Chapter

Advances in Conceptual Modeling – Applications and Challenges

Volume 6413 of the series Lecture Notes in Computer Science pp 54-64

Provenance Management in BioSciences

  • Sudha RamAffiliated withCarnegie Mellon UniversityDepartment of MIS, Eller School of Management, University of Arizona
  • , Jun LiuAffiliated withCarnegie Mellon UniversityDepartment of MIS, Eller School of Management, University of Arizona

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Abstract

Data provenance is becoming increasingly important for biosciences with the advent of large-scale collaborative environments such as the iPlant collaborative, where scientists collaborate by using data that they themselves did not generate. To facilitate the widespread use and sharing of provenance, ontologies of provenance need to be developed to enable the capture and standardized representation of provenance for biosciences. Working with researchers from the iPlant Tree of Life (iPToL) Grand Challenge Project, we developed a domain ontology of provenance for phylogenetic analysis. Relying on the conceptual graph formalism, we describe the process of developing the provenance ontology based on the W7 model, a generic ontology of data provenance. This domain ontology provides a structured model for harvesting, storing and querying provenance. We also illustrate how the harvested data provenance based on our ontology can be used for different purposes.

Keywords

Provenance tree of life W7 model conceptual graphs