52
J. R. Prasad et al.
In paper [10] authors have created reliable semantic web by exploiting provenance assertions and have also provided the mechanism to verify this trust ability
using provenance of provenance descriptions. PROV-DM data model is used for
deployment. In this paper provenance is created using the concept of entity, agent and
activity and these provenance descriptions are connected to each other via Bundle and
Mentionof concepts using Prov-store tool for University people program ontology
application. Authors have demonstrated that to render the trustworthiness of document provenance of provenance must be ensured and this can be effectively accomplished with the help of Bundles data structure. Also Mentionof relation offers the
opportunities to stitch provenance definitions provided by one group to be utilized
by another group.
Pandey et al. describes action research methodology using OWL functional syntax
[11] and using XML/OWL syntax in Protégé [12] to add provenance to Amity university program ontology. This provenance is confirmed using Hermit Reasoner. Provenance allows processes to be reproduced, and also provides new reasoning information. There, authors explored how interactions between activities, entities, and
agents are interested in constructing new entities from the initial by the use of their
ontology at the university. They showed the procedures for forming, embedding and
reasoning provenance in relation to their Ontology, and also claimed that it can also
be used effectively in other applications.
6 Semantic Web Implementations and Applications
6.1 Software Agents
More effective work communication is possible between human users and machines
by using semantic web and agents. In order to facilitate automatic web discovery
based on customization of user requests, users’ constraints and preferences are used
by semantic web. Software agents have been defined as prospective customers of
semantic web services in order to communicate with semantic SWS specifications
in order to independently find, search, write, activate and execute services based on
user requirements. There is, though, a communication gap between the two. AgentWeb gateway is an initiative for dynamic and seamless interoperation of multi agent
systems and Web services [13]. By taking into consideration engineering student’s
learning preferences and their specific needs one framework is proposed by authors
in [14]. This system is useful for personalized learning and can be thought of as a
concept of a tailored intelligent multi-agent learning system. Authors used Semantic
Web, Ontologies, recommender system and Intelligent Software Agents for its development. In [15] test environment that is intended to support e-learning in software
engineering education is discussed in which automatic questions generation is done
by software agents using ontologies.
J. R. Prasad et al.
In paper [10] authors have created reliable semantic web by exploiting provenance assertions and have also provided the mechanism to verify this trust ability
using provenance of provenance descriptions. PROV-DM data model is used for
deployment. In this paper provenance is created using the concept of entity, agent and
activity and these provenance descriptions are connected to each other via Bundle and
Mentionof concepts using Prov-store tool for University people program ontology
application. Authors have demonstrated that to render the trustworthiness of document provenance of provenance must be ensured and this can be effectively accomplished with the help of Bundles data structure. Also Mentionof relation offers the
opportunities to stitch provenance definitions provided by one group to be utilized
by another group.
Pandey et al. describes action research methodology using OWL functional syntax
[11] and using XML/OWL syntax in Protégé [12] to add provenance to Amity university program ontology. This provenance is confirmed using Hermit Reasoner. Provenance allows processes to be reproduced, and also provides new reasoning information. There, authors explored how interactions between activities, entities, and
agents are interested in constructing new entities from the initial by the use of their
ontology at the university. They showed the procedures for forming, embedding and
reasoning provenance in relation to their Ontology, and also claimed that it can also
be used effectively in other applications.
6 Semantic Web Implementations and Applications
6.1 Software Agents
More effective work communication is possible between human users and machines
by using semantic web and agents. In order to facilitate automatic web discovery
based on customization of user requests, users’ constraints and preferences are used
by semantic web. Software agents have been defined as prospective customers of
semantic web services in order to communicate with semantic SWS specifications
in order to independently find, search, write, activate and execute services based on
user requirements. There is, though, a communication gap between the two. AgentWeb gateway is an initiative for dynamic and seamless interoperation of multi agent
systems and Web services [13]. By taking into consideration engineering student’s
learning preferences and their specific needs one framework is proposed by authors
in [14]. This system is useful for personalized learning and can be thought of as a
concept of a tailored intelligent multi-agent learning system. Authors used Semantic
Web, Ontologies, recommender system and Intelligent Software Agents for its development. In [15] test environment that is intended to support e-learning in software
engineering education is discussed in which automatic questions generation is done
by software agents using ontologies.