To become widely accepted by the research community, citizen-science projects must underscore the need to apply standards for all phases of community-generated data flow gathered by large numbers of people with varying level of expertise. Within the context of biodiversity it means standardization and validation of respective data categories such as: taxonomic identifications, habitat-code, monitoring and sampling protocols, confirmation protocols, data fields and formats (e.g. dates, time, units) and of geolocations, to name a few.
Hence data-quality of public-based observations must be the main target while setting up metadata as in the above list.
The required field should answer the obvious questions that any researcher will ask when considering using the data.
That said, here are a bunch of data-quality topics that should/recommended considering for metadata fields:
– Identification-capacity -namely participant skill levels
– Training method
– Protocol in use or sampling design
– Validation method/processes
– Confirmation and approval process (e.g by expert reviewers, name, professional/experience level)
– Source of data for identification of species (e.g identification by name or using a picture)
– Existing document, e.g. picture taken
– Accuracy of measurements , or source of measured data , e.g. (coordinates, temperature, level above sea)
There is much more to those, but I guess I made the point.
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