Lab notebook software
Last year, I wrote about using Evernote as my digital lab notebook. With the release of Findings, a new digital notebook software from the people who created my favorite reference management software Papers, I thought I would reflect on my digital notebook needs.
A digital notebook should be:
- Indexed and searchable, with both automatic (embedded text searching) and manual (tags) search functions. Evernote handles this quite well- I can easily manage what tags I have available and organize them how I wish, but searching my notebook will also find terms in embedded word documents and PDFs, for example.
- OS integration. The great thing about drinking the Apple koolaid is these apps can work well across platforms. We don’t tend to have our laptop on our experimental benchtop; being able to pull up a notebook on my iPhone is great.
- Multimedia friendly. My notebook is a mix of text, snapshots, data annotated in Powerpoint, excel files, word documents, and PDFs. Again, Evernote handles this quite well. It falters a bit in flexibility when printing out my notebook- usually my images don’t come out formatted quite right and I end up with a single image per page.
A sample printout from my notebook. Note that I have a mix of media types (annotated powerpoint files, notebook scans, raw text). While Evernote holds them all seamlessly, printing to this PDF (and into a paper notebook) results in clunky blank pages. There is also no support for printing header information: ie experiment name, tags, dates… I have to manually write the file name on each page afterwards.
- Traceable. Ultimately, a lab notebook is for tracing the lineage of data. Whether this is at the troubleshooting or the writeup phase, I need to understand what the starting material, protocol, and resulting output were at each stage of the experiment. Science is seldom perfect, and a good lab notebook can prevent some confusing mixups (was that DNA sample prepared before or after I optimized the pH of buffer X?) Here is where Evernote isn’t perfect, largely because this is a science problem.
I’m looking forward to trying out Findings and reporting back how it improves on these key issues (and others I haven’t thought about).