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

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