data-housekeeping.md

Data housekeeping

File names

General pricinples

• Machine readable
• Human readable
• Plays well with default ordering

Separators

• No spaces
• Underscore to separate
• Hyphen to combine

Date format follows ISO 8601

2018-12-03
2018-12-06_1700

Bad names

 PhD-project-Jan19 alldata_final.foo
 Finacial detailes BIocore 19/11/12.xls
 ATACseq1Londonmapped.bam
 Hlad.jez.M-L-průtoky JíObj.z Ohře-od 10-2011.xlsx

Good names

Iris-setosa_samples_1927-05-12.csv
PI102_Mouse12_EEG_2018-11-03_1245.tsv
Bioinfiniti_FullProposal_2018-11-15_1655.do

From Jenny Bryan by CC-BY (https://speakerdeck.com/jennybc/how-to-name-files)

Data housekeeping

File organization

• Have folder organization conventions for your group

  • Per Paper
  • Per Study/Project
  • Per Collaborator

• Keep readme files for data

  • Title
  • Date of Creation/Receipt
  • Instrument or software specific information
  • People involved
  • Relations between multiple files/folders

• Separate files you are actively working from the old ones

• Orient newcomers to the group's conventions

Foundational Practices of Research Data Management

Data housekeeping

When working

• Clarify and separate source and intermediate data
• Keep data copies to a minimum
• Cleanup post-analysis
• Cleanup copies created for presentations or for sharing

Data housekeeping

End of project

• handover data to a new responsible when leaving
• data should be kept as a single copy on server-side storage
  • no copies on desktops and external devices
• non-proprietary formats
• minimal metadata
• sensitive data (e.g. whole genome) must be encrypted

* If not specified otherwise, data must be kept for **10 years** following project end for reproducibility purposes Note: sometimes it is hard to find/understand dataset 10 days old

In doubt on data archival?

Contact R³ for support on archival of datasets using tickets:

• https://service.uni.lu/sp
• Home > Catalog > LCSB > Biocore: Application services > Request for: Support

Research Data Retention and Archival Policy

Data housekeeping - Summary

Server is your friend!

• Allows a consistent backup policy for your datasets
• Keeps number of copies to minimum
• Specification of clear access rights
• High accessibility
• Data are discoverable
• Server can't be stolen

General guidelines

• Use institutional media for storage of all data
• Research data (particularly sensitive data) should be in a single source location
• Enable encryption for data stored on movable media
• Clarify and separate source and intermediate data
• Disable write access to relevant source data (read-only)
• Backup research data!
• Download Anti-virus software
• Generate checksums