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![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](/image.pl?url=https%3a%2f%2fimage.slidesharecdn.com%2fdatamanagementcrashcourse-131122135249-phpapp01%2f75%2fData-Management-Crash-Course-12-2048.jpg&f=jpg&w=240)
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Data Management Crash Course
The document emphasizes the importance of data management to prevent data loss, facilitate data retrieval, and ensure data integrity. It outlines best practices for storage, backups, consistency in file naming and documentation, and planning for future data accessibility. It concludes by providing resources for further assistance, including data services and management plans.
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Data Management Crash Course
- 1.••••••••What if yourhard 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••••Easier to analyze organized, documented dataAvoid accusations of fraud & misconductGet credit for your dataDon’t drown in irrelevant data
- 3.For each minuteof planning atbeginning of a project, you will save10 minutes of headache later
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- 5.What Are Data?•“Research data is defined as the recordedfactual material commonly accepted in thescientific community as necessary to validateresearch findings”– OMB Circular A-110http://www.whitehouse.gov/omb/circulars_a110
- 6.What Are Data?•Observational– Sensor data, telemetry, survey data, sampledata, images• Experimental– Gene sequences, chromatograms, toroid magneticfield data• Simulation– Climate models, economic models• Derived or compiled– Text and data mining, compiled database, 3Dmodels, data gathered from public documents
- 7.A Crash CourseinPRACTICAL DATA MANAGEMENT
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- 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 backupplan– Periodically test restore from backup!
- 10.Example• I keepmy data– On my computer– Backed up manually on shared drive• I set a weekly reminder to do this– Backed up automatically via SpiderOak cloudstorage• A note on cloud storage…
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- 12.Consistency• Consistent filenaming– 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
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- 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 myexperiment, I need to collect:– Date– Experiment– Scan number– Powers– Wavelengths– Concentration (or sample weight)– Calibration factors, like timing and beam size
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- 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 outnear 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 theFuturehttp://www.flickr.com/photos/bonedaddy/2791636546/ (CC BY-SA)
- 20.Planning for theFuture• 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 theFuture• 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 StressOver Datahttp://www.flickr.com/photos/72775875@N06/7729764370/ (CC BY-NC-SA)
- 23.More Information• DataServices– www.uwm.edu/libraries/dataservices/• Data Management Plans– dataplan.uwm.edu• Kristin Briney, Data Services Librarian– Contact me!
- 24.Thank You• Thecontent of this presentation is licensedunder a Creative Commons Attribution 3.0Unported License (CC BY)– Image licenses as marked