Data Management Brown-bag/Seminar March 12, 2014



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Transcription:

Data Management Brown-bag/Seminar March 12, 2014 Bonnie Bowen, Dept. Ecology, Evolution & Organismal Biology & SP@ISU Megan O Donnell, Scholarly Communications Librarian

Data Images: wikipedia, lepidopteralovers.com, wessexchemicalfactors.co.uk, oldcomputers.net, xbmxhub.com, multimedia.journalism.berkeley.edu, alexanderlab.org, pnas.org

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?

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

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

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

Library Guide http://instr.iastate.libguides.com/dmp Home: Funding agency requirements Recommended readings Best Practices ISU Resources DMP checklists Data & text repositories FAQs

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?

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

Data Sharing and Management

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

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?

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

The Checklists Short Only contains the bare essentials Is focused on the big picture 6 sections with 3 questions each Full 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

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

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

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

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.

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?

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)

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.

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.

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.

Data Repository: Dryad Tracks downloads Assigns a DOI to datasets. Includes instructions for citation Packages data with metadata. Preservation actions

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!

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?

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

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