Automatic Mapping of Quranic Ontologies Using RML and Cellfie Plugin

EasyChair Preprint 7860

Abstract

The text of the Qur’an has been analysed, segmented and annotated by linguists and religious scholars, using a range of represen- tations and formats, Quranic resources in different scopes and formats can be difficult to link due to their complexity. Qur’an segmentation and annotation can be represented in a heterogeneous structure (e.g., CSV, JSON, and XML). However, there is the lack of a standardised mapping formalisation for the data. For this reason, this study’s motivation is to link morphological segmentation tags and syntactic analyses, in Arabic and Buckwalter forms, to the Hakkoum ontology to enable further clar- ification of the Qur’an. For achieving this aim, the paper combines two mapping methods: the RDF (resources description framework) mapping language, which is an R2RML extension (the W3C level necessary when mapping relational databases into RDF), and Cellfie plugin, which is a part of the Protégé system. The proposed approach provides the possi- bility to automatically map and merge the heterogeneous data sources into an RDF data model. Also, the integrated ontology is evaluated by a SPARQL query using an Apache Jena Fuseki server. This experiment was conducted in all the Qur’an chapters and verses, containing all the words and segments of the entire Qur’an corpus.

Keyphrases: Cellfie plugin, Classical Islamic Text, RML, heterogeneous data, ontology integration, ontology mapping

@booklet{EasyChair:7860,
  author    = {Ibtisam Khalaf Alshammari and Eric Atwell and Mohammad Ammar Alsalka},
  title     = {Automatic Mapping of Quranic Ontologies Using RML and Cellfie Plugin},
  howpublished = {EasyChair Preprint 7860},
  year      = {EasyChair, 2022}}