Open AccessOWL2 benchmarking for the evaluation of knowledge based systems
Author(s) -
Sher Afgun Khan,
Muhammad Abdul Qadir,
Muhammad Azeem Abbas,
Muhammad Afzal
Publication year - 2017
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0179578
Subject(s) - benchmarking , computer science , benchmark (surveying) , scalability , knowledge base , semantics (computer science) , subject matter expert , workload , domain (mathematical analysis) , ontology , artificial intelligence , domain knowledge , data mining , information retrieval , machine learning , database , expert system , programming language , mathematical analysis , philosophy , mathematics , geodesy , epistemology , marketing , business , geography , operating system
OWL2 semantics are becoming increasingly popular for the real domain applications like Gene engineering and health MIS. The present work identifies the research gap that negligible attention has been paid to the performance evaluation of Knowledge Base Systems (KBS) using OWL2 semantics. To fulfil this identified research gap, an OWL2 benchmark for the evaluation of KBS is proposed. The proposed benchmark addresses the foundational blocks of an ontology benchmark i.e. data schema, workload and performance metrics. The proposed benchmark is tested on memory based, file based, relational database and graph based KBS for performance and scalability measures. The results show that the proposed benchmark is able to evaluate the behaviour of different state of the art KBS on OWL2 semantics. On the basis of the results, the end users (i.e. domain expert) would be able to select a suitable KBS appropriate for his domain.