Data Management Plans: Tips, Tricks and Tools
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Data Management Plans: Tips, Tricks and Tools

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  • Data are lost
  • Data are lost
  • IDeally
  • less time on DM, more time on researchOthers = collaborators and those not assciated with projectfunder requirements met
  • NSB Expert Panel in Data Policies meeting : check thishttp://www.casc.org/meetings/11mar/
  • Types: experimental, observational, raw or derived, physical collections, models, simulations, curriculum materials, software etc.
  • http://dorrys.com/
  • say way UC3 is
  • say way UC3 is
  • say way UC3 is

Data Management Plans: Tips, Tricks and Tools Data Management Plans: Tips, Tricks and Tools Presentation Transcript

  • Data Management Plans Tips TricksFrom Flickr by dipster1 Tools Carly Strasser & Perry Willett University of California Curation Center California Digital Library 11 January 2012  Webinar Series California Digital Library UC3
  • Roadmap 4. DMPTool 3. Toolbox 2. Data Management Plans 1011. Welcome & Logistics
  • Roadmap 4. DMPTool 3. Toolbox 2. Data Management Plans 1011. Welcome & Logistics
  • Logistics for Webinar• 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 11 January 2012  Webinar Series California Digital Library UC3
  • Who we arePartnership between CDL | 10 UC campuses | Peer institutionsProvide solutions, services, resources for digital assetsPool & distribute diverse experience, expertise, & resources 11 January 2012  Webinar Series California Digital Library UC3
  • Who we are 11 January 2012  Webinar Series California Digital Library UC3
  • Who you are 11 January 2012  Webinar Series California Digital Library UC3
  • Who you areHelp us improve the DMPToolBy taking this survey: http://tinyurl.com/DMPToolsurvey http://www.surveymonkey.com/s/LSTV8QL 11 January 2012  Webinar Series California Digital Library UC3
  • Who you areHelp us improve the DMPToolBy taking this survey: http://tinyurl.com/DMPToolsurvey http://www.surveymonkey.com/s/LSTV8QL 11 January 2012  Webinar Series California Digital Library UC3
  • Roadmap 4. DMPTool 3. Toolbox 2. Data Management Plans 1011. Welcome & Logistics
  • From Flickr by DW0825 From Flickr by Flickmor From Flickr by deltaMike Digital data www.woodrow.org C. Strasser Courtesey of WHOI From Flickr by US Army Environmental Command
  • Where data end up From Flickr by diylibrarian www blog.order2disorder.com From Flickr by csessums DataMetadata From Flickr by csessums Recreated from Klump et al. 2006
  • Who cares? www.rba.gov.au From Flickr by AJC1 From Flickr by Redden-McAllister
  • Where data end up From Flickr by diylibrarian www From Flickr by csessums blog.order2disorder.com DataMetadata From Flickr by csessums Recreated from Klump et al. 2006
  • Where data end up From Flickr by diylibrarian www Data wwwMetadata From Flickr by torkildr Recreated from Klump et al. 2006
  • Trends in Data ArchivingJournal publishersJoint Data Archiving Agreement
  • Trends in Data ArchivingJournal publishersJoint Data Archiving AgreementData PapersEcological Archives, Beyond the PDF
  • Trends in Data ArchivingJournal publishersJoint Data Archiving AgreementData PapersEcological Archives, Beyond the PDF
  • Trends in Data ArchivingJournal publishersJoint Data Archiving AgreementData Papers etc.Ecological Archives, Beyond the PDFFundersData management requirements
  • What is a data management plan?A document that describes what you will do with your data during and after you complete your research Robert Stadler installation from Flickr by Dom Dada
  • Why should I prepare a DMP?Saves timeIncreases efficiencyEasier to use dataOthers can understand & use dataCredit for data productsFunders require it
  • NSF DMP RequirementsFrom Grant Proposal Guidelines: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’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*Unofficially Help from Jennifer Schopf, NSF
  • NSF’s Vision* 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*Unofficially
  • NSF DMP RequirementsFrom Grant Proposal Guidelines: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
  • 1. Types of data & other information• Types of data produced• Relationship to existing data• How/when/where will the data be captured or created? C. Strasser• How will the data be processed?• Quality assurance & quality control measures• Security: version control, backing up biology.kenyon.edu• Who will be responsible for data management during/after project? From Flickr by Lazurite
  • 2. Data & metadata standards What is metadata?Data reporting • WHO created the data? Wired.com • 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
  • 2. Data & metadata standards• What metadata are needed to make the data meaningful?• How will you create or capture these metadata? Wired.com• Why have you chosen particular standards and approaches for metadata?
  • 3. Policies for access & sharing 4. Policies for re-use & re-distribution• 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?
  • 5. Plans for archiving & preservation• 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? will be submitted What metadata alongside the datasets?• Who will be responsible for preparing data for preservation? Who will be the main contact person for the archived data? From Flickr by theManWhoSurfedTooMuch
  • Don’t forget: Budget• Costs of data preparation & documentation Hardware, software Personnel Archive fees• How costs will be paid Request funding! dorrvs.com
  • Roadmap 4. DMPTool 3. Toolbox 2. Data Management Plans 1011. Welcome & Logistics
  • Toolbox:From Flickr by dipster1 www.dataone.org • Data Education Tutorials • Database of best practices & software tools • Links to DMPTool • Primer on data management From Flickr by Robert Hruzek
  • Toolbox: 101 Data ManagementFrom Flickr by dipster1 DCXL website dcxl.cdlib.org • Data Education Tutorials • Primer on data management • Other resources
  • Toolbox:From Flickr by dipster1 DCXL blog: dcxl.cdlib.org • Data Education Tutorials • Primer on data management • Other resources dcxl.cdlib.org www.carlystrasser.net/Resources
  • Toolbox:From Flickr by dipster1 Institutional Services UC Community: www.cdlib.org/services/uc3 Deposit | Share | Preserve data Precise identification of a dataset Credit to data producers and data publishers Link traditional literature to data Research metrics for datasets
  • Toolbox:From Flickr by dipster1 Institutional Services Check with your institution’s librarians
  • Toolbox:From Flickr by dipster1 DMPTool dmp.cdlib.org
  • Roadmap 4. DMPTool 3. Toolbox 2. Data Management Plans 1011. Welcome & Logistics
  • 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
  • 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 http://dmp.cdlib.org Jan 11, 2012
  • 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 http://dmp.cdlib.org Jan 11, 2012
  • 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 http://dmp.cdlib.org Jan 11, 2012
  • 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 http://dmp.cdlib.org Jan 11, 2012
  • 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 http://dmp.cdlib.org Jan 11, 2012
  • Project participants• CDL/UC3: • Smithsonian • Univ of Illinois: – Trisha Cruse Institution: – Michael Grady – Perry Willett – Günter Waibel – Howard Ding – Marisa Strong – Sarah Shreeves – Tracy Seneca • UCLA: – Scott Fisher – Todd Grappone • Univ of Virginia: – Stephen Abrams – Gary Thompson – Andrew Sallans – Mark Reyes – Darrow Cole – Sherry Lake – Margaret Low • UCSD: – Carla Lee• DataONE: – Brad Westbrook • Digital Curation – Amber Budden Centre: – Martin Donnelly http://dmp.cdlib.org Jan 11, 2012
  • Email us! uc3@ucop.eduUC Community: www.cdlib.org/services/uc3Help us improve the DMPToolBy taking this survey:http://tinyurl.com/DMPToolsurveyhttp://www.surveymonkey.com/s/LSTV8QL 11 January 2012  Webinar Series California Digital Library UC3