Provenance Data Models and Assertions: A Demonstrative Approach

Part of the Studies in Computational Intelligence book series (SCI, volume 941)


Provenance as perceived is a trail of a piece of a data item that helps in linking derived pieces of web resources or Internet of Everything (IoE) data to its creators. Provenance allows the software agents and developers to assert that devices across the IoE landscape can be made trustworthy if the same has a valid derivation path that is associated with it and is reliable/trustworthy. Provenance is considered as metadata that must be embedded into an OWL ontology, this metadata supports the semantic agents/reasoners to evaluate the data or workflow trail of the item in question. Contemporary researchers have proposed several models of trust that are based on mathematical calculations, however, the implementation of trust on semantically generated and modified documents i.e. ontologies at large is still evolving. This chapter thus aims to discuss, deliberate, and implement trust in an existing ontology using provenance assertions. This implementation of trust is based on the PROV-DM (Data Model) that has been suggested by the World Wide Web consortium. The chapter illustrates the implementation and inferencing of trust embedded in an OWL-based University Ontology. Provenance assertions using various scenarios and their inference have been highlighted to signify the validity and consistency of the ontology an XML serialized dataset.


Provenance Scenario-based assertions Semantic IoT Interoperability Ontology Semantic web 


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© Springer Nature Switzerland AG 2021

Authors and Affiliations

  1. 1.Amity Institute of Information TechnologyAmity University Uttar Pradesh Lucknow CampusLucknowIndia
  2. 2.AIIT, Amity University Lucknow CampusLucknowIndia

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