On Modeling and Querying Concept Evolution

Entities and the concepts they instantiate evolve over time. For example, a corporate entity may have resulted from a series of mergers and splits, or a concept such as that of Whale may have evolved along with our understanding of the physical world. We propose a model for capturing and querying concept evolution. Our proposal extends an RDF-like model with temporal features and evolution operators. In addition, we provide a query language that exploits these extensions and supports historical queries. Moreover, we study how evolution information can be exploited to answer queries that are agnostic to evolution details (hence, evolution-unaware). For these, we propose dynamic programming algorithms and evaluate their efficiency and scalability by experimenting with both real and synthetic datasets.