The dynamic nature of web data brings forward the need for maintaining data versions as well as identifying changes between them. In this paper, we deal with problems regarding understanding evolution, focusing on RDF(S) knowledge bases, as RDF is a de-facto standard for representing data on the web. We argue that revisiting past snapshots or the differences between them is not enough for understanding how and why data evolved. Instead, changes should be treated as first-class-citizens. In our view, this involves supporting semantically rich, user-defined changes that we call complex changes, as well as identifying the interrelations between them. In this paper, we present our perspective regarding complex changes, propose a declarative language for defining complex changes for RDF(S) knowledge bases, and show how this language is used to detect complex change instances among dataset versions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.