Data Management

CC-BY Kristin Briney, Data Services Librarian University of Wisconsin-Milwaukee Libraries http://www4.uwm.edu/libraries/dataservices/

Use Backups

Rule of 3: have 2 on-site copies, 1 offsite

Automate backups whenever possible

Periodically test restore data from backups

Be Consistent

Name your files consistently

Avoid spaces and the following characters: “ / \ : * ? ‘ < > [ ] & $

Use date conventions: YYYY-MM-DD or YYYYMMDD

Examples: 20090923_spctrm_trans_03.csv, SLAposter_FINAL.ai, BlogPost-2011-11-12.docx

Consistent documentation

Think about documentation before you start a project

Make a list of the information to record when you acquire a dataset

Examples: date, experiment, sample number, calibration factors, temperature, etc.

Document Your Conventions

Print out near computer/experiment area

In front of research/lab notebook

Page 1: Project information

Page 2: Document conventions and abbreviations

Page 3-X: Index of experiments (use 1 index line per page in notebook)

README.txt in computer folders

Top-level folder: Project information

Lower-level folders: What’s in this folder?

Plan ahead

Get security assistance if you deal with HIPPA, FERPA, IRB, or other sensitive information

UWM Information Security Office: www.uwm.edu/itsecurity/

HIPAA: www.uwm.edu/legal/hipaa/index.cfm

FERPA: www.uwm.edu/academics/ferpa.cfm

Avoid proprietary file formats or convert to them as soon as possible

Examples: .doc to .txt, .xls to .csv, .jpg to .tif

Preserve software if no open format available

Periodically move data off outdated media