Collective ontology alignment

Enterprises are captivated by the promise of using big data to develop new products and services that provide new insights into their customers and businesses. However, there are significant challenges leveraging data across heterogeneous data stores, including making those data accessible and usable by non-experts. We designed a novel system called Helix which employs a combination of userdriven and automated techniques to bootstrap the building of a unified semantic model over virtualized data. Such a uniform semantic model allows users to query across data stores transparently, without needing to navigate a maze of data silos, data formats, and query languages. In this poster, we discuss a specific aspect of Helix: the method by which it facilitates ontology alignment. Such alignments are very noisy and manually fixing the issues is a laborious process, especially when all the work must be done prior to putting the system into use. Instead, Helix proposes to engage users progressively in the process of ontology alignment through the course of their everyday use of the system. We do this by framing ontology alignment as a guided data exploration and integration task.