Why is change discovery important for open data?

by

Lost Boy

Change discovery is the process of identifying changes to a resource. For example, that a document has been updated. Or, in the case of a dataset, whether some part of the data has been amended, e.g. to add data, fill in missing values, or correct existing data. If we can identify that changes have been made to a dataset, then we can update our locally cached copies, re-run analyses or generate new, enriched versions of the original.

Any developer who is building more than a disposable prototype will be looking for information about the ongoing stability and change frequency of a dataset. Typical questions might be:

  • How often will a dataset get routinely updated and republished?
  • What types of data updates are anticipated? E.g. are only new records added, or might data be amended and removed?
  • How will the dataset, or parts of it be version controlled?
  • How will changes…

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