2013 hackathon data elements
Target Data Elements
Primary scoring for critical items dwc:catalogNumber dwc:recordedBy dwc:recordNumber dwc:verbatimEventDate aocr:verbatimScientificName Secondary scoring for other key items aocr:verbatimInstitution dwc:datasetName dwc:verbatimLocality dwc:country dwc:stateProvince dwc:county dwc:verbatimLatitude dwc:verbatimLongitude Lastly, scoring for optional items dwc:eventDate dwc:scientificName dwc:decimalLatitude dwc:decimalLongitude dwc:fieldNotes dwc:sex dwc:dateIdentified dwc:identifiedBy
Given the discussion from the broader community, it may also be that we change our minds with respect to what belongs in categories above. For now, those fields above should be seen as the ones of general interest and we can be flexible and discuss our evaluation strategy further with regard to primary / secondary / last. Participants may decide what is more important. It's clear that who is using the data and for what purpose drives which fields are seen as of greater value. If you are trying to find duplicate voucher records, the "who" is very important. If you are an ecologist looking for evidence of an organism in nature, you are more interested in the "where" fields and not so much interested in who collected the physical object as a voucher.
Note extra credit will be figured in for those that manage to get their data from CSV to XML format. Extra credit may also be given for those that manage to get their CSV columns according to the order of the fields as their appear in the image.
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