Non-temporal orderings as proxies for extensional concept drift

Abstract

In census data, concepts are central entities represented by variables and their values. The meaning of these concepts is often assumed to be stable, but in fact it can change over time: we call this concept drift. Extensional concept drift is one type of change of meaning that affects the things the concept extends to, having drastic consequences on longitudinal querying. In this paper we detect extensionally drifted concepts in current Linked Census Data when a time ordering of such concepts is not available. We exploit the Linked Data cloud to obtain meaningful proxies for such orderings.