Data Reuse Fitness Assessment Using Provenance

<p>Assessing the fitness of data for reuse may require knowledge of how that data was produced. If knowledge of how data is produced can be represented using a standard data model, automated assessments of data fitness may take place, based on aspects of its production. In addition to knowledge of data's production, knowledge of how it has or hasn't been used can also be used to assess its fitness for further reuse. <p>Since 2014 we have had an international data model for representing data's production, namely the W3C's provenance data model, PROV-DM. It can also be used to represent how data has been used which is known as 'forward provenance'. <p>Here we present several types of provenance queries one may pose in order to assess data's fitness for reuse. These include discovering the methods used in data production; determining the reputation of ancestor data; determining the reputation of agents (human or machine) involved in data production; and assessing the social acceptance of data via its reported use which we believe to be the best form of social endorsement for data's utility.