available for research purposes for use by investigators who agree to stringent conditions for the use of the data and its physical safekeeping. • Enclave Data are those datasets which present especially acute disclosure risks. They can be accessed only on-site in ICPSR's physical data enclave in Ann Arbor. Investigators must be approved. Their notes and analytic output are reviewed by ICPSR staff.
  • 10. Preserve Intellectual Property Rights and Commercial Interests Original research may be both commercially valuable and proprietary. There are several approaches to managing these interests, including: – Tailor copyright and patent licenses, such as through Creative Commons licenses – Establish an embargo period or delayed dissemination on distribution.
  • 11. Balance Demands of Long-term Preservation and Access • Preserving digital data requires much more than storing files on a server, desktop, or in the cloud! • Digital preservation is the active and ongoing management of digital content to lengthen the lifespan and mitigate against loss, including physical deterioration, format obsolescence, and hardware and software failure.
  • 12. Balance Demands of Long-term Preservation and Access cont. • Not all data are worth preserving indefinitely; less valuable or easily producible data may be preserved for shorter periods. • Establish selection and appraisal guidelines that make it clear what to save or discard. – Selection criteria consider factors like availability, confidentiality, copyright, quality, f ile format, and financial commitment.
  • 13. Use of Data Management Plans • Data management plans describe how researchers will provide for long-term preservation of, and access to, scientific data in digital formats. • Data management plans provide opportunities for researchers to manage and curate their data more actively from project inception to completion. • See ICPSR's resource: Guidelines for Effective Data Management Plans
  • 14. Include Cost of Data Management in Funding Proposals • Data management services carry real costs, ranging from personnel to storage to software. • Maintenance costs are routinely built into physical infrastructure development, so too should data management costs be built into data development. • Long-term access to data requires durable institutions that plan on a scale of decades and even generations. • Cost resources: – DataONE's Provide budget information for your data management plan – UK Data Archive's Costing Tool: Data Management Planning.
  • 15. Evaluate Data Management Plans & Ensure Compliance • Plans help researchers prepare for working with and preserving data, repositories get ready to accession and provide access, and agencies to understand the community needs for archiving and access. Evaluation helps refine plans so they are realistic and attainable. • If data management plans are to be a standard component of funding applications, funding recipients should be held accountable for diversions from the originally stated plans.
  • 16. Promote Public Deposit of Data • Public deposit of data helps to ensure the long-term accessibility and preservation of the data. • It removes the burden of ongoing maintenance and care (and user support) from the researcher and provides a stable system to which data can be entrusted. • Many sustainable online repositories are already available to host and archive research data. These may include discipline- specific repositories, archives administered by funding agencies, or institutional repositories. • Databib, a searchable directory of over 500 research data repositories, can help locate relevant repositories by subject area.
  • 17. Private-sector Cooperation to Improve Access Encourage cooperation with the private sector to improve data access and compatibility. Issues to consider: • What funding structures will be in place to ensure that both organizations involved are benefiting from the partnership? • Will the partnership require any rights to be transferred to the private organization? • How does private-sector cooperation affect access restrictions and intellectual property concerns?
  • 18. Mechanisms for Identification & Attribution of Data • Properly citing data encourages the replication of scientific results, improves research standards, guarantees persistent reference, and gives proper credit to data producers. • Citing data is straightforward. Each citation must include the basic elements that allow a unique dataset to be identified over time: title, author, date, version, and persistent identifier. • Resources: ICPSR's Data Citations page , IASSIST's Quick Guide to Data Citation, DataCite.
  • 19. Data Stewardship Workforce Development In coordination with other agencies and the private sector, support training, education, and workforce development related to scientific data management, analysis, storage, preservation, and stewardship. Recent data stewardship workforce development in the United States has included: • Digital Preservation Outreach and Education, from the Library of Congress • Digital Preservation Management tutorial, from Cornell University, ICPSR, and MIT • DigCCurr, from the University of North Carolina
  • 20. Data Stewardship Workforce Development cont. ICPSR hosts data stewardship courses as part of its Summer Program in Quantitative Methods of Social Research. These include: • Curating and Managing Research Data for Re-Use • Assessing and Mitigating Disclosure Risk: Essentials for Social Science • Providing Social Science Data Services: Strategies for Design and Operation
  • 21. Long-term Support for Repository Development • ICPSR advocates long-term funding for specialized, long- lived, trustworthy, and sustainable repositories that can mediate between the needs of scientific disciplines and data preservation requirements. • As digital data management becomes an increasingly important part of scientific research, funding agencies must contribute to the developing ecosystem of services and technologies that support access to and preservation of data. • For more information, including various long-term funding models, see ICPSR’s 2013 position paper – “The Price of Keeping Knowledge”
  • 22. Visit ICPSR Archives/Repositories already Meeting Public Access Requirements
  • 23. ICPSR’s Data Management & Curation Site http://www.icpsr.umich.edu/datamanagement/
  • 25. ICPSR – a 50-Year History of Providing Access to Research Data Established in 1962, ICPSR maintains and shares over 8,600 research datasets and hosts 16 public- access specialized collections of data funded by various government agencies and foundations. Our mission: ICPSR advances and expands social and behavioral research, acting as a global leader in data stewardship and providing rich data resources and responsive educational opportunities for present and future generations.
  • 26. The Concept of Data Curation • Curation, from the Latin "to care," is the process that ICPSR uses to add value to data, maximize access, and ensure long-term preservation. • Data curation is akin to work performed by an art or museum curator. – Data are organized, described, cleaned, enhanced, and preserved for public use, much like the work done on paintings or rare books to make the works accessible to the public now and in the future. • Through curation, ICPSR provides meaningful and enduring access to data.
  • 27. ICPSR’s Data Management & Curation Goals • Quality - Data at ICSPR are enhanced with meaningful information to make it complete, self-explanatory, and usable for future researchers • Access – Sought by over 730 member institutions an indexed by all the major search engines, ICPSR data are easily discoverable and widely accessible to the public. • Citation - By providing standardized and well-recognized data citations, ICPSR ensures that data producers receive credit for their archived data • Preservation – For over 50 years, ICPSR has preserved its data resources for the long- term, guarding against deterioration, accidental loss, and digital obsolescence • Confidentiality - Stringent protections are in place for securing and distributing sensitive data • Educational Support – ICPSR has a long tradition of supporting training in quantitative methods, scientific data management, and resources for instruction
  • 28. Copies of these Slides & Use • Feel free to share it; present it; cite it! • Find copies of these slides on Slideshare.net
  • 29. Get More information • Visit ICPSR’s Data Management & Curation site: http://www.icpsr.umich.edu/datamanage ment/index.jsp • Contact us: – netmail@icpsr.umich.edu – (734) 647-2200

Notes de l'éditeur

  1. Current archives/collections/repositories already meeting public access requirements regarding dataNACDA – NACJD – SAMHDA: examples of long term sustainabilityNAHDAP – SAMHDA – DSDR: examples of sharing of confidential dataNACJD – example of depository/researcher compliance (holding 10% of funding to PI)LGBT – MET: unique infrastructure and disseminationResearch Connections: reports and data dissemination; audiences including policymakers