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.


Provenance tree of life W7 model conceptual graphs 


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  1. 1.
    Simmhan, Y., Plale, B., Gannon, D.: A Survey of Data Provenance Techniques, Indiana University, Technical Report IUB-CS-TR618 (2005)Google Scholar
  2. 2.
    Moreau, L., Freire, J., Futrelle, J., McGrath, R.E., Myers, J., Paulson, P.: The Open Provenance Model: An Overview. In: Freire, J., Koop, D., Moreau, L. (eds.) IPAW 2008. LNCS, vol. 5272, pp. 323–326. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  3. 3.
    Ram, S., Liu, J.: Understanding the Semantics of Data Provenance to Support Active Conceptual Modeling. In: Chen, P.P., Wong, L.Y. (eds.) ACM-L 2006. LNCS, vol. 4512, pp. 17–29. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  4. 4.
    Ram, S., Liu, J.: A New Perspective on Semantics of Data Provenance. Presented at the First International Workshop on the Role of Semantic Web in Provenance Management, Washington D.C., (2009)Google Scholar
  5. 5.
    Sowa, J.: Conceptual structures: Information processing in Mind and Machine. Addison-Wesley, Reading (1984)MATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Sudha Ram
    • 1
  • Jun Liu
    • 1
  1. 1.Department of MIS, Eller School of ManagementUniversity of ArizonaTucsonUSA

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