Semantic Situation Reporting Mechanism Based on 4W'H Ontology Modeling in Battlefield

Main Article Content

Naeem Iqbal
Murad Ali Khan
Atif Rizwan
Do-Hyeun Kim

Abstract

 Recently, semantic ontologies have been considered essential in knowledge representation systems to form interactive user-centric query systems. Therefore, it is gaining significant importance in the battlefield situations domain to offer several services to military officials; for example, it enables military officials to deduce battlefield situations information to drive effective decisions in a short time during tactics. This paper presents a battlefield ontology based on a 4W'H architecture using battlefield terms to enhance the existing Army Tactical Command Information System (ATCIS) to intelligent ATCIS. Furthermore, we used a well-known ontology editor known as Protégé to design an ontology to report battlefield situations semantically and effectively. In addition, a use case is defined in order to reveal the effectiveness of the designed semantic ontology-based on 4W'H architecture.

Article Details

How to Cite
Iqbal, N., Khan, M. A., Rizwan, A., & Kim, D.-H. (2022). Semantic Situation Reporting Mechanism Based on 4W’H Ontology Modeling in Battlefield. Journal of Intelligent Pervasive and Soft Computing, 1(01), 25–31. Retrieved from https://scirep.institute/journals/index.php/jipsc/article/view/3
Section
Computer Science and Multidisciplinary research
Author Biography

Naeem Iqbal, Department of Computer Engineering, Jeju National University, Jeju-si 63243, Korea

Image of author Naeem Iqbal

Naeem Iqbal received the B.S. and M.S. degrees in computer science from COMSATS University Islamabad, Attock Campus, Punjab, Pakistan, in 2019. He is currently pursuing the Ph.D. degree with the Department of Computer Engineering, Jeju National University, Republic of Korea. He has professional experience in the software development industry and in academic as well. His research work mainly focused on AI-based intelligent systems, data science, big data analytics, machine learning, deep learning, analysis of optimization algorithms, the IoT, and blockchain-based secured applications. He has published more than 20 papers in peer-reviewed international journals and conferences. He is serving as a professional reviewer for various well-reputed journals and conferences.

References

Gómez-Pérez, A., & Corcho, O. (2002). Ontology languages for the semantic web. IEEE Intelligent systems, 17(1), 54-60.

Paton, N. W., Stevens, R., Baker, P., Goble, C. A., Bechhofer, S., & Brass, A. (1999, July). Query processing in the TAMBIS bioinformatics source integration system. In Proceedings. Eleventh International Conference on Scientific and Statistical Database Management (pp. 138-147). IEEE.

Meštrović, A., & Calì, A. (2016, September). An ontology-based approach to information retrieval. In Semanitic Keyword-based Search on Structured Data Sources (pp. 150-156). Springer, Cham.

Ramli, F., Noah, S. A., & Kurniawan, T. B. (2016, August). Ontology-based information retrieval for historical documents. In 2016 Third International Conference on Information Retrieval and Knowledge Management (CAMP) (pp. 55-59). IEEE.

Munir, K., & Anjum, M. S. (2018). The use of ontologies for effective knowledge modelling and information retrieval. Applied Computing and Informatics, 14(2), 116-126.

Gruber, T. R. (1993). A translation approach to portable ontology specifications. Knowledge acquisition, 5(2), 199-220.

Xu, Z., Zhang, S., & Dong, Y. (2006, December). Mapping between relational database schema and OWL ontology for deep annotation. In 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings) (WI'06) (pp. 548-552). IEEE.

Trinkunas, J., & Vasilecas, O. (2007, June). Building ontologies from relational databases using reverse engineering methods. In Proceedings of the 2007 international conference on Computer systems and technologies (pp. 1-6).

Zhou, S., Ling, H., Han, M., & Zhang, H. (2010). Ontology Generator from Relational Database Based on Jena. Computer and Information Science, 3(2), 263-267.

Cullot, N., Ghawi, R., & Yétongnon, K. (2007, June). Db2owl: a tool for automatic database-to-ontology mapping. In SEBD (Vol. 7, pp. 491-494).

Van Der Vet, P. E., & Mars, N. J. (1998). Bottom-up construction of ontologies. IEEE Transactions on Knowledge and data Engineering, 10(4), 513-526.

Schreiber, G., Wielinga, B., & Jansweijer, W. (1995, August). The KACTUS view on the 'O'word. In IJCAI workshop on basic ontological issues in knowledge sharing (pp. 159-168).

López-Pellicer, F. J., Vilches-Blázquez, L. M., Nogueras-Iso, J., Corcho, O., Bernabé, M. A., & Rodríguez, A. F. (2007, October). Using a hybrid approach for the development of an ontology in the hydrographical domain. In Proceedings of 2nd Workshop of COST Action C21-Towntology Ontologies for urban development: conceptual models for practitioners.

Ra, M., Yoo, D., No, S., Shin, J., & Han, C. (2012, March). The mixed ontology building methodology using database information. In Proceedings of the International MultiConference of Engineers and Computer Scientists (Vol. 1).

Ra, M., Yoo, D., & No, S. (2013, June). Construction and applicability of military ontology for semantic data processing. In Proceedings of the 3rd International Conference on Web Intelligence, Mining and Semantics (pp. 1-7).

Ra, M., Yoo, D., No, S., Shin, J., & Han, C. (2013, February). Constructing a Military Ontology According to the Mixed Ontology Building Methodology. In Proceedings of the 5th International Conference on Computer Research and Development (ICCRD 2013), Vietnam.

Yoo, D., No, S., & Ra, M. (2014). A practical military ontology construction for the intelligent army tactical command information system. International Journal of Computers Communications & Control, 9(1), 93-100.

Matheus, C. J., Kokar, M. M., & Baclawski, K. (2003, July). A core ontology for situation awareness. In Proceedings of the Sixth International Conference on Information Fusion (Vol. 1, pp. 545-552).

Song, S., Ryu, K., & Kim, M. (2010, May). Ontology-based decision support for military information systems. In 2010 IEEE Long Island Systems, Applications and Technology Conference (pp. 1-5). IEEE.

Feng, Y. H., Teng, T. H., & Tan, A. H. (2009). Modelling situation awareness for Context-aware Decision Support. Expert Systems with Applications, 36(1), 455-463.

Song, J., Jun, D., & Wang, S. H. (2003). Analysing web ontology in Alloy: A military case study.

Chmielewski, M. (2009, October). Ontology applications for achieving situation awareness in military decision support systems. In International Conference on Computational Collective Intelligence (pp. 528-539). Springer, Berlin, Heidelberg.

Valente, A., Holmes, D., & Alvidrez, F. C. (2005, March). Using a military information ontology to build semantic architecture models for airspace systems. In 2005 IEEE Aerospace Conference (pp. 1-7). IEEE.

Bowyer, R. (2015). Dictionary of Military Terms: Over 6,000 words clearly defined. Bloomsbury Publishing.

Gortney, W. E. (2012). Dictionary of Military and Associated Terms.

Bock, J., Tserendorj, T., Xu, Y., Wissmann, J., & Grimm, S. (2009, October). A Reasoning Broker Framework for OWL. In OWLED.