Content is adapted from the Love Your Data website.
It’s day 3 of Love Your Data Week! Today is all about documentation – one of the easiest and hardest things about data management! Documenting your data is all about giving it context and ensuring that it continues to be usable to you and others. Today’s activity will help you think through using readme files, writing metadata, and taking better notes. If you’ve made improvement to your data documentation, share it with us on Twitter!
Document, document, document! You probably won’t remember that weird thing that happened yesterday unless you write it down. Your documentation provides crucial context for your data. So whatever your preferred method of record keeping is, today is the day to make it a little bit better! Some general strategies that work for any format:
- Be clear, concise, and consistent.
- Write legibly.
- Number pages.
- Date everything, use a standard format (ex: YYYYMMDD).
- Try to organize information in a logical and consistent way.
- Define your assumptions, parameters, codes, abbreviations, etc.
- If documentation is scattered across more than one place or file (e.g., protocols & lab notebook), remind yourself of the file names and where those files are located.
- Review your notes regularly and keep them current.
- Keep all of your notes for at least 7 years after the project is completed.
Things to Avoid
- Writing illegibly.
- Using abbreviations or codes that aren’t defined.
- Using abbreviations or codes inconsistently.
- Forgetting to jot down what was unusual or what went wrong. This is usually the most important type of information when it comes to analysis and write up!
Take a few minutes to think about how you document your data. What’s missing? Where are the gaps?
If your documentation could be better, try out some of these strategies and tools.
- Readme files are a simple and low-tech way to start documenting your data better. Check out the sample readme.txt (filename = ) from IU.
- Cornell University RDMSG also has a guide with tips for using readme files
- Check out Kristin Briney’s post on taking better notes
- Cornell University RDMSG has some tips for writing metadata