Leveraging Ontology-based Systems through Continuous Ontology Engineering
Resumo
Research Context: Ontologies have been recognized as key enablers of digital transformation in industry. They are used to assign semantics to information items, supporting data and knowledge management based on a common and shared understanding and representation. They play a paramount role in the Semantic Web and the implementation of Linked Open Data (LOD). Scientific and/or Practical Problem: Developing and maintaining ontologies may be complex, time-consuming, and resource-intensive. Additionally, traditional sequential ontology engineering methods often fail to address industrial needs such as changing requirements and time constraints. Iterative approaches mitigate some challenges but are not always sufficient. Proposed Solution and/or Analysis: To align ontology development with information systems development, both processes must be integrated. An end-to-end flow that integrates and supports ontology engineering from conception to operation is required to enable a continuous and industry-aligned process. We propose the use of a Continuous Ontology Engineering (COE) approach. We define principles that characterize COE, report on its adoption in a multinational chemical company, and share lessons learned. Related IS Theory: This work relates to the organizational knowledge creation theory. Ontologies structure and organize knowledge, help capture tacit knowledge and transform it into explicit, enabling knowledge integration into information systems and supporting open data publication. Research Method: We conducted a participative case study to investigate the use of COE. Summary of Results: Findings suggest that COE contributes to aligning ontology and information system development. However, challenges remain, such as the lack of comprehensive and integrated tool support. Contributions and Impact to IS area: For researchers, this work advances the state of the art in a novel and relevant topic for developing knowledge-based systems, Semantic Web, and LOD solutions. For practitioners, it offers knowledge about COE and an example that may inspire organizations to implement COE practices to align ontology and information systems development.Referências
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Copeland, M., Brown, A., Parkinson, H. E., Stevens, R., and Malone, J. (2012). The swo project: A case study for applying agile ontology engineering methods for community driven ontologies. Proc. of the 3rd Int. Conf. on Biomedical Ontology (ICBO 2012).
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dos Santos Júnior, P. S., Barcellos, M. P., and Calhau, R. F. (2022). First step climbing the stairway to heaven model-results from a case study in industry. Journal of Software Engineering Research and Development, 10:1–5.
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El Kadiri, S. and Kiritsis, D. (2015). Ontologies in the context of product lifecycle management: state of the art literature review. Int. Journal of Production Research, 53(18):5657–5668, Taylor & Francis.
Falbo, R. d. A. (2014). Sabio: Systematic approach for building ontologies. In 1st Joint Workshop ONTO.COM / ODISE on Ontologies in Conceptual Modeling and Information Systems Engineering (FOIS 2014).
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Fonseca, C. M., Sales, T. P., Viola, V., da Fonseca, L. B. R., Guizzardi, G., and Almeida, J. P. A. (2021). Ontology-driven conceptual modeling as a service. In Joint Ontology Workshops, JOWO 2021.
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Garijo, D. (2017). Widoco: a wizard for documenting ontologies. In The Semantic Web–ISWC 2017, LNCS, volume 10588, pages 94–102. Springer.
Guizzardi, G. (2005). Ontological foundations for structural conceptual models. Phd thesis, Telematica Instituut Fundamental Research, University of Twente, The Netherlands. ISBN 90-75176-81-3.
Guizzardi, G. (2007). On ontology, ontologies, conceptualizations, modeling languages, and (meta)models. In Proc. of the 2007 conference on Databases and Information Systems IV: Selected Papers from the Seventh International Baltic Conference DBIS’2006, pages 18–39. IOS Press.
Guizzardi, G., Fonseca, C., Almeida, J., Sales, T., Benevides, A., and Porello, D. (2021). Types and Taxonomic Structures in Conceptual Modeling: A Novel Ontological Theory and Engineering Support. Data & Knowledge Engineering, 134:101891.
Hagedorn, T., Bone, M., Kruse, B., Grosse, I., and Blackburn, M. (2020). Knowledge representation with ontologies and semantic web technologies to promote augmented and artificial intelligence in systems engineering. Insight, 23(1):15–20.
Halilaj, L., Petersen, N., Grangel-González, I., Lange, C., Auer, S., Coskun, G., and Lohmann, S. (2016). Vocol: An integrated environment to support version-controlled vocabulary development. In Knowledge Engineering and Knowledge Management. EKAW 2016. LNCS, volume 10024, pages 303–319. Springer.
Heath, T. (2011). Linked data: Evolving the web into a global data space. Morgan & Claypool.
Jackson, R. C., Balhoff, J. P., Douglass, E., Harris, N. L., Mungall, C. J., and Overton, J. A. (2019). Robot: a tool for automating ontology workflows. BMC bioinformatics, 20:1–10.
Jaskó, S., Skrop, A., Holczinger, T., Chován, T., and Abonyi, J. (2020). Development of manufacturing execution systems in accordance with industry 4.0 requirements: A review of standard-and ontology-based methodologies and tools. Computers in industry, 123:103300.
Johanssen, J. O., Kleebaum, A., Paech, B., and Bruegge, B. (2019). Continuous software engineering and its support by usage and decision knowledge: An interview study with practitioners. Journal of software: evolution and process, 31(5).
Kumar, S. (2023). Data silos a roadblock for AIOps. arXiv preprint arXiv:2312.10039.
Matentzoglu, N., Goutte-Gattat, D., Tan, S. Z. K., Balhoff, J. P., Carbon, S., Caron, A. R., Duncan, W. D., Flack, J. E., Haendel, M., Harris, N. L., et al. (2022). Ontology development kit: a toolkit for building, maintaining and standardizing biomedical ontologies. Database, 2022:baac087.
Mealy, G. H. (1967). Another look at data. In Proc. of the November 14-16, 1967, fall joint computer conference, pages 525–534.
Musen, M. (2015). The protégé project: A look back and a look forward. AI Matters, 1(4).
Noppens, O. and Liebig, T. (2009). Ontology patterns and beyond: towards a universal pattern language. In Proc. of the 2009 Int. Conf. on Ontology Patterns - Volume 516, pages 179–186.
Norris, E., Hastings, J., Marques, M. M., Mutlu, A. N. F., Zink, S., and Michie, S. (2021). Why and how to engage expert stakeholders in ontology development: insights from social and behavioural sciences. Journal of Biomedical Semantics, 12.
Ohno, T. (1988). Toyota Production System: Beyond Large-Scale Production. Productivity Press.
Osumi-Sutherland, D., Courtot, M., Balhoff, J. P., and Mungall, C. (2017). Dead simple owl design patterns. Journal of biomedical semantics, 8.
Paschke, A. and Schäfermeier, R. (2018). OntoMaven: Maven-based ontology development and management of distributed ontology repositories. In Synergies Between Knowledge Engineering and Software Engineering, volume 626 of Advances in Intelligent Systems and Computing, pages 251–273. Springer.
Peroni, S. (2017). A simplified agile methodology for ontology development. In OWL: Experiences and Directions – Reasoner Evaluation, LNCS, volume 10161, pages 55–69. Springer.
Petersen, K. (2011). Is lean agile and agile lean?: a comparison between two software development paradigms. In Modern software engineering concepts and practices: Advanced approaches, pages 19–46. IGI Global.
Poveda-Villalón, M., Fernández-Izquierdo, A., Fernández-López, M., and García-Castro, R. (2022). Lot: An industrial oriented ontology engineering framework. Engineering Applications of Artificial Intelligence, 111:104755.
Ragavan, S. K. V., Khamis, A. M., Fiorini, S. R., Carbonera, J. L., Alarcos, A. O., Habib, M. K., Gonçalves, P. J. S., Li, H., and Olszewska, J. I. (2019). Ontologies for industry 4.0. Knowl. Eng. Rev., 34:e17.
Reginato, C. C., Salamon, J. S., Nogueira, G. G., Barcellos, M. P., Souza, V. E. S., Monteiro, M. E., and Guizzardi, R. (2022). A goal-oriented framework for ontology reuse. Applied Ontology, 17(3):365–399.
Ries, E. (2011). The lean startup. New York: Crown Business, 27:2016–2020.
Salamon, J. S. and Barcellos, M. P. (2022). Towards a framework for continuous ontology engineering. In XV Seminar on Ontology Research in Brazil (ONTOBRAS 2022), pages 158–165.
Salkin, C., Oner, M., Ustundag, A., and Cevikcan, E. (2018). A conceptual framework for industry 4.0. Industry 4.0: managing the digital transformation, pages 3–23.
Sandkuhl, K., Shilov, N., and Smirnov, A. (2020). Facilitating digital transformation: success factors and multi-aspect ontologies. Int. Journal of Integrated Supply Management, 13(4):376–393.
Spoladore, D. and Pessot, E. (2022). An evaluation of agile ontology engineering methodologies for the digital transformation of companies. Computers in Industry, 140:103690.
Studer, R., Benjamins, V. R., and Fensel, D. (1998). Knowledge engineering: Principles and methods. Data & knowledge engineering, 25(1-2):161–197.
Suárez-Figueroa, M. C., Gómez-Pérez, A., and Fernández-López, M. (2011). The neon methodology for ontology engineering. In Ontology engineering in a networked world, pages 9–34. Springer.
Taher, A., Vahdatikhaki, F., and Hammad, A. (2022). Formalizing knowledge representation in earthwork operations through development of domain ontology. Engineering, Construction and Architectural Management, 29(6):2382–2414.
Wieringa, R. and Daneva, M. (2015). Six strategies for generalizing software engineering theories. Science of computer programming, 101:136–152.
Womack, J. P. and Jones, D. T. (1997). Lean thinking—banish waste and create wealth in your corporation. Journal of the Operational Research Society, 48(11):1148–1148.
Yang, X. (2025). The role of data-driven decision-making in corporate digital transformation. Studies in Social Science & Humanities, 4(3):18–25.
Yildiz, B. and Miksch, S. (2007). Ontology-driven information systems: Challenges and requirements. In Int. Conf. on Semantic Web and Digital Libraries. Indian Statistical Institute Platinum Jubilee Conference Series, pages 35–44.
Abdelghany, A. S., Darwish, N. R., and Hefni, H. A. (2019). An agile methodology for ontology development. Int. Journal of Intelligent Engineering and Systems, 12(2):170–181.
Allemang, D., Garbacz, P., Gradzki, P., Kendall, E., and Trypuz, R. (2021). An infrastructure for collaborative ontology development. In Formal Ontology in Information Systems, volume 344 of Frontiers in Artificial Intelligence and Applications, pages 112–126. IOS Press.
Alobaid, A., Garijo, D., Poveda-Villalón, M., Santana-Perez, I., Fernández-Izquierdo, A., and Corcho, O. (2019). Automating ontology engineering support activities with ontoology. Journal of Web Semantics, 57:100472.
Barcellos, M. P. (2020). Towards a framework for continuous software engineering. In Proc. of the XXXIV Brazilian Symposium on Software Engineering, pages 626–631.
Baskerville, R. L. (1997). Distinguishing action research from participative case studies. Journal of systems and information technology, 1(1):24–43.
Blomqvist, E., Hammar, K., and Presutti, V. (2016). Engineering ontologies with patterns- the extreme design methodology. Ontology Engineering with Ontology Design Patterns, 25:23–50.
Chávez-Feria, S., García-Castro, R., and Poveda-Villalón, M. (2022). Chowlk: from uml-based ontology conceptualizations to owl. In European Semantic Web Conference, pages 338–352. Springer.
Copeland, M., Brown, A., Parkinson, H. E., Stevens, R., and Malone, J. (2012). The swo project: A case study for applying agile ontology engineering methods for community driven ontologies. Proc. of the 3rd Int. Conf. on Biomedical Ontology (ICBO 2012).
Cummings, J. and Stacey, D. (2018). Lean ontology development: An ontology development paradigm based on continuous innovation. In Proc. of the 10th Int. Joint Confer ence on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - Volume 2: KEOD, pages 365–372. SciTePress.
Davis, E. (1998). Naive physics perplex. AI magazine, 19(4):51–79.
Debois, P. et al. (2011). Devops: A software revolution in the making. Journal of Information Technology Management, 24(8):3–39.
dos Santos Júnior, P. S., Barcellos, M. P., and Calhau, R. F. (2022). First step climbing the stairway to heaven model-results from a case study in industry. Journal of Software Engineering Research and Development, 10:1–5.
Earley, S. (2020). The AI-powered enterprise: Harness the power of ontologies to make your business smarter, faster, and more profitable. LifeTree Media.
El Kadiri, S. and Kiritsis, D. (2015). Ontologies in the context of product lifecycle management: state of the art literature review. Int. Journal of Production Research, 53(18):5657–5668, Taylor & Francis.
Falbo, R. d. A. (2014). Sabio: Systematic approach for building ontologies. In 1st Joint Workshop ONTO.COM / ODISE on Ontologies in Conceptual Modeling and Information Systems Engineering (FOIS 2014).
Fernández-López, M., Gómez-Pérez, A., and Juristo, N. (1997). Methontology: from ontological art towards ontological engineering. In Papers from the 1997 AAAI Spring Symposium.
Fitzgerald, B. and Stol, K.-J. (2017). Continuous software engineering: A roadmap and agenda. Journal of Systems and Software, 123:176–189.
Fonseca, C. M., Sales, T. P., Viola, V., da Fonseca, L. B. R., Guizzardi, G., and Almeida, J. P. A. (2021). Ontology-driven conceptual modeling as a service. In Joint Ontology Workshops, JOWO 2021.
Gangemi, A. and Presutti, V. (2009). Ontology design patterns. In Handbook on ontologies, pages 221–243. Springer, Berlin, Heidelberg.
Garijo, D. (2017). Widoco: a wizard for documenting ontologies. In The Semantic Web–ISWC 2017, LNCS, volume 10588, pages 94–102. Springer.
Guizzardi, G. (2005). Ontological foundations for structural conceptual models. Phd thesis, Telematica Instituut Fundamental Research, University of Twente, The Netherlands. ISBN 90-75176-81-3.
Guizzardi, G. (2007). On ontology, ontologies, conceptualizations, modeling languages, and (meta)models. In Proc. of the 2007 conference on Databases and Information Systems IV: Selected Papers from the Seventh International Baltic Conference DBIS’2006, pages 18–39. IOS Press.
Guizzardi, G., Fonseca, C., Almeida, J., Sales, T., Benevides, A., and Porello, D. (2021). Types and Taxonomic Structures in Conceptual Modeling: A Novel Ontological Theory and Engineering Support. Data & Knowledge Engineering, 134:101891.
Hagedorn, T., Bone, M., Kruse, B., Grosse, I., and Blackburn, M. (2020). Knowledge representation with ontologies and semantic web technologies to promote augmented and artificial intelligence in systems engineering. Insight, 23(1):15–20.
Halilaj, L., Petersen, N., Grangel-González, I., Lange, C., Auer, S., Coskun, G., and Lohmann, S. (2016). Vocol: An integrated environment to support version-controlled vocabulary development. In Knowledge Engineering and Knowledge Management. EKAW 2016. LNCS, volume 10024, pages 303–319. Springer.
Heath, T. (2011). Linked data: Evolving the web into a global data space. Morgan & Claypool.
Jackson, R. C., Balhoff, J. P., Douglass, E., Harris, N. L., Mungall, C. J., and Overton, J. A. (2019). Robot: a tool for automating ontology workflows. BMC bioinformatics, 20:1–10.
Jaskó, S., Skrop, A., Holczinger, T., Chován, T., and Abonyi, J. (2020). Development of manufacturing execution systems in accordance with industry 4.0 requirements: A review of standard-and ontology-based methodologies and tools. Computers in industry, 123:103300.
Johanssen, J. O., Kleebaum, A., Paech, B., and Bruegge, B. (2019). Continuous software engineering and its support by usage and decision knowledge: An interview study with practitioners. Journal of software: evolution and process, 31(5).
Kumar, S. (2023). Data silos a roadblock for AIOps. arXiv preprint arXiv:2312.10039.
Matentzoglu, N., Goutte-Gattat, D., Tan, S. Z. K., Balhoff, J. P., Carbon, S., Caron, A. R., Duncan, W. D., Flack, J. E., Haendel, M., Harris, N. L., et al. (2022). Ontology development kit: a toolkit for building, maintaining and standardizing biomedical ontologies. Database, 2022:baac087.
Mealy, G. H. (1967). Another look at data. In Proc. of the November 14-16, 1967, fall joint computer conference, pages 525–534.
Musen, M. (2015). The protégé project: A look back and a look forward. AI Matters, 1(4).
Noppens, O. and Liebig, T. (2009). Ontology patterns and beyond: towards a universal pattern language. In Proc. of the 2009 Int. Conf. on Ontology Patterns - Volume 516, pages 179–186.
Norris, E., Hastings, J., Marques, M. M., Mutlu, A. N. F., Zink, S., and Michie, S. (2021). Why and how to engage expert stakeholders in ontology development: insights from social and behavioural sciences. Journal of Biomedical Semantics, 12.
Ohno, T. (1988). Toyota Production System: Beyond Large-Scale Production. Productivity Press.
Osumi-Sutherland, D., Courtot, M., Balhoff, J. P., and Mungall, C. (2017). Dead simple owl design patterns. Journal of biomedical semantics, 8.
Paschke, A. and Schäfermeier, R. (2018). OntoMaven: Maven-based ontology development and management of distributed ontology repositories. In Synergies Between Knowledge Engineering and Software Engineering, volume 626 of Advances in Intelligent Systems and Computing, pages 251–273. Springer.
Peroni, S. (2017). A simplified agile methodology for ontology development. In OWL: Experiences and Directions – Reasoner Evaluation, LNCS, volume 10161, pages 55–69. Springer.
Petersen, K. (2011). Is lean agile and agile lean?: a comparison between two software development paradigms. In Modern software engineering concepts and practices: Advanced approaches, pages 19–46. IGI Global.
Poveda-Villalón, M., Fernández-Izquierdo, A., Fernández-López, M., and García-Castro, R. (2022). Lot: An industrial oriented ontology engineering framework. Engineering Applications of Artificial Intelligence, 111:104755.
Ragavan, S. K. V., Khamis, A. M., Fiorini, S. R., Carbonera, J. L., Alarcos, A. O., Habib, M. K., Gonçalves, P. J. S., Li, H., and Olszewska, J. I. (2019). Ontologies for industry 4.0. Knowl. Eng. Rev., 34:e17.
Reginato, C. C., Salamon, J. S., Nogueira, G. G., Barcellos, M. P., Souza, V. E. S., Monteiro, M. E., and Guizzardi, R. (2022). A goal-oriented framework for ontology reuse. Applied Ontology, 17(3):365–399.
Ries, E. (2011). The lean startup. New York: Crown Business, 27:2016–2020.
Salamon, J. S. and Barcellos, M. P. (2022). Towards a framework for continuous ontology engineering. In XV Seminar on Ontology Research in Brazil (ONTOBRAS 2022), pages 158–165.
Salkin, C., Oner, M., Ustundag, A., and Cevikcan, E. (2018). A conceptual framework for industry 4.0. Industry 4.0: managing the digital transformation, pages 3–23.
Sandkuhl, K., Shilov, N., and Smirnov, A. (2020). Facilitating digital transformation: success factors and multi-aspect ontologies. Int. Journal of Integrated Supply Management, 13(4):376–393.
Spoladore, D. and Pessot, E. (2022). An evaluation of agile ontology engineering methodologies for the digital transformation of companies. Computers in Industry, 140:103690.
Studer, R., Benjamins, V. R., and Fensel, D. (1998). Knowledge engineering: Principles and methods. Data & knowledge engineering, 25(1-2):161–197.
Suárez-Figueroa, M. C., Gómez-Pérez, A., and Fernández-López, M. (2011). The neon methodology for ontology engineering. In Ontology engineering in a networked world, pages 9–34. Springer.
Taher, A., Vahdatikhaki, F., and Hammad, A. (2022). Formalizing knowledge representation in earthwork operations through development of domain ontology. Engineering, Construction and Architectural Management, 29(6):2382–2414.
Wieringa, R. and Daneva, M. (2015). Six strategies for generalizing software engineering theories. Science of computer programming, 101:136–152.
Womack, J. P. and Jones, D. T. (1997). Lean thinking—banish waste and create wealth in your corporation. Journal of the Operational Research Society, 48(11):1148–1148.
Yang, X. (2025). The role of data-driven decision-making in corporate digital transformation. Studies in Social Science & Humanities, 4(3):18–25.
Yildiz, B. and Miksch, S. (2007). Ontology-driven information systems: Challenges and requirements. In Int. Conf. on Semantic Web and Digital Libraries. Indian Statistical Institute Platinum Jubilee Conference Series, pages 35–44.
Publicado
25/05/2026
Como Citar
SALAMON, Jordana Sarmenghi; ARIAS, Paola Espinoza; BARCELLOS, Monalessa Perini.
Leveraging Ontology-based Systems through Continuous Ontology Engineering. In: SIMPÓSIO BRASILEIRO DE SISTEMAS DE INFORMAÇÃO (SBSI), 22. , 2026, Vitória/ES.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 141-160.
DOI: https://doi.org/10.5753/sbsi.2026.248312.
