Provenance Data Models and Assertions:
A Demonstrative Approach
Rajiv Pandey and Mrinal Pande
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.
Keywords Provenance · Scenario-based assertions · Semantic IoT ·
Interoperability · Ontology · Semantic web
1 Introduction
The Semantic Web since its inception has come a long way. Most of the ontologies and
sematic models that have been proposed are limited to vocabulary confirmations. The
R. Pandey (B)
Amity Institute of Information Technology,
Amity University Uttar Pradesh Lucknow Campus, Lucknow, India
e-mail: rpandey@lko.amity.edu
M. Pande
AIIT, Amity University Lucknow Campus, Lucknow, India
e-mail: mrinalkidak@gmail.com
© Springer Nature Switzerland AG 2021
R. Pandey et al. (eds.), Semantic IoT: Theory and Applications, Studies in Computational
Intelligence 941, https://doi.org/10.1007/978-3-030-64619-6_5
103
A Demonstrative Approach
Rajiv Pandey and Mrinal Pande
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.
Keywords Provenance · Scenario-based assertions · Semantic IoT ·
Interoperability · Ontology · Semantic web
1 Introduction
The Semantic Web since its inception has come a long way. Most of the ontologies and
sematic models that have been proposed are limited to vocabulary confirmations. The
R. Pandey (B)
Amity Institute of Information Technology,
Amity University Uttar Pradesh Lucknow Campus, Lucknow, India
e-mail: rpandey@lko.amity.edu
M. Pande
AIIT, Amity University Lucknow Campus, Lucknow, India
e-mail: mrinalkidak@gmail.com
© Springer Nature Switzerland AG 2021
R. Pandey et al. (eds.), Semantic IoT: Theory and Applications, Studies in Computational
Intelligence 941, https://doi.org/10.1007/978-3-030-64619-6_5
103