This example is to show techniques for identifying personal data and special category data. It uses Quickforms and JavaScript views to surface the informaiton and to capture the decisions made. If special category data is identified then a simple linear correlation is run to see if there is any strong correlation to any of the other data - if so, this might be an indication that we should also look at that data. A decision can be made and will be documented as to whether special category fields as well as any other fields correlated to that field should be kept or deleted. Information about the workflow and its context information (who wrote it, when, etc.) as well as detailed statistics about the data and the decisions made about that data are captured. The interactive wrapped metanodes (identify PII and Special Category Fiels, Identify Pseudo Special Category Fields and Decide in Inclusion) can be run either on the KNIME Analytics Platform (ie on the desktop) or can be used with the KNIME Server and the KNIME Web Portal.
This is a companion discussion topic for the original entry at https://kni.me/w/3-Um4jZswQLFM3JI