Analyzing/mining specimen data for novel applications

One assumption is that all collections staff are concerned about their data and/or have appropriate technology skills.

These are generally the same people who on any given day are skinning a bird, checking a dermestid colony, performing integrated pest management, hunting down specimens for a loan or a borrower to get specimens back, supervising volunteers, interns and if they are lucky an actual paid assistant. Perhaps they learned Python or R while in school, but perhaps those languages weren’t even in use when they were in school. Yet it does seem that we expect that collections staff can manage data in the ways that often are discussed at the level of aggregators and that they all understand the technology and terms being used by the biodiversity data community.

This feeds into:

How do we avoid losing sight of the other important tasks that collections staff do? Maintenance of the physical specimens (which underpin the data) should be part of the puzzle.

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