data management plans: tips, tricks and tools

Data Management Plans

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Carly Strasser & Perry Willett

University of California Curation Center

California Digital Library11 January 2012 UC3 Webinar Series California Digital Library

Roadmap

4. DMPTool

2. Data Management Plans 101

3. Toolbox

1. Welcome & Logistics

Logistics for Webinar

11 January 2012 UC3 Webinar Series California Digital Library

• Participants on mute• Chat is being monitored• ~15 minutes for Q&A after webinar• Slides and web/voice recordings will be posted after

presentation• Phone: 866-740-1260, access code 6408974#• Schedule of webinars available at

www.cdlib.org/uc3/uc3webinars.html

Who we are


Partnership between CDL | 10 UC campuses | Peer institutions

Provide solutions, services, resources for digital assets

Pool & distribute diverse experience, expertise, & resources

Who we are


Who you are


Researcher Librarian

Grad student

???

Administrator

From Flickr by maybeemily

Who you are


http://tinyurl.com/DMPToolsurvey

http://www.surveymonkey.com/s/LSTV8QL

Help us improve the DMPToolBy taking this survey:

Contributor

Roadmap

4. DMPTool


3. Toolbox


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Where data end up

Data

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Who cares?

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Where data end up

Data

Metadata


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From Flickr by csessums


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Data

Metadata


www

Where data end up

From Flickr by torkildr


www

Trends in Data Archiving

Journal publishersJoint Data Archiving Agreement



Data PapersEcological Archives, Beyond the PDF



Data Papers etc.Ecological Archives, Beyond the PDF

FundersData management requirements

A document that describes what you will do with your data during and after you complete your

research

What is a data management plan?

Robert Stadler installation from Flickr by Dom Dada

Saves timeIncreases efficiencyEasier to use data Others can understand & use dataCredit for data productsFunders require it

Why should I prepare a DMP?

DMP supplement may include:1. the types of data, samples, physical collections, software,

curriculum materials, and other materials to be produced in the course of the project

2. the standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies)

3. policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements

4. policies and provisions for re-use, re-distribution, and the production of derivatives

5. plans for archiving data, samples, and other research products, and for preservation of access to them

NSF DMP Requirements

From Grant Proposal Guidelines:

NSF’s Vision*

DMPs and their evaluation will grow & change over time (similar to broader impacts)

Peer review will determine next steps

Community-driven guidelines – Disciplines have different definitions of acceptable

data sharing– Flexibility at the directorate and division levels– Tailor implementation of DMP requirement

Evaluation will vary with directorate, division, & program officer

*UnofficiallyHelp from Jennifer Schopf, NSF

DMPs are a good first step towards improving data stewardship

– starting discussion– scientists learning about data management

Additional expertise on panels to effectively evaluate DMPs (?)

Working group will assess outcomes

NSF’s Vision*

*Unofficially

DMP supplement may include:1. the types of data, samples, physical collections, software,

curriculum materials, and other materials to be produced in the course of the project

2. the standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies)

3. policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements

4. policies and provisions for re-use, re-distribution, and the production of derivatives

5. plans for archiving data, samples, and other research products, and for preservation of access to them

NSF DMP Requirements

From Grant Proposal Guidelines:

• Types of data produced

• Relationship to existing data

• How/when/where will the data be captured or created?

• How will the data be processed?

• Quality assurance & quality control measures

• Security: version control, backing up

• Who will be responsible for data management during/after project?

1. Types of data & other information

biology.kenyon.edu

C. Strasser

From Flickr by Lazurite

Wired.com

2. Data & metadata standardsWhat is metadata?

Data reporting• WHO created the data?

• WHAT is the content of the data set?

• WHEN was it created?

• WHERE was it collected?

• HOW was it developed?

• WHY was it developed?

From Flickr by proteinbiochemist

Wired.com

• What metadata are needed to make the data meaningful?

• How will you create or capture these metadata?

• Why have you chosen particular standards and approaches for metadata?

2. Data & metadata standards

• Are you under any obligation to share data?

• How, when, & where will you make the data available?

• What is the process for gaining access to the data?

• Who owns the copyright and/or intellectual property?

• Will you retain rights before opening data to wider use? How long?

• Are permission restrictions necessary?• Embargo periods for political/commercial/patent

reasons? • Ethical and privacy issues?• Who are the foreseeable data users?• How should your data be cited?

3. Policies for access & sharing4. Policies for re-use & re-

distribution

• What data will be preserved for the long term? For how long?

• Where will data be preserved?

• What data transformations need to occur before preservation?

5. Plans for archiving & preservation

From Flickr by theManWhoSurfedTooMuch

• What metadata will be submitted alongside the datasets?

• Who will be responsible for preparing data for preservation? Who will be the main contact person for the archived data?

Don’t forget: Budget

• Costs of data preparation & documentation

Hardware, softwarePersonnelArchive fees

• How costs will be paid Request funding!

dorrvs.com

Roadmap

4. DMPTool


3. Toolbox


Toolbox:

• Data Education Tutorials

• Database of best practices & software tools

• Links to DMPTool• Primer on data

management

www.dataone.org

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Toolbox:DCXL website dcxl.cdlib.org

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• Data Education Tutorials• Primer on data

management• Other resources

Data Management 101

DCXL blog: dcxl.cdlib.org

Toolbox:Fro

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• Data Education Tutorials• Primer on data

management• Other resources

dcxl.cdlib.orgwww.carlystrasser.net/Resources

Institutional Services

Precise identification of a datasetCredit to data producers and data publishersLink traditional literature to dataResearch metrics for datasets

UC Community: www.cdlib.org/services/uc3

Toolbox:

Deposit | Share | Preserve data

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Institutional Services

Toolbox:

Check with your institution’s

librarians

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DMPTool

Toolbox:dmp.cdlib.org

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Roadmap

4. DMPTool


3. Toolbox


DMPTool for Data Management Plans

• Helps researchers meet requirements of NSF and other U.S. funding agencies.

• Guides researchers through the process of creating a data management plan.

• Is available to everyone at no cost.• Provides additional help for researchers at

DMPTool partner institutions

http://dmp.cdlib.org Jan 11, 2012

http://dmp.cdlib.org/

Goals of the DMPTool, I

• To provide researchers a simple way to create a Data Management Plan by giving them information from the funding agency:– Questions asked by the agency– Any additional explanation or context

provided by the agency– Links to the agency website for policies,

help, guidance



Goals of the DMPTool, II

• To provide researchers with additional information from their local institution:– Resources and services to help them

manage data– Help text for specific questions– Suggested answers to questions that they

can simply cut-and-paste– News and events related to data

management on their campus



DMPTool project

• Partners: CDL, DataONE, Smithsonian, UCLA, UCSD, UIUC, UVa, Digital Curation Centre (UK)– Great team!

• Started work in January 2011• Developed requirements, divided work

among partners, self-funded• Usability testing at Ecological Society of

America conference and Univ of Virginia



Future Development

• Partners’ meeting in late January to discuss– User survey results– Priorities for additional development– Governance, development, funding

models

• Additional US funding agencies (NIH, others) coming soon



How you can participate

• User survey• Talk to your librarian or data center

staff about:– Shibboleth login (“single sign-on”)– Add links to local resources, help text,

suggested answers, contact information– Blog for local news and events



Project participants• CDL/UC3:

– Trisha Cruse– Perry Willett– Marisa Strong– Tracy Seneca – Scott Fisher– Stephen Abrams– Mark Reyes– Margaret Low

• DataONE:– Amber Budden

• Smithsonian Institution:– Günter Waibel

• UCLA:– Todd Grappone– Gary Thompson– Darrow Cole

• UCSD:– Brad Westbrook

• Univ of Illinois:– Michael Grady– Howard Ding– Sarah Shreeves

• Univ of Virginia:– Andrew Sallans– Sherry Lake– Carla Lee

• Digital Curation Centre:– Martin Donnelly



Email us! [email protected]


http://tinyurl.com/DMPToolsurvey

http://www.surveymonkey.com/s/LSTV8QL

Help us improve the DMPToolBy taking this survey:

UC Community: www.cdlib.org/services/uc3