Data Mangement Brown-bag/Seminar [Iowa State Univ.]
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An introduction to data management and how to prepare and write a data management plan. Discuses ways to meet funding agency requirements as well as best practices and local solutions. The video on ...

An introduction to data management and how to prepare and write a data management plan. Discuses ways to meet funding agency requirements as well as best practices and local solutions. The video on slide 10 is available at: http://youtu.be/N2zK3sAtr-4

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  • Not just the PIsHow would good data management advance your goals?
  • Format impacts accessibility, sharing and preservation. - proprietary formats? Standard formats for your discipline? Analog formats? (paper)What kind of data will you be working with?Observational, experimental, simulation, derived, etc.How are they collected or gathered?Surveys, direct observation, images, audio analysis, etc.What is the expected size of the data?Will the size impact other parts of the project?
  • Metadata, commonly called "data about data", is information which describes data. Good metadata enables others understand and reuse data that they themselves did not create. Metadata elements should be agreed upon and implemented before starting data collection. Data collection and documentation is easier if you know what you need to record and helps maintain consistency and quality.
  • Can help you locate an appropriate repository.Will broaden your research’s impact
  • Dryad allows you to track downloads of the data (research impact)Assigns a DOI – tracking and locatingPackages data with metadata for easy reusePreforms preservation actions like validating checksums
  • More detailed answers for question related to DMPs

Data Mangement Brown-bag/Seminar [Iowa State Univ.] Presentation Transcript

  • 1. Data Management Brown-bag/Seminar November 5, 2013 Bonnie Bowen, Dept. Ecology, Evolution & Organismal Biology Megan O’Donnell, Scholarly Communications Librarian Andrea Dinkelman, Science & Technology Librarian
  • 2. Data Images: wikipedia, lepidopteralovers.com, wessexchemicalfactors.co.uk, oldcomputers.net, xbmxhub.com, multimedia.journalism.berkeley.edu, alexanderlab.org, pnas.org
  • 3. Data Management: Our Goals Today • Why should we care about data management? • What resources are available to help and assist data management and data management planning? • What are Best Practices for data management? • What tools are available for developing Data Management Plans (DMPs)? • What ISU resources are available?
  • 4. Why should we care about data management? • Requirement of funding agencies • • • • NSF requires a data management plan in all proposals Data sharing is a component NIH has data sharing policy Other agencies likely to add or refine requirements in the future • NSF awards support ISU research: • In FY 2013 >$38,000,000 • Top 9 departments represent three STEM colleges • ECpE, ME, GDCB, EEOB, Chem, CompSci, BBMB, Geol/Atmos Sci, Agron
  • 5. Why should we care about data management? • As scientists, we need to be able to use our data now and in the future • Scientific findings built on data • We are experiencing an explosion of data and information • To use data now and in the future, it needs to be managed
  • 6. Data Management: Our Goals Today • Why should we care about data management? • What resources are available to help and assist data management and data management planning? • Why the Library? • Library Guide for Data Management
  • 7. Library Guide http://instr.iastate.libguides.com/dmp • Home: • Funding agency requirements • Recommended readings • • • • Best Practices ISU Resources DMP checklists Data & text repositories • FAQs
  • 8. Data Management: Our Goals Today • Why should we care about data management? • What resources are available to help and assist data management and data management planning? • What are Best Practices for data management?
  • 9. Library Guide: Best Practices • • • • • • • Know your data Document your data Make your data and notes understandable Keep your data organized Keep copies and make backups Secure your data Resources: DataONE Primer on data management and DataONE Best Practices
  • 10. Data Sharing and Management
  • 11. Library Guide: Best Practices • Know your data • Document your data • Keep your data organized • Keep copies and make backups • Make your data and notes understandable • Secure your data
  • 12. Data Management: Our Goals Today • Why should we care about data management? • What resources are available to help and assist data management and data management planning? • What are Best Practices for data management? • What tools are available for developing Data Management Plans?
  • 13. Library Guide: DMP Checklists • Boiler plate language for CyBox and DR@ISU • Short checklist • Full checklist • Links to tools and resources for writing and developing a DMP
  • 14. The Checklists Short Full • Only contains the “bare essentials” • Is focused on the big picture • 6 sections with 3 questions each • Drills down to the details • Contains links to “more information” • 7 sections; variable number of questions per section • A good place to start • Will help you develop a comprehensive DMP
  • 15. Full Checklist – section 0: Describe the Research Project • Recap only the aspects that apply to data management. • Who is involved? • What’s the goal? • What are your expected research products? Databases? Images? Code/Software? Image credits: Sean MacEntee (databases); NIAID (SEM image); James Cridland (code) ; all via Flickr
  • 16. Full Checklist – section 1: Data Description & Identification Describe and identify the data products of your proposal. • Formats • Digital: .jpeg, .pdf, .csv, webpages, etc. • Analog: lab notebooks, surveys, specimens/artifacts, etc. • Kinds of data • Observational, experimental, simulation, derived? • Methods of collection • Surveys, direct observation, remote sensors ? • Expected sizes
  • 17. Full Checklist – section 2: Data Creation & Organization How will your data be managed and what steps are being taken to ensure quality? • File naming and organization systems • Quality assurance • File versioning Image credits: PhD Comics: “Final”.doc
  • 18. Full Checklist – section 3: Data Documentation & Metadata For data to be useful to you, your colleagues, and other researchers, it needs to be carefully documented and described. • What is metadata? (not just for use by the NSA) • “data about data” which provides descriptive information. • Why is metadata important? • It facilitates reuse by other researchers (including other members of your research team). • Discoverability – it lets others find your data.
  • 19. Full Checklist – section 4: Data Storage, Backup, & Security Technical information about the machines, software, and systems used to create, backup, and store your data. • Locations • Physical and digital • Security • Who has access? How is it secured? • Disaster Planning • How often do you make backups? Where are they stored?
  • 20. Full Checklist – section 5: Data Sharing & Ethics What are your plans for data sharing and distribution? • Can the data be shared? • Are there any legal or ethical restrictions that prevent sharing? • How will others find, locate, and access the data? • How long will it be available? • Will the data be stored in a repository? (more on this soon)
  • 21. Full Checklist – section 6: Data Preservation Storage is not preservation. Storage is static; preservation is an active process. Preserving is defined as: 1. To maintain in safety from injury, peril, or harm; protect. 2. To keep in perfect or unaltered condition; maintain unchanged….” Definition source: American Heritage Dictionary of the English Language, Fourth Edition copyright ©2000 by Houghton Mifflin Company.
  • 22. Full Checklist – section 6: Data Preservation Data preservation is a complex and on-going commitment. To start, decide: • Which data will be preserved? • What is the long-term value of the data? • Who will have custody? • Will you deposit your data in repository? • Trusted repositories are institutions devoted to both storage and preservation. Definition source: American Heritage Dictionary of the English Language, Fourth Edition copyright ©2000 by Houghton Mifflin Company.
  • 23. Library Guide: Repositories • Data & Text Repositories • Data Repositories: • Dryad, GenBank, ICPSR, TreeBASE, Dataverse Network, FigShare, etc. • Find a Data Repository • Databib, Re3data.org, DataONE, etc. • Text Repositories • Institutional: • Digital Repository @ Iowa State University • Disciplinary: • ArXIv, CogPrints, Earth-Prints, etc.
  • 24. Data Repository: Dryad • Tracks downloads • Assigns a DOI to datasets. • Includes instructions for citation • Packages data with metadata. • Preservation actions
  • 25. Library Guide: FAQs • Targeted answers on specific topics such as: • What counts as data? • What is metadata? • What if my research doesn’t produce data? • What if I cannot share my data? • And more!
  • 26. Data Management: Our Goals Today • Why should we care about data management? • What resources are available to help and assist data management and data management planning? • What are Best Practices for data management? • What tools are available for developing Data Management Plans? • What ISU resources are available?
  • 27. Library Guide: ISU Resources • ITS Policies and Standards • Digital Repository @ Iowa State University • ISU’s open access repository for scholarly and creative works • Can be used to fulfill open access mandates for research papers • Data Storage Services • CyBox • Cloud storage, file versioning, syncs to multiple machines, 30-day file recovery, etc. • CyFiles / OrgFiles
  • 28. Questions? • Contact information: • Megan O’Donnell – mno@iastate.edu • Bonnie Bowen – bsbowen@iastate.edu • Feedback form on the guide • Workshop evaluation form – please fill out today