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Provenance Data Models and Assertions: A Demonstrative Approach

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Semantic IoT: Theory and Applications

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

Abstract

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.

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Author information

Authors and Affiliations

  1. Amity Institute of Information Technology, Amity University Uttar Pradesh Lucknow Campus, Lucknow, India

    Rajiv Pandey

  2. AIIT, Amity University Lucknow Campus, Lucknow, India

    Mrinal Pande

Authors
  1. Rajiv Pandey
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  2. Mrinal Pande
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Corresponding author

Correspondence to Rajiv Pandey .

Editor information

Editors and Affiliations

  1. Amity Institute of Information Technology, Amity University Uttar Pradesh Lucknow Campus, Lucknow, Uttar Pradesh, India

    Rajiv Pandey

  2. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Marcin Paprzycki

  3. Amity Institute of Information Technology, Amity University Uttar Pradesh Lucknow Campus, Lucknow, Uttar Pradesh, India

    Nidhi Srivastava

  4. Database System Laboratory, University of Aizu, Aizu-Wakamatsu, Fukushima, Japan

    Subhash Bhalla

  5. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Katarzyna Wasielewska-Michniewska

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Pandey, R., Pande, M. (2021). Provenance Data Models and Assertions: A Demonstrative Approach. In: Pandey, R., Paprzycki, M., Srivastava, N., Bhalla, S., Wasielewska-Michniewska, K. (eds) Semantic IoT: Theory and Applications. Studies in Computational Intelligence, vol 941. Springer, Cham. https://doi.org/10.1007/978-3-030-64619-6_5

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