Scientific provenance metadata capture and management using Semantic Web

Abstract

Providing historical scientific information to deal with knowledge loss about scientific experiment is a strategical question in scientific research. One key aspect is the reuse of generated knowledge. Provenance data, extracted from multiple sources, must be reused in order to provide strategical information for scientists, including also inferred information based on these data. SciProv consists of an architecture that aims to interact with Scientific Workflow Management Systems SWfMS for capturing and managing provenance metadata. This work adopts an approach based on a standard model to represent the lineage and to handle distributed and heterogeneous provenance metadata. Using ontologies and inference engines, SciProv provides resources to make inferences about provenance data and to obtain important results considering the extraction of information beyond those that are explicitly registered. The paper also presents proof of concept in bioinformatics domain.