Enabling Trust in an E-Learning Ontology Through Provenance

Author:

Pandey Rajiv1ORCID,Srivastava Nidhi1,Bajpai Amit Kumar2

Affiliation:

1. Amity University, Lucknow, India

2. UPTEC, India

Abstract

E-learning is the acquisition and application of knowledge that is primarily provided and assisted through electronic means. Ontology is the pillar on which the semantic web stands. They provide a common framework for organizing and sharing knowledge, making it easier for machines to process and make inferences from data. The proliferation of online content has made it increasingly difficult to differentiate between true and false information. This underscores the importance of evaluating the credibility of documents within the semantic web. Provenance can help in this as it refers to a collection of records that shed light on the activities, participants, and entities involved in creating, updating, and utilizing web-based data. In this chapter, the authors have used PROV-DM model to add provenance to our academic ontology which will help in building trust. The system generates effective decision and trustworthiness results, supporting users in retrieving authentic and up-to-date information.

Publisher

IGI Global

Reference11 articles.

1. Butt, A. (2021). A provenance model for control-flow driven scientific workflows. Data & Knowledge Engineering.

2. Obitko, M. (2007). Frame Based Models. https://www.obitko.com/tutorials/ontologies-semantic-web/frame-based-models.html

3. Provenance Constraints and Attributes Definition in OWL Ontology to Support Machine Learning

4. JSON and its use in Semantic Web

5. PandeyR. (2021). Provenance Data Models and Assertions: A Demonstrative Approach. Springer.

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