Should you georeference your scientific data?

As Jeff Thurston writes in his blog, a strong case can be made for spatially enabling scientific research. This is especially true for biological / ecological research as biological processes occur across different scales. It certainly would make it that much easier to re-use or complement existing data. Not only would it facilitate collaboration amongst researchers, it would also help ‘end-users’ to find information that is relevant to them.

In some disciplines including location data in the meta-data is well established. Good examples are the accessions in herbaria, which often include information  about where the specimen has been collected. And herbaria working hard to get their collection digitized and geo-referenced. See for example the work of Kew Botanical Gardens on the digitization of their herbarium material.

Getting their accessions digitized is a huge undertaking. For example, the Kew Botanical Gardens has more than 7 million specimens. But, as argued in the editorial of Nature ‘A place for everything‘,  for new data geo-referencing has become much easier using Global Positioning System (GPS) at the point of capture, or any other specified point of relevance.

Being so easy to capture and store spatial data, there isn’t really an excuse not collecting spatial information only because it is not relevant to the data collector’s project. After all, it might not be relevant to you, but it could make your research more relevant to others.

Two nice, but very different examples, of how spatially enabled data can be stored, shared and used are:

  • An interesting initiative is the Publishing Network for Geoscientific and Environmental Data (PANGAEA). This is a data library for georeferenced data from earth system research operated in Open Access.
  • See for a great example of distribution of spatially enable data (species occurrence data). It goes one (big) step further, it can also generate probability distribution maps under different climate change scenarios. It thus makes data available in a form useful for non-specialists.

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