If no HXL hashtag is a perfect match, you still have a few options:
You can use a more general hashtag combined with attributes, e.g. #affected +refugees +injured +elderly +f for the number of elderly refugee women injured.
You can use the general #indicator hashtag combined with your own custom attribute to identify an indicator specific to your own organisation, project, or cluster, e.g. #indicator +facilities_damaged +num for the number of facilities damaged (where +facilities_damaged is the attribute that you created).
If no general hashtag applies, you can create your own custom hashtag beginning with “x_”, e.g. #x_virulence for the virulence of a disease.
No. It is fine to leave some columns untagged, especially if they’re highly-specialised data that wouldn’t be of general interest. However, if the answer to any of these questions is “yes,” we strongly recommend tagging:
Is the column important for connecting your data with related datasets (e.g. locations, dates, sectors, org names, population figures)?
Do you want to be able to work on the data in the column using HXL-aware tools (transform, validate, visualise, search, etc)?
Do you want to be able to operate on the data yourself, even if the column orders or headers change (e.g. importing into a database)?