Data Management Planning for Engineers


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DMP Workshop for UVa Engineers

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  • If have journal article, have record of what you did stored in journals,..But the data underlying the results are really important,funders careColleagues – potential collaboratorsInstitutions (not shown here)Tenure committees more in the future.You: need to care you might need to go back to it in a few years… need good description.Future scientists – potentially use your data to discover important things. Need to be thinking about the future. (providing data for them)Slide from Carly Strasser
  • In addition to addressing the issue of public access to scientific publications, the memorandum requires that agencies start to address the need to improve upon the management and sharing of scientific data produced with Federal funding. Strengthening these policies will promote entrepreneurship and jobs growth in addition to driving scientific progress. Also requires researchers to better account for and manage dataDATA: OMB circular A-110:“data” = digital recorded factual material commonly accepted in the scientific community as necessary to validate research findingsincluding data sets used to support scholarly publications, but does not include laboratory notebooks, preliminary analyses, drafts of scientific papers, plans for future research, peer review reports, communications with colleagues, or physical objects, such as laboratory specimens
  • Read calls for proposals carefully and ask program director about specific data management requirements. Build time into your proposal development to formulate a data management plan!Private & public – in the US, UK and other countriesOther agencies require sharing, but do not explicitly require a DMP as part of a proposal – NASA, NEH access & preservationNEH Sustainability of project deliverables and datasets – long term preservationDissemination – sharingNew NSF as of Jan. 2013 – Bio Sketch can include products of research
  • The rest of this talk will focus on the Data Management Plan requirements for the NSFHas been in the Grant Policy Manual since 2002.Even though this “sharing” requirement was in the Admin Guide, there had been little if any enforcement. There was only a “check box” in the Fast Lane system.
  • Types: experimental, observational, raw or derived, physical collections, models, simulations, curriculum materials, software etc.How will data be collected?Are there tools or software needed to create/process/visualize the data?SciDaC Tip: Describe in general any descriptive or analytical statistics that will run on the data. ORCould include data generated by computer, data collected from sensors or instruments, images, audio files, video files, reports, surveys, patient records, and or other.Qualityassurance & quality control measuresSecurity: version control, backing upWho will be responsible for data management during/after project?
  • Data documentation (metadata) explains:How data was createdWhat the data meanWhat the content & structure isWhat manipulations have taken placeIt ensures data understanding in the long-termData documentation includes information on:The ProjectData Collection MethodsStructure of the data filesData sources usedAt the data-level, information on:Labels and descriptions for variables & recordsCodes and classificationsDerived data algorithmsWhat 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?
  • Embargo period:Does the original data collector/creator/principal investigator retain the right to use the data before opening it up to wider use?Are you under any obligationto share data? What is the process for gaining access to the data? How should your data be cited?Question we have been asking…. Who owns the data you collect during your research grant?See SciDaC guidelines….. Data Rights and Responsibilities GuidanceOn our web pageCover copyright, licensing if required.Who owns the copyrightand/or intellectual property?Will youretain rights before opening data to wider use? How long?Embargoperiodsfor political/commercial/patent reasons? Ethicaland privacy issues?If you are planning on restricting access, use or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions. Who are the foreseeable data users?
  • UVA policy states that “data will be preserved for a minimum of five years upon completion of the project” – explain if you’ll be preserving the data longer than five yearsPolicy: Laboratory Notebook and Recordkeeping to archive your data:The University of Virginia is developing an institutional repository (Libra), which will serve as an ideal long-term storage facility for digital research data. Deposit in discipline specific repositoryDeposit in Institutional RepositoryMake accessible on online project web page Make accessible on institutional web siteInformally on a peer-to-peer basisSubmitting to a journalWhat datatransformationsneed to occur before preservation?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?
  • With differing guidelines, which one should you use? Guidelines should be followed in this order:First, follow the requirements laid out in the specific solicitation, if any. These can generally be found in a section entitled "Proposal Preparation Instructions." Contact the program officer with any questions. Second, follow the guidelines published by the appropriate NSF directorate and/or division. Not all directorates and divisions have published data management guidelines; check the NSF's page on Dissemination and Sharing of Research Results for updates (1st link in handout) Third, follow the more general guidelines in the Grant Proposal Guide.
  • The DMPTool was launched in October 2011.Online Data Management Plan creation toolHelps researchers meet requirements of NSF and other U.S. funding agenciesStep-by-step wizard for generating a DMP Open to anyone, even those not affiliated with an institution. Links to institutional resources Directorate information & updates
  • Helps researchers meet requirements of NSF and other US Funding agencies.Guides researchers thru the process of creating a DMP
  • Tool is for multi-institutionsIt is available to everyone, even those not affiliated with an institution.Provides additional help for researchers @UVa and Virginia Tech.
  • Data Management Planning for Engineers

    1. 1. Hands-On Data Management Planning for Engineering Bill Corey Data Management Consultant University of Virginia Library Sherry Lake Data Management Consultant University of Virginia Library Data Life Cycle Re-Purpose Re-Use Deposit Data Collection Data Analysis Data Sharing Proposal Planning Writing Data Discovery End of Project Data Archive Project Start Up
    2. 2. Goals for the workshop • Learn about data management planning • Learn about available resources • Develop rough draft of a data management plan for a grant • Gain peer and expert feedback
    3. 3. (Good) Data Management… …helps research to be: Replicated and verified Preserved for future use Linked with other research products Shared and reused …helps researchers: Meet funding requirements Increase visibility of research Save time and effort (avoid data loss) Deal with an ever-increasing amount of data unlocking-value-clinical-data-many-times-requires-enter
    4. 4. Who Cares? From Flickr by Redden-McAllister From Flickr by AJC1
    5. 5. Recent News • Memo released February 22, 2013 • Direct results of federally funded scientific research are made available… • Federal research agencies funding more than $100M/year must develop plan to make the results (papers and data) of federally funded research available to the public within one year of publication
    6. 6. Require a Data Management Plan (DMP) Require Sharing of Results – per a Data Policy • National Science Foundation • National Institutes of Health • National Oceanographic and Atmospheric Research (NOAA) • Institute of Museum and Library Services (IMLS) • National Endowment of Humanities – office of digital humanities (NEH) • NASA • NEH – Preservation & Access Who’s Requiring Data Management? This list is not inclusive.
    7. 7. Example: National Science Foundation • Data Sharing Policy: Awards & Administration Guide Chapter IV.D.4 • Data Management Plan requirement: Grant Proposal Guide Chapter II.C.2.j • Additional requirements from individual Directorates and Divisions (e.g., BIO, CISE, EHR, GEO, MPS, SBE): Dissemination and Sharing of Results
    8. 8. NSF: Dissemination & Sharing of Research Results: “Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing.” Award & Administration Guide (AAG) Chapter VI.D.4 8
    9. 9. Plans for Data Management & Sharing Since January 18, 2011: • Proposals must include a supplementary document of no more than two pages labeled: “Data Management Plan” • Document should describe how the proposal with conform to NSF sharing policy NSF: Grant Proposal Guide (GPG) Chapter II.C.2.j of the Products of Research
    10. 10. Parts of a (Generic) NSF Data Management Plan I. Products of the Research: The types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project. II. Data Formats: 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). III. Access to Data and Data Sharing Practices and Policies: Policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. IV. Policies for Re-Use, Re-Distribution, and Production of Derivatives. V. Archiving of Data: Plans for archiving data, samples, and other research products, and for preservation of access to them. 10 Grant Proposal Guide (GPG) Chapter II.C.2.j
    11. 11. I. Types of Data & Other Information • 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? eCmmt002.svg Images by Antti-Pekka Hynninen
    12. 12. II. Data & Metadata Standards • Identify the formats of data files created over the course of the project • 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?
    13. 13. III. Policies for Access & Sharing • 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? IV. Policies for Re-use & Re-distribution
    14. 14. V. 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? 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?
    15. 15. Which NSF Requirement to Use? Which Guideline Should I follow?  First: follow the requirements laid out in the specific solicitation, if any.  Second: follow the guidelines published by the appropriate NSF directorate and/or division. If there is a conflict, the latter takes precedence.  Third: follow the more general guidelines. Interdisciplinary Proposals  Use guidelines appropriate to the lead program (if there are specific guidelines)
    16. 16. Data Management Planning Resources – Helps you create a data management plan to meet grant requirements and identify UVA support resources and policies – Helps you find an appropriate place to deposit your data - Helps UVA faculty, graduate students, and staff by providing a place to deposit and share datasets
    17. 17. Step-by-step wizard for generating DMP Create | edit | re-use | share | save | generate Open to community Links to institutional resources Directorate information & updates
    18. 18. Goals of the DMPTool I. To provide researchers a simple way to create a DMP for their funding agency • Questions asked by the agency • Additional explanation/context provided by the agency • Links to the agency website for policies, help, guidance
    19. 19. Goals of the DMPTool II. To provide researchers with DMP information from their home institution • Resources and services to help them manage data • Help text for specific questions • Suggested answers to questions; easy to cut-N- paste • News & events related to data management on campus
    20. 20. What is a Data Management Plan? • A comprehensive plan of how you will manage your research data throughout the lifecycle of your research project AND • Brief description of how you will comply with funder’s data sharing policy • Reviewed as part of a grant application
    21. 21. Data Management Plans • Grant Driven – Requirements – Sharing and public access to research • Operational – Research continuity – Avoiding data loss – Efficiency
    22. 22. Team Exercise 30 minutes 1. Identify a grant that you have or might apply for 2. Locate the requirements for that grant in the DMPTool: 3. Go through the sections in the DMPTool workflow to produce draft plan Be sure to address metadata, access policies, repositories . 4. Identify solutions and available support through DMPTool sections or ask for guidance 5. Record issues and questions for discussion
    23. 23. Presentation of Draft DMPs 15 minutes • Identify grant • Describe project briefly • Explain requirements • Describe planned solutions – Must address metadata, access policies, and repositories.
    24. 24. Questions and Discussion?
    25. 25. Follow-up • Contact the Data Management Consulting Group for help with DMP preparation Grant driven and operational: Email: