Practical Data Management

1. Practical Data Management ACRL DCIG Webinar 30 April 2014 Kristin Briney, PhD

2. andrius.v, https://www.flickr.com/photos/banditaz/6823875954 (CC BY-NC-SA)

3. Mr.TinDC, https://www.flickr.com/photos/mr_t_in_dc/5940438148 (CC BY-ND)

4. International Institute of Tropical Agriculture, https://www.flickr.com/photos/iita-media-library/8160877379 (CC BY-NC) MusgoDumio_Momio, https://www.flickr.com/photos/30976576@N07/2903662286 (CC BY-NC-SA)

5. Jen Doty and Rob O'Reilly, “Learning to Curate @ Emory”. RDAP 2014

6. Data Management Basics • Introduction to a few topics in data management • File organization and naming • Documentation • Storage and backups • Future file usability

7. Data Management Basics • Introduction to a few topics in data management • File organization and naming • Documentation • Storage and backups • Future file usability  Teach & Use

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

9. File Organization & NAming Dan Zen, http://www.flickr.com/photos/danzen/5551831155/ (CC BY)

10. File Organization • What? • Keeping your files in order

11. File Organization • Why? • Easier to find and use data • Tell, at a glance, what is done and what you have yet to do • Can still find and use files in the future

12. File Organization • When? • Always! • Get in the habit of putting files in the right place

13. File Organization • How? • Any system is better than none • Make your system logical for your data • 80/20 Rule • Possibilities • By project • By analysis type • By date • …

14. Example • Thesis • By chapter • By file type (draft, figure, table, etc.) • Data • By researcher • By analysis type • By date

15. File Naming Conventions • What? • Consistent naming for files

16. http://retractionwatch.com/2014/01/07/doing-the-right-thing-authors-retract-brain-paper-with-systematic-human-error-in-coding/http://retractionwatch.com/2014/01/07/doing-the-right-thing-authors-retract-brain-paper-with-systematic-human-error-in-coding/

17. File Naming Conventions • Why? • Make it easier to find files • Avoid duplicates • Make it easier to wrap up a project because you know which files belong to it

18. File Naming Conventions • When? • For a group of related files (3 to 1000+) • May need different conventions for different groups

19. File Naming Conventions • How? • Pick what is most important for your name • Date • Site • Analysis • Sample • Short description

20. File Naming Conventions • How? • Files should be named consistently • Files names should be descriptive but short (<25 characters) • Use underscores instead of spaces • Avoid these characters: “ / \ : * ? ‘ < > [ ] & $ • Use the dating convention: YYYY-MM-DD

21. Example • YYYYMMDD_site_sampleNum • 20140422_PikeLake_03 • 20140424_EastLake_12 • Analysis-sample-concentration • UVVis-stilbene-10mM • IR-benzene-pure

22. Documentation Brady, https://www.flickr.com/photos/freddyfromutah/4424199420 (CC BY)

23. What would someone unfamiliar with your data need in order to find, evaluate, understand, and reuse them?

24. Documentation • Why? • Data without notes are unusable • Because you won’t remember everything • For others who may need to use your files

25. Documentation • When? • Always • Documentation needs will vary between files

26. Documentation • How? • Take good notes • Metadata schemas • http://www.dcc.ac.uk/resources/metadata-standards

27. Documentation • How? • Methods • Protocols • Code • Survey • Codebook • Data dictionary • Anything that lets someone reproduce your results

28. Documentation • How? • Templates • Like structured metadata but easier • Decide on a list of information before you collect data • Make sure you record all necessary details • Takes a few minutes upfront, easy to use later • Print and post in prominent place or use as worksheet

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

30. Documentation • How? • README.txt • For digital information, address the questions • “What the heck am I looking at?” • “Where do I find X?” • Use for project description in main folder • Use to document conventions • Use where ever you need extra clarity

31. Example • Project-wide README.txt • Basic project information • Title • Contributors • Grant info • etc. • Contact information for at least one person • All locations where data live, including backups

32. Example “Talk_v1: rough outline of talk Talk_v2: draft of talk Talk_v3: updated 2014-01-15 after feedback” “ ‘Data’ folder contains all raw data files by date ‘Analysis’ has analyzed data and plots ‘Paper’ has drafts of article on this work”

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

34. Storage • Why? • Need good storage practices to prevent loss • Keep data secure

35. Storage • How? • Library motto: Lots of Copies Keeps Stuff Safe! • Rule of 3: 2 onsite, 1 offsite

36. Storage • How? • Computer • External hard drive • Shared drives/servers • Tape backup • Cloud storage* • CDs/DVDs • USB flash drive Erica Wheelan, https://www.flickr.com/photos/reinventedwheel/5985479866 (CC BY)

37. *Cloud Storage • Read the Terms of Service! • Eg. Google Drive • “When you upload or otherwise submit content to our Services, you give Google (and those we work with) a worldwide license to use, host, store, reproduce, modify, create derivative works (such as those resulting from translations, adaptations or other changes we make so that your content works better with our Services), communicate, publish, publicly perform, publicly display and distribute such content. The rights you grant in this license are for the limited purpose of operating, promoting, and improving our Services, and to develop new ones”

38. Backups http://toystory.disney.com/

39. Backups • How? • Any backup is better than none • Automatic backup is better than manual • Your work is only as safe as your backup plan

40. Backups • How? • Check your backups • Backups only as good as ability to recover data • Test your backups periodically • Preferably a fixed schedule • 1 or 2 times a year may be enough • Bigger/more complex backups should be checked more often • Test your backup whenever you change things

41. 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

42. Future File Usability Ian, http://www.flickr.com/photos/ian-s/2152798588/ (CC BY-NC-ND)

43. Future File Usability • What? • Can you read your files from 10 years ago? • Data needs to be • Accessible • Interpretable • Readable

44. lukasbenc, https://www.flickr.com/photos/lukasbenc/3493808772 (CC BY-NC-SA)

45. Future File Usability • Why? • You may want to use the data in 5 years • PI sometimes keeps data and notes • Prep for data sharing • Per OMB Circular A-110, must retain data at least 3 years post-project • Better to retain for >6 years

46. Future File Usability • When? • When you wrap up a project • (As you work on a project)

47. Future File Usability • How? • Back up written notes • People always forget this one • Difficult to interpret data without notes • Options • Digitally scan (recommended with digital data) • Photocopies

48. Future File Usability • How? • Convert file formats • Can you open digital files from 10 years ago? • Use open, non-proprietary formats that are in wide use • .docx .txt • .xlsx .csv • .jpg  .tif • Save a copy in the old format, just in case • Preserve software if no open file format

49. Future File Usability • How? • Move to new media • Hardware dies and becomes obsolete • Floppy disks! • Expect average lifetime to be 3-5 years • Keep up with technology

50. Where to Go from Here