Blog
- Home /
- Blog
Do's and Don'ts in Research Data Management
Research Data Management Do’s and Don’ts - Step up your RDM skills!
1. Structuring and naming your folders There is an easy way to make your data findable for you and your team: establish a folder structure which makes sense for you and your working group as well as naming conventions for your folders.
Don’t:
Paul and Suzie
»Guideline
>application
»version2_final
»v.3
»review
»3rd.version
>JD
»qn
»0-1
Instead do:
000_int_orga
Read More
»01_application
»02_review 120_questionaires
»01_qualitative »02_quantitative 130_data
»01_qualitative »02_quantitative
Documentation From User Experience
- Marvin Lorber
- Documentation , Software , RDM
This post is a condensed version of a talk at our Data Compentcy College
If you regularly use scientific software written by others, or tried to replicate interesting research that relies on software, you have probably also invested weeks of work to solve a software problem or even given up on a software because of missing documentation. Finding a project that might be the solution to your problem and then failing to run the code is frustrating. Being unable to run a project you have built yourself years ago is even worse. Having experienced all those setbacks myself in the past I want to use this post to channel that frustration to fuel solutions for better documentation for our current and future projects.
Read MoreTags
- Carpentries
- Collaborative Editing
- Competition
- Consulting
- CRDT
- Data Analytics
- Data Cafe
- Data Vizualization
- DKZ-Event
- Documentation
- Editors
- Emacs
- Fdm-Werkstatt
- FLINTA
- General_consulting
- Git
- GitLab
- How To
- HPC
- LaTeX
- Literate Programming
- Machine Learning
- Main
- Metadata
- Org Mode
- Org-Babel
- Participation
- Python
- R
- Research Data Management
- Self-Study
- Seminar
- Software
- Statistical Learning
- Statistics
- Training
- Trainings
- Unix Shell
- Vim
- Workshop