Provenance management in BioSciences

Sudha Ram, Jun Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationAdvances in Conceptual Modeling - Applications and Challenges, ER 2010 Workshops ACM-L, CMLSA, CMS, DE@ER, FP-UML, SeCoGIS, WISM, Proceedings
Number of pages11
StatePublished - 2010
Event29th International Conference on Conceptual Modeling, ER 2010 - Vancouver, BC, Canada
Duration: Nov 1 2010Nov 4 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6413 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other29th International Conference on Conceptual Modeling, ER 2010
CityVancouver, BC


  • Provenance
  • W7 model
  • conceptual graphs
  • tree of life

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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