Proposing an Integrated Multi Source Ontology Construction Methodology

Document Type : Semantic Technology-Kahani

Authors

1 Iranian Research Institute for Information Science and Technology (IRANDOC), Tehran, Iran.

2 Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.

Abstract

The goal of this research is to create a reference data model for educational and research institutes of Iranian Ministry of Sciences, Research, and Technology. After investigating existing technologies and considering the problem context, ontology was chosen as the data model format. In order to create the target ontology, an ontology construction methodology was designed and implemented. This methodology is created using design science research method and contains an architecture, a detailed workflow process, a guideline for performing 1each step, and related softwares in an integrated web-based system. The designed system is implemented in PHP and is available as open source. The system is used as the main tool to construct the target ontology. The proposed methodology leverages the three main knowledge sources including textual documents, existing ontologies in the higher education domain, and reverse engineering of a relational database of an integrated university system. The resulted product of this methodology was evaluated based on the data requirements of the Ministry of Sciences, Research, and Technology, and its shortcomings were resolved. The novelty of this work is both on the generated product, that is, a localized reference data model, and an ontology construction methodology.

Keywords


[1] T. R. Gruber, “Toward principles for the design of ontologies used for knowledge sharing,” International journal of human-computer studies, vol. 43, no. 5-6, pp. 907-928, 1995
[2] N. Guarino, D. Oberle, and S. Staab, “What is ontology?” In Handbook, Handbook on ontologies. Springer, Heidelberg, Berlin, pp. 1-17, 2009.
[3] A. Zouaq, D. Gasevic and M. Hatala, “Towards open ontology learning and filtering,” Information Systems, vol. 36, no. 7, pp. 1064-1081, 2011.
[4] C. V. Satyamurty, J. V. Murthy and M. Raghava, “Developing Higher Education Ontology Using Protégé Tool: Reasoning,” In Smart Computing and Informatics,” Springer , Singapore, pp. 233-241, 2018.
[5] K. Hadjar, “University Ontology: A Case Study at Ahlia University,” In Semantic Web, Springer, Cham, pp. 173-183, 2016.
[6] M. Uschold and M. Gruninger, “Ontologies: Principles, methods and applications,” The Knowledge Engineering Review, vol. 11, no. 2, pp. 93-136, 1996.
[7] L. Zemmouchi-Ghomari and A. R. Ghomari, “Process of Building Reference Ontology for Higher Education,” In Proceedings of the World Congress on Engineering vol. 3, WCE, London, U.K., pp. 1595-1600, 2013.
[8] M. C. Suarez-Figueroa, “NeOn methodology for building ontology networks: Specification, scheduling and reuse (Doctoral dissertation),” Univ. Politécnica, Madrid, 2010.
[9] A. Ameen, K. R. Khan and B. P. Rani. “Construction of university ontology,” In Information and Communication Technologies (WICT), 2012 World Congress, IEEE, Trivandrum, India, pp. 39-44, 2012.
[10] S. K. Malik, N. Prakash and S. A. Rizvi, “Developing an university ontology in education domain using protégé for semantic web,” International Journal of Science and Technology, vol. 2, no. 9, pp. 4673-4681, 2010.
[11] A. Gomez-Perez, M. Fernández-López and O. Corcho, “Ontological engineering: With examples from the areas of Knowledge Management, e-Commerce and the Semantic Web,” Springer Science & Business Media, 2006.
[12] M. Fernández-López, A. Gómez-Pérez and N. Juristo, “Methontology: from ontological art towards ontological engineering”, Univ. Politécnica, Madrid, 1997.
[13] M. Grüninger and M. S. Fox, “Methodology for the design and evaluation of ontologies”. in Proc. of the Workshop on Basic Ontological Issues in Knowledge Sharing, IJCAI-95 , Montreal, 1995.
[14] N. F. Noy and D. L. McGuinness, “Ontology development 101: A guide to creating your first ontology,” Stanford University, Stanford, CA, 2001.
[15] H. S. Pinto, C. Tempich and S. Staab, “Ontology engineering and evolution in a distributed world using DILIGENT,” In Handbook on ontologies, Springer-Verlag, Berlin, Heidelberg, pp. 153-176, 2009.
[16] A. De Nicola, M. Missikoff and R. Navigli, “A software engineering approach to ontology building”. Information Systems, vol. 34, no. 2, pp. 258-275, 2009.
[17] Y. Sure, S. Staab and R. Studer, “On-to-knowledge methodology (OTKM),” In Handbook on ontologies, Springer, Berlin, Heidelberg, pp. 117-132, 2004.
[18] V. K. Vaishnavi and W. Kuechler, “Design science research methods and patterns: innovating information and communication technology”. Crc Press, New York, 2015.
[19] A. Zouaq and R. Nkambou, “A survey of domain ontology engineering: methods and tools,” In Advances in intelligent tutoring systems, Springer, Berlin Heidelberg, pp. 103-119, 2010.
[20] C. Sammut and G. I. Webb, Encyclopedia of Machine Learning, Springer, Boston, MA, 2011.
[21] P. Cimiano, “Ontology Learning and Population from Text Algorithms: Evaluation and Applications,” Springer-Verlag, New York, USA, 2006.
[22] D. E. Spanos, P. Stavrou and N. Mitrou, “Bringing relational databases into the semantic web: A survey,” Semantic Web, vol. 3, no. 2, pp. 169-209, 2012.
[23] T. Berners-Lee, “Relational databases and the semantic web (in design issues),” World Wide Web Consortium, https://www.w3.org/DesignIssues/RDB-RDF.html, 1998.
[24] B. El Idrissi, S. Baïna and K. Baïna, “A methodology to prepare real-world and large databases to ontology learning,” Enterprise Interoperability VI, Springer, pp. 175-185, 2014
[25] G. Shen, Z. Huang, X. Zhu and X. Zhao, “Research on the Rules of Mapping from Relational Model to OWL,” In Proceedings of the OWLED’06 Workshop on OWL: Experiences and Directions, Athens, GA, USA, 2006.
[26] R. Ghawi and N. Cullot, “Database-to-ontology mapping generation for semantic interoperability,” VDBL’07 conference, VLDB Endowment, ACM, Vienna, Austria, pp. 1-8, 2007.
[27] S. H. Tirmizi, J. Sequeda and D. Miranker, “Translating sql applications to the semantic web,” International Conference on Database and Expert Systems Applications, Springer, Berlin, Heidelberg, pp. 450-464, 2008.
[28] F. Cerbah, “Mining the content of relational databases to learn ontologies with deeper taxonomies,” IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology-Volume 01, IEEE Computer Society, Sydney, NSW, Australia, pp. 553-557, 2008.
[29] N. Alalwan, H. Zedan and F. Siewe, “Generating OWL ontology for database integration,” Advances in Semantic Processing, SEMAPRO'09. Third International Conference. IEEE, Sliema, Malta, pp. 22-31, 2009.
[30] L. Lubyte and S. Tessaris, “Automatic extraction of ontologies wrapping relational data sources,” International Conference on Database and Expert Systems Applications, Springer, Berlin, Heidelberg, pp. 128-142, 2009.
[31] K. M. Albarrak and E. H. Sibley, “Translating relational & object-relational database models into OWL models,” Information Reuse & Integration, 2009. IRI'09. IEEE International Conference, Las Vegas, NV, USA, pp. 336-341, 2009.
[32] I. Astrova, “Rules for mapping SQL relational databases to OWL ontologies,” In Metadata and Semantics, Springer, Boston, MA, pp. 415-424, 2009.
[33] P. Liu, X. Wang, A. Bao and X. Wang, “Ontology automatic constructing based on relational database,” Grid and Cooperative Computing (GCC), 2010 9th International Conference, IEEE, Nanjing, China, pp. 412-415, 2010.
[34] H. A. Santoso, S. C. Haw and Z. T. Abdul-Mehdi, “Ontology extraction from relational database: Concept hierarchy as background knowledge,” Knowledge-Based Systems, vol. 24, no. 3, pp. 457-464, 2011
[35] S. Khan, K. Sonia, “R2o: Relation to ontology transformation system,” Journal of Information & Knowledge Management, vol. 10, no. 01, pp. 71-89, 2011.
[36] B. Blobel, “Conceptual Model Formalization in a Semantic Interoperability Service Framework: Transforming Relational Database Schemas to OWL,” 11th International Conference on Wearable Micro and Nano Technologies for Personalized Health, IOS Press , Vienna, Austria, p. 35, 2014.
[37] A. Kaulins and A. Borisov, “Building Ontology from Relational Database,” Information Technology and Management Science, vol. 17, no. 1, pp. 45-49, 2014.
[38] I. Zarembo, “Automatic Transformation of Relational Database Schema into OWL Ontologies,” International Scientific and Practical Conference (Vol. 3), Rezekne, Latvia, pp. 217-222, 2015.
[39] K. Ramar and G. Gurunathan, “Technical review on ontology mapping techniques,” Asian Journal of Information Technology, vol. 15, no. 4, pp. 676-688, 2016.
[40] N. F. Noy and M. A. Musen, “The PROMPT suite: interactive tools for ontology merging and mapping,” International Journal of Human-Computer Studies, vol. 59, no. 6, pp. 983-1024, 2003.
[41] R. E. Menéndez-Mora and R. Ichise, “Ontology matching by actively propagating user feedbacks through upper ontologies,” Revista Vínculos, vol. 10, no. 2, pp. 85-92, 2013.
[42] J. Madhavan, P. A. Bernstein, A. Doan and A. Halevy, “Corpus-based schema matching”. In Data Engineering, ICDE 2005 Proceedings. 21st International Conference. IEEE, Tokyo, Japan, pp. 57-68, 2005.
[43] P. Jain, P. Hitzler, A. P. Sheth, K. Verma and P. Z. Yeh, “Ontology alignment for linked open data,” International Semantic Web Conference. Springer, Berlin, Heidelberg, pp. 402-417, 2010.
[44] L. Otero-Cerdeira, F. J. Rodríguez-Martínez and A. Gómez-Rodríguez, “Ontology matching: A literature review,” Expert Systems with Applications, vol. 42, no. 2, pp. 949-971, 2015.
[45] IEEE Guide for Software Quality Assurance Planning. Std. 730.1–1995 IEEE Computer Society, 1995.
[46] W3C., Ontology Dowsing [online]. ESW Wiki. Retrieved from http://esw.w3.org/Ontology Dowsing, 2010, January 14.
[47] J. Corbin and A. Strauss,  Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory,  Sage Publications, 2008
[48] D. Octaviani, A. Pranolo and S. Othman, “RDB2Onto: an approach for creating semantic metadata from relational educational data,” Science in Information Technology (ICSITech), 2015 International Conference. IEEE, Yogyakarta, Indonesia, pp. 137-140, 2015.
[49] S. Massmann, S. Raunich, D. Aumüller, P. Arnold and E. Rahm, “Evolution of the COMA match system,” In Proceedings of the 6th International Conference on Ontology Matching-Volume 814, CEUR-WS. Org, Bonn, Germany, pp. 49-60, 2011.
[50] L. Ouyang, B. Zou, M. Qu and C. Zhang, “A method of ontology evaluation based on coverage, cohesion and coupling,”  In Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on (Vol. 4). IEEE, Shanghai, China, pp. 2451-2455, 2011.
[51] J. Brank, M. Grobelnik and D. Mladenić, “A survey of ontology evaluation techniques,” In Proceedings of the Conference on Data Mining and Data Warehouses (SiKDD) , Ljubljana, Slovenia, 2005.
[52] G. Simsion and G. Witt, Data modeling essentials, Morgan Kaufmann, San Fransisco, 2005.
[53] A. M. Orme, H. Yao and L. H. Etzkorn, “Indicating ontology data quality, stability, and completeness throughout ontology evolution,” Journal of Software: Evolution and Process, vol. 19, no. 1, pp. 49-75, 2007.
[54] M. J. Khoshroo and O. Fatemi, "SEMAT, National Current Research Information System for IRAN," In Connecting Science with Society: the Role of Research Information in a knowledge-based Society. 10th International Conference on Current Research Information Systems (CRIS2010), Aalbort, Denmark, pp. 27-33, 2010.
[55] A. Hamzelooi, E. Khodabakhsh, H. Javdani, A. Davari, D. Hatami, M. Shirazi, R. Norooz zadeh, Statistical concepts of science, research and technology. Higher Education Research and Planning institue, Tehran, 2015.
[56] A. Saeedi, Statistics of Higher Education in Iran (Academic Year 2015-2016). Higher Education Research and Planning institue, Tehran, 2016.