Choosing keywords#

There are a few categories you should try to cover when assigning keywords:

  • dataset acronym: if your data is strictly related to another dataset, or your code is applied to a specific dataset

  • model acronym and version: as for datasets if you generated the data using a model

  • project acronym: if your dataset and or code relates to a specific project

  • programming language: you should add this to your code records and be as specific as possible, for example use python3, rather than just python

  • data type: observation, model output, etc.

  • realm or discipline: like ocean, land and/or physical oceanography, climate science etc. For the disciplines you can use the Fields of Research codes from the Bureau of Statistics

  • variable names: if you have many just list the more relevant

  • spatiotemporal characteristic of the data: frequency, resolution, region covered

Every time you define a keyword you should favour terms provided in a vocabulary, the GCMD keywords for example will cover most of the categories listed above. If you are using a speciifc name as for datasets, models and projects, then use the official acronyms and specify the versions whenever possible.

Also remember that if a portal has a free text search, any word in your title will be also used as a keyword, which is why it is useful to have a descriptive title for your dataset or code.