Excel Spreadsheets
“I had the worst day today; all my falcon tubes had their tops missing, the centrifuge wasn’t cleaned in a year and I had to look for my samples on 4 different floors.” This is not a common complaint you hear around any reasonably run biomedical institute. If it were, not a single project worthy of publication in Science, Nature or Cell would ever be finished. Scientists understand that tidying up is vital for project success as well as good relations with colleagues and collaborators. Unfortunately, the same care is almost never extended to the digital output, mostly stored in Excel spreadsheets, of these same projects. Data pertaining to the same project are routinely stored over many individual Excel spreadsheets. Sometimes multiple data sets are shared in the same spreadsheet with only an empty column or row separating them. Information describing the data are for the most scarce, completely missing or color coded. However unlike messy laboratories, only rarely does a messy Excel spreadsheet lead to the complete breakdown of science (here is one example). This comforting fact though should not result in complacency! The current status quo is maintained on the backs of data analysts who spend 80% of their time cleaning and managing data sets.
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The problem, as so often, arises because we fail to train wet lab scientists in data management. Most supervisors will never talk to their PhD students about adequate ways to record their data, courses at university rarely concern themselves with such trivial matters and the collaborating data analyst will never be consulted. Furthermore while the correct manner to store data is obvious to anyone tasked with the analysis of the data, it can be arduous and hard to explain. Just imagine having to spell out that most analysis software cannot read different colors very easily. However, this should not cause us to give up and accept that most of our time will be taken up with the most tedious job known to mankind: Cleaning someone else’s mess!
