Conceptual structures: information processing in mind and machine
Conceptual structures: information processing in mind and machine
The Open Provenance Model: An Overview
Provenance and Annotation of Data and Processes
Understanding the semantics of data provenance to support active conceptual modeling
Active conceptual modeling of learning
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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.