Ontology-based registration of entities for data integration in large biomedical research projects

Abstract

Large biomedical projects often include workflows running across institutional borders. In these workflows, data describing biomedical entities, such as patients, bio-materials but also processes itself, is typically produced, modified and analyzed at different locations and by several systems. Therefore, both tracking entities within inter-organizational workflows and data integration are often crucial steps. To address these problems, we centrally register entities and their relationships by using a multi-layered model. The model utilizes an ontology and a typed system graph to semantically describe and classify entities and their relationships but also to access entity data on demand in their original source. Moreover, this integration approach allows to centrally track entities along the project workflows and can be used in explorative data analyses as well as by other data integration approaches using the registered entity relationships. We describe the model, the utilized ontology, and a system implementing this approach, which is applied in a large biomedical research project.