This presentation is a crash course on practical data management. It is actually a portion of this talk (http://www.slideshare.net/kbriney/responsible-conduct-of-research-data-management) on data management and management plans, but I think the slides are useful enough to stand on their own.

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What if your hard drive crashes?
What if you are accused of fraud?
What if your collaborator abruptly quits?
What if the building burns down?
What if you need to use your old data?
What if your backup fails?
What if your computer gets stolen?
What if…
Do You Still Have Your Data?

2. Why Data Management?
• Don’t lose data
• Find data more easily
– Especially if you need older data
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Easier to analyze organized, documented data
Avoid accusations of fraud & misconduct
Get credit for your data
Don’t drown in irrelevant data

3. For each minute of planning at
beginning of a project, you will save
10 minutes of headache later

4. What Are Data?
http://www.flickr.com/photos/dia-a-dia/7046151669/ (CC BY-NC-SA)

5. What Are Data?
• “Research data is defined as the recorded
factual material commonly accepted in the
scientific community as necessary to validate
research findings”
– OMB Circular A-110
http://www.whitehouse.gov/omb/circulars_a110

6. What Are Data?
• Observational
– Sensor data, telemetry, survey data, sample
data, images
• Experimental
– Gene sequences, chromatograms, toroid magnetic
field data
• Simulation
– Climate models, economic models
• Derived or compiled
– Text and data mining, compiled database, 3D
models, data gathered from public documents

7. A Crash Course in
PRACTICAL DATA MANAGEMENT

8. Storage and Backups
http://www.flickr.com/photos/9246159@N06/599820538/ (CC BY-ND)

9. Storage and Backups
• Library motto: Lots of Copies Keeps Stuff Safe!
• Rule of 3: 2 onsite, 1 offsite
• Any backup is better than none
• Automatic backup is better than manual
• Your research is only as safe as your backup
plan
– Periodically test restore from backup!

10. Example
• I keep my data
– On my computer
– Backed up manually on shared drive
• I set a weekly reminder to do this
– Backed up automatically via SpiderOak cloud
storage
• A note on cloud storage…

11. Consistency
http://www.flickr.com/photos/mactucket/361798299/ (CC-BY-ND)

12. Consistency
• Consistent file naming
– Make it easier to find files
– Avoid many duplicates
– Make it easier to wrap up a project
• Names descriptive but short (<25 characters)
• Avoid “ / : * ? ‘ < > [ ] & $ and spaces
• Date convention: YYYY-MM-DD

13. Examples
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DataManagement_v6.pptx
20090923_spctrm_trans_03.csv
SLAposter_FINAL.ai
BlogPost-2011-11-12.docx
• Find a system that works for you

14. Consistency
• Consistent documentation
– Record all necessary information
– Keep information in one place
– Easier to search and use later
• Take 5 minutes before starting a project
• Create a list of information to record
– Don’t forget to record the units!

15. Example
• For my experiment, I need to collect:
– Date
– Experiment
– Scan number
– Powers
– Wavelengths
– Concentration (or sample weight)
– Calibration factors, like timing and beam size

16. Recording Your Conventions
http://www.flickr.com/photos/jjpacres/3293117576/ (CC BY-NC-ND)

17. Recording Your Conventions
• What if someone needs to find your data?
• Eventually will hand off data to your PI
• Record your naming conventions
• Record your documentation schemes
• Record overall project information
– Contact info, grant #, project summary, etc.

18. Examples
• Print out near computer/experiment area
– Document conventions
• In front of research/lab notebook
– Page 1: Project information
– Page 2: Conventions and abbreviations
– Page 3-X: Index of experiments
• README.txt in data folder
– Top-level folder: project information
– Lower-level folder: what’s in this folder?

19. Planning for the Future
http://www.flickr.com/photos/bonedaddy/2791636546/ (CC BY-SA)

20. Planning for the Future
• Get help for sensitive data!
– HIPAA, FERPA, FISMA, IRB, etc.
• UWM Information Security Office
– Visit: www.uwm.edu/itsecurity/
• Policy pages
– www.uwm.edu/legal/hipaa/index.cfm
– www.uwm.edu/academics/ferpa.cfm

21. Planning for the Future
• We can’t open files from 10 years ago
• Proprietary file types
– Convert to open file format
• .doc  .txt
• .xls  .csv
• .jpg  .tif
– Preserve software if no open file format
• Periodically move data to new media

22. Goal: Don’t Stress Over Data
http://www.flickr.com/photos/72775875@N06/7729764370/ (CC BY-NC-SA)

23. More Information
• Data Services
– www.uwm.edu/libraries/dataservices/
• Data Management Plans
– dataplan.uwm.edu
• Kristin Briney, Data Services Librarian
– Contact me!

24. Thank You
• The content of this presentation is licensed
under a Creative Commons Attribution 3.0
Unported License (CC BY)
– Image licenses as marked