Data Management and Ontology Development for Provenance-Aware Organizations in Linked Data Space

Year 2023, , 130 - 141, 31.12.2023

Fatih Soygazi , Tuğkan Tuğlular , Oğuz Dikenelli

https://doi.org/10.36222/ejt.1402149

Abstract

The need to track the origin of shared data/datasets has become apparent, highlighting the necessity of monitoring factors such as trust related to the data/datasets with the widespread use of social media. The concept of Linked Data Space needs to be considered in conjunction with organizations and their provenance with respect to their origin assuming that the shared data is semantic and considering organizations' access to relevant semantic data. In this context, this study elaborates on the concept of Linked Data Space, introducing the terms Internal Data and External Data to the literature. An architecture for Linked Data Space and data management for organizations is defined in addition to these concepts. Furthermore, the study explains how organizations can access External Data in the Linked Data Space and how provenance metadata and ontologies will be created. These developed methods are illustrated in the News Aggregator Scenario, a main scenario for provenance, demonstrating how it can work in a use case.

Keywords

Linked data space, Organization, Ontology, VoID, Metadata

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