Advocates of data sharing standards — guidelines for which elements ought to be included in a dataset for a particular datatype, controlled vocabularies for describing the data, or formatting specifications — usually tout effective reuse as the main benefit. Data can be understood more accurately, interpreted more easily, and technically stitched together at a much larger scale when it adheres to well-defined standards.
This is important. Crucial. That said, it isn’t what gets me excited about data standards.
I think data standards also make it easier for people to *share* their data. I don’t have evidence of this, but I think it is true. It may not be easier in terms of minutes and hours and curse words… some standards are fiddly unfortunate things. But it is easier in that it turns what was a cognitively difficult task into a cognitively easy one. *How* to share data (well)(or well enough)(or how to know what is well enough) is hard. How to get my data into that format is easier.
To the extent that data sharing becomes more institutionalized, less about whether and more about how, less about how and more about “how in the heck can I do that?”, we are on our way to cultural change.
Consequently, even though data sharing standards haven’t been my thing till now, I’m really happy to have joined in the efforts to collect and publish data sharing standards as part of the BMC series. Data standards are never perfect, they create their own problems, but they are the right sorts of problems.