Department of Cultural Technology and Communications, Intelligent Systems Lab, University of the Aegean, University Hill, 81100Lesvos, Greece, e-mail: kotis@aegean.gr"/> Department of Digital Systems, AI Lab, Gr. Lampraki 126, University of Piraeus, Piraeus, Greece, e-mail: georgev@unipi.gr"/> Department of Informatics and Telecommunications, University of the Peloponnese, Tripoli, Greece, e-mail: dspiliot@uop.gr"/>
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2020 Volume 35
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RESEARCH ARTICLE   Open Access    

Ontology engineering methodologies for the evolution of living and reused ontologies: status, trends, findings and recommendations

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  • Abstract: The aim of this critical review paper is threefold: (a) to provide an insight on the impact of ontology engineering methodologies (OEMs) to the evolution of living and reused ontologies, (b) to update the ontology engineering (OE) community on the status and trends in OEMs and of their use in practice and (c) to propose a set of recommendations for working ontologists to consider during the life cycle of living, evolved and reused ontologies. The work outlined in this critical review paper has been motivated by the need to address critical issues on keeping ontologies alive and evolving while these are shared in wide communities. It is argued that the engineering of ontologies must follow a well-defined methodology, addressing practical aspects that would allow (sometimes wide) communities of experts and ontologists to reach consensus on developments and keep the evolution of ontologies ‘in track’. In doing so, specific collaborative and iterative tool-supported tasks and phases within a complete and evaluated ontology life cycle are necessary. This way the engineered ontologies can be considered ‘shared, commonly agreed and continuously evolved “live” conceptualizations’ of domains of discourse. Today, in the era of Linked Data and Knowledge Graphs, it is more necessary than ever not to neglect to consider the recommendations that OEMs explicitly and implicitly introduce and their implications to the evolution of living ontologies. This paper reports on the status of OEMs, identifies trends and provides recommendations based on the findings of an analysis that concerns the impact of OEMs to the status of well-known, widely used and representative ontologies.
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  • Berrueta , D.et al.2018. SIOC Core Ontology Specification. Retrieved September 17, 2018, from http://rdfs.org/sioc/spec/.

    Google Scholar

    Bojars , U., Passant , A., Breslin , J. G. & Decker , S. 2009. The Semantically-Interlinked Online Communities (SIOC) project. In Proceedings of the Second Multi-Agent Logics, Languages, and Organisations Federated Workshops, 3–4, Turin, Italy.

    Google Scholar

    Fernández-López , M., Gómez-Pérez , A. & Juristo , N.1997. METHONTOLOGY: From Ontological Art Towards Ontological Engineering. In: “AAAI-97 Spring Symposium Series”, 24–26 March 1997, Stanford University, EEUU.

    Google Scholar

    Hepp , M. 2011. GoodRelations Language Reference. Retrieved September 17, 2018, from http://www.heppnetz.de/ontologies/goodrelations/v1.html

    Google Scholar

    About Human Resources Management Ontology | Joinup. n.d. Retrieved September 27, 2018, from https://joinup.ec.europa.eu/solution/human-resources-management-ontology/about.

    Google Scholar

    Alobaid , A., Garijo , D., Poveda-Villalón , M., Santana-Perez , I., Fernández-Izquierdo , A., & Corcho , O. (2019). Automating ontology engineering support activities with OnToology. Journal of Web Semantics, 57, 100472. https://doi.org/10.1016/J.WEBSEM.2018.09.003.

    Google Scholar

    Arakaki , F. A., Alves , R. C. V. & Santos , P. L. V. A. da C. 2018. Dublin Core: state of art (1995 to 2015). Informação & Sociedade: Estudos28(2). https://doi.org/10.22478/ufpb.1809-4783.2018v28n2.38012.

    Google Scholar

    Arndt , N., Naumann , P., Radtke , N., Martin , M. & Marx , E.2019. Decentralized collaborative knowledge management using git. Journal of Web Semantics, 54, 29–47. https://doi.org/10.1016/j.websem.2018.08.002.

    Google Scholar

    Basca , C., Corlosquet , S., Cyganiak , R., Fernández , S. & Schandl , T.2008. Neologism: Easy vocabulary publishing.

    Google Scholar

    Bekiari , C., Doerr , M., Tzitzikas , Y., Allocca , C., Barde , J., Minadakis , N. & Marketakis , Y.2017. MARINETLO-DRAFT iMarine-Data e-Infrastructure Initiative for Fisheries Management and Conservation of Marine Living Resources (EU-FP7-CP & CSA) BlueBRIDGE: Building Research environments for fostering Innovation, Decision making, Governance and Educat. https://www.ics.forth.gr/isl/MarineTLO/documentation/MarineTLO_documentation_v5.pdf.

    Google Scholar

    Bosca , A., Casu , M., Dragoni , M. & Rexha , A.2014. Modeling, managing, exposing, and linking ontologies with a wiki-based tool. In Proceedings of LREC, 1668.

    Google Scholar

    Calbimonte , J. P., Dubosson , F., Hilfiker , R., Cotting , A. & Schumacher , M.2017. The MedRed ontology for representing clinical data acquisition metadata. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10588 LNCS, 38–47. https://doi.org/10.1007/978-3-319-68204-4_4.

    Google Scholar

    Carbon , S., Dietze , H., Lewis , S. E., Mungall , C. J., Munoz-Torres , M. C., Basu , S., … Westerfield , M.2017. Expansion of the gene ontology knowledgebase and resources: The gene ontology consortium. Nucleic Acids Research, 45(D1), D331–D338. https://doi.org/10.1093/nar/gkw1108

    Google Scholar

    Casanovas , P., Casellas , N., Tempich , C., Vrandečić , D. & Benjamins , R.2007. OPJK and DILIGENT: ontology modeling in a distributed environment. Artificial Intelligence and Law, 15(2), 171–186. https://doi.org/10.1007/s10506-007-9036-2.

    Google Scholar

    Compton , M., Barnaghi , P., Bermudez , L., García-Castro , R., Corcho , O., Cox , S., … Taylor , K.2012. The SSN ontology of the W3C semantic sensor network incubator group. Web Semantics: Science, Services and Agents on the World Wide Web, 17, 25–32. https://doi.org/10.1016/j.websem.2012.05.003

    Google Scholar

    Corcho , O. & Espinoza-Arias , P.n.d. Vocabulary for data representation of the local business census and activities licenses. Retrieved August 19, 2019, from http://vocab.ciudadesabiertas.es/def/comercio/tejido-comercial/index-en.html#Terraza.

    Google Scholar

    Corcho , O., Fernández-López , M. & Gómez-Pérez , A.2003. Methodologies, tools and languages for building ontologies. Where is their meeting point?Data and Knowledge Engineering, 46(1), 41–64. https://doi.org/10.1016/S0169-023X(02)00195-7.

    Google Scholar

    D’Amato , C., Fanizzi , N. & Esposito , F.2010. Inductive learning for the Semantic Web: What does it buy?Semantic Web, 1(1–2), 53–59. https://doi.org/10.3233/SW-2010-0007.

    Google Scholar

    Damova , M., Kiryakov , A., Simov , K. & Petrov , S.2010. Mapping the central LOD ontologies to PROTON upper-level ontology. CEUR Workshop Proceedings, 689(c), 61–72.

    Google Scholar

    Dan Brickley , L. M.2014. FOAF Vocabulary Specification 0.99. Retrieved September 17, 2018, from http://xmlns.com/foaf/spec/.

    Google Scholar

    De Leenheer , P., Christiaens , S. & Meersman , R.2010. Business semantics management: A case study for competency-centric HRM. Computers in Industry, 61(8), 760–775. https://doi.org/10.1016/J.COMPIND.2010.05.005.

    Google Scholar

    de Moor , A., De Leenheer , P. & Meersman , R.2006. DOGMA-MESS: A Meaning Evolution Support System for Interorganizational Ontology Engineering. In H.Schärfe , P.Hitzler & P.Øhrstrøm (Eds.), Conceptual Structures: Inspiration and Application,189–202. Springer.

    Google Scholar

    De Nicola , A. & Missikoff , M.2016. A lightweight methodology for rapid ontology engineering. Communications of the ACM, 59(3), 79–86. https://doi.org/10.1145/2818359.

    Google Scholar

    Debruyne , C., Tran , T. K. & Meersman , R.2013. Grounding Ontologies with Social Processes and Natural Language. Journal on Data Semantics, 2(2–3), 89–118. https://doi.org/10.1007/s13740-013-0023-3

    Google Scholar

    Dellschaft , K., Engelbrecht , H., Barreto , J. M., Rutenbeck , S. & Staab , S.2008. Cicero: Tracking Design Rationale in Collaborative Ontology Engineering. In The Semantic Web: Research and Applications, 782–786. Springer. https://doi.org/10.1007/978-3-540-68234-9_58.

    Google Scholar

    Dessimoz , C. & Škunca , N. (Eds.). 2017. The Gene Ontology Handbook, 1446. Springer. https://doi.org/10.1007/978-1-4939-3743-1.

    Google Scholar

    DiGiuseppe , N., Pouchard , L. C. & Noy , N. F.2014. SWEET ontology coverage for earth system sciences. Earth Science Informatics, 7(4), 249–264. https://doi.org/10.1007/s12145-013-0143-1.

    Google Scholar

    Dragoni , M., Bailoni , T., Maimone , R. & Eccher , C.2018. HeLiS: An Ontology for Supporting Healthy Lifestyles,53–69. Springer, Cham. https://doi.org/10.1007/978-3-030-00668-6_4.

    Google Scholar

    Espinoza-Arias , P., Poveda-Villalón , M., García-Castro , R. & Corcho , O.2018. Ontological representation of smart city data: From devices to cities. Applied Sciences, 9(1), 32. https://doi.org/10.3390/app9010032.

    Google Scholar

    Farazi , F., Maltese , V., Dutta , B., Ivanyukovich , A. & Rizzi , V.2013. A semantic geo-catalogue for a local administration. Artificial Intelligence Review, 40(2), 193–212. https://doi.org/10.1007/s10462-012-9353-z.

    Google Scholar

    Fernández-López , M. & Gómez-Pérez , A.2002. Overview and analysis of methodologies for building ontologies. Knowledge Engineering Review, 17(2), 129–156. https://doi.org/10.1017/S0269888902000462.

    Google Scholar

    Garcia , A., Neill , K. O., Garcia , L. J., Lord , P., Corcho , O. & Gibson , F.2010. Developing ontologies within decentralised settings. In Semantic e-Science. Annals of Information Systems, 11, 99–139). Springer. https://doi.org/10.1007/978-1-4419-5908-9

    Google Scholar

    George Fazekas , M. C.2018. Audio Commons ontology: a data model for an audio content ecosystem. In Proceedings of the 17th International Semantic Web Conference.

    Google Scholar

    George Fazekas , M. C.n.d. The Audio Commons Ontology. Retrieved September 12, 2018, from http://www.audiocommons.org/ac-ontology/aco.html

    Google Scholar

    Giménez-García , J. M., Zimmermann , A. & Maret , P.2017. NdFluents: An ontology for annotated statements with inference preservation. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10249LNCS, 638–654. https://doi.org/10.1007/978-3-319-58068-5_39.

    Google Scholar

    Giunchiglia , F., Dutta , B., Maltese , V. & Farazi , F.2012. A facet-based methodology for the construction of a large-scale geospatial ontology. Journal on Data Semantics, 1(1), 57–73. https://doi.org/10.1007/s13740-012-0005-x.

    Google Scholar

    Giunchiglia , F., Maltese , V., Farazi , F. & Dutta , B.2010. GeoWordNet: A Resource for Geo-spatial Applications, 121–136. Springer. https://doi.org/10.1007/978-3-642-13486-9_9.

    Google Scholar

    Giunchiglia , F., Shvaiko , P. & Yatskevich , M.2004. S-Match: an Algorithm and an Implementation of Semantic Matching, pp. 61–75. Springer. https://doi.org/10.1007/978-3-540-25956-5_5.

    Google Scholar

    Gómez-Pérez , A., Ramírez , J. & Villazón-Terrazas , B.2007. An ontology for modelling human resources management based on standards. In Knowledge-Based Intelligent Information and Engineering Systems, Lectur. Springer. http://oa.upm.es/5168/.

    Google Scholar

    Grau , B. C., Horrocks , I., Kazakov , Y. & Sattler , U.2008. Modular reuse of ontologies: theory and practice. JAIR, 31, 273–318.

    Google Scholar

    M. O.Group . 2013. The Music Ontology. Retrieved September 26, 2018, from http://musicontology.com/docs/getting-started.html

    Google Scholar

    O. E.Group . 2019. Linked Open Terms (LOT) Methodology. https://doi.org/10.5281/ZENODO.2539305.

    Google Scholar

    Guarino , N. & Oberle , D.2009. Handbook on Ontologies, 1–17. https://doi.org/10.1007/978-3-540-92673-3.

    Google Scholar

    Guha , R. V., Brickley , D. & Macbeth , S.2016. Schema.org. Communications of the ACM, 59(2), 44–51. https://doi.org/10.1145/2844544.

    Google Scholar

    Halilaj , L., Petersen , N., Grangel-González , I., Lange , C., Auer , S., Coskun , G. & Lohmann , S.2016. Vocol: An integrated environment to support version-controlled vocabulary development.

    Google Scholar

    Haller , A., Janowicz , K., Cox , S. J. D., Lefrançois , M., Taylor , K., Le Phuoc , D., … Stadler , C.2018. The modular SSN ontology: A joint W3C and OGC standard specifying the semantics of sensors, observations, sampling, and actuation. Semantic Web, Preprint (Preprint), 1–24. https://doi.org/10.3233/SW-180320.

    Google Scholar

    Hepp , M.2008. GoodRelations: An ontology for describing products and services offers on the web. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5268LNAI, 329–346. https://doi.org/10.1007/978-3-540-87696-0-29.

    Google Scholar

    Hoffart , J., Suchanek , F. M., Berberich , K. & Weikum , G.2013. YAGO2: A spatially and temporally enhanced knowledge base from Wikipedia. Artificial Intelligence, 194, 28–61. https://doi.org/10.1016/J.ARTINT.2012.06.001.

    Google Scholar

    Iqbal , R., Murad , M. A. A., Mustapha , A. & Sharef , N. M.2013. An analysis of ontology engineering methodologies: A literature review. Research Journal of Applied Sciences, Engineering and Technology, 6(16), 2993–3000. https://doi.org/10.19026/rjaset.6.3684.

    Google Scholar

    Janowicz , K., Haller , A., Cox , S. J. D., Phuoc , D. Le, Lefrançois , M., Janowicz , K., … Lefranc , M.2018. SOSA: a lightweight ontology for sensors, observations, samples, and actuators. Journal of Web Semantics, In Press.

    Google Scholar

    Kanza , S., Stolz , A., Hepp , M. & Simperl , E.2018. What does an ontology engineering community look like? A systematic analysis of the schema.org Community, 335–350. Springer, Cham. https://doi.org/10.1007/978-3-319-93417-4_22.

    Google Scholar

    Katis , E., Kondylakis , H., Agathangelos , G. & Vassilakis , K.2018. Developing an Ontology for Curriculum and Syllabus, 55–59. Springer, Cham. https://doi.org/10.1007/978-3-319-98192-5_11.

    Google Scholar

    Keet , C. M.2018. An Introduction to Ontology Engineering. Cape Town: Independent. https://open.umn.edu/opentextbooks/textbooks/590

    Google Scholar

    Kotis , K. & Papasalouros , A.2010. Learning useful kick-off ontologies from query logs: HCOME revised. In CISIS 2010 – The 4th International Conference on Complex, Intelligent and Software Intensive Systems. https://doi.org/10.1109/CISIS.2010.50.

    Google Scholar

    Kotis , K., Papasalouros , A., Vouros , G., Pappas , N. & Zoumpatianos , K.2011. Enhancing the collective knowledge for the engineering of ontologies in open and socially constructed learning spaces. Journal of Universal Computer Science, 17(12).

    Google Scholar

    Kotis , K. & Vouros , G. A.2006. Human-centered ontology engineering: the HCOME methodology. Knowledge and Information Systems, 10(1). https://doi.org/10.1007/s10115-005-0227-4.

    Google Scholar

    Kotis , K. & Katasonov , A.2013. Semantic interoperability on the Internet of Things. International Journal of Distributed Systems and Technologies, 4(3), 47–69. https://doi.org/10.4018/jdst.2013070104.

    Google Scholar

    Leenheer , P. D. & Debruyne , C.2008. DOGMA-MESS: a tool for fact-oriented collaborative ontology evolution, 5333(November). https://doi.org/10.1007/978-3-540-88875-8.

    Google Scholar

    Liu , D., Mikroyannidi , E. & Lee , R.2014. Semantic web technologies supporting the BBC knowledge & learning beta online pages. CEUR Workshop Proceedings, 1254.

    Google Scholar

    Liu , W., Liu , J. & Rajapakse , J. C.2018. Gene ontology enrichment improves performances of functional similarity of genes. Scientific Reports, 8(1), 12100. https://doi.org/10.1038/s41598-018-30455-0.

    Google Scholar

    Maria Keet , C. & Ławrynowicz , A.2016. Test-driven development of ontologies. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9678, 642–657. https://doi.org/10.1007/978-3-319-34129-3_39.

    Google Scholar

    Mendes , P. N., Jakob , M. & Bizer , C.2012. DBpedia: A multilingual cross-domain knowledge base. Language Resources and Evaluation LRES, 1813–1817. https://doi.org/978-2-9517408-7-7

    Google Scholar

    Munoz-Torres , M. & Carbon , S.2017. Get GO! Retrieving GO Data Using AmiGO, QuickGO, API, Files, and Tools,149–160. Humana Press. https://doi.org/10.1007/978-1-4939-3743-1_11.

    Google Scholar

    Narula , G. S., Yadav , U., Duhan , N. & Jain , V.2018. Evolution of FOAF and SIOC in Semantic Web: A Survey, 253–263. Springer. https://doi.org/10.1007/978-981-10-6620-7_25.

    Google Scholar

    Noy , N. F. & McGuinness , D. L.2001. Ontology development 101: a guide to creating your first ontology. Knowledge Systems Laboratory Stanford University, 25. https://doi.org/10.1016/j.artmed.2004.01.014.

    Google Scholar

    Pérez , A., Baonza , M. & Villazón , B.2008. Neon methodology for building ontology networks: Ontology specification. Methodology.https://doi.org/10.1016/j.landurbplan.2011.04.007.

    Google Scholar

    Peroni , S.2017. A simplified agile methodology for ontology development. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10161 LNCS, 55–69. https://doi.org/10.1007/978-3-319-54627-8_5

    Google Scholar

    Peroni , S., Palmirani , M. & Vitali , F.2017. UNDO: The United Nations system document ontology. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10588 LNCS, 175–183. https://doi.org/10.1007/978-3-319-68204-4_18

    Google Scholar

    Peroni , S. & Shotton , D.2018. The spar ontologies. In Proceedings of the 17th International Semantic Web Conference. https://sparontologies.github.io/article/spar-iswc2018/

    Google Scholar

    Pinto , S., Tempich , C. & Staab , S.2009. Ontology engineering and evolution in a distributed world using DILIGENT. In S.Staab & R.Studer (eds.), Handbook on Ontologies, 153–176. Springer. https://doi.org/10.1007/978-3-540-92673-3_7.

    Google Scholar

    Poveda-Villalón , M., Gómez-Pérez , A. & Suárez-Figueroa , M. C.2014. OOPS! (OntOlogy Pitfall Scanner!): an on-line tool for ontology evaluation. Int. J. Semant. Web Inf. Syst., 10(2), 7–34. https://doi.org/10.4018/ijswis.2014040102.

    Google Scholar

    Raimond , Y., Abdallah , S., Sandler , M. & Giasson , F.2007. The Music Ontology. In ISMIR 2007: 8th International Conference on Music Information Retrieval, 8, 417–422. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.173.5403&rep=rep1&type=pdf.

    Google Scholar

    Raimond , Y. & Sandler , M.2012. Evaluation of the music ontology framework. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7295LNCS, 255–269. https://doi.org/10.1007/978-3-642-30284-8_24.

    Google Scholar

    Raimond , Y., Scott , T., Oliver , S., Sinclair , P. & Smethurst , M.2010. Use of semantic web technologies on the BBC web sites. In Linking Enterprise Data, 263–283. Boston, MA: Springer US. https://doi.org/10.1007/978-1-4419-7665-9_13.

    Google Scholar

    Raskin , R.2003. Semantic Web for Earth and Environmental Terminology (SWEET). https://sweet.jpl.nasa.gov/.

    Google Scholar

    Raskin , R. G. & Pan , M. J.2005. Knowledge representation in the semantic web for Earth and environmental terminology (SWEET). Computers & Geosciences, 31(9), 1119–1125. https://doi.org/10.1016/J.CAGEO.2004.12.004

    Google Scholar

    Rebele , T., Suchanek , F. M., Hoffart , J., Biega , J., Kuzey , E. & Weikum , G.2016. YAGO: A Multilingual Knowledge Base from Wikipedia, Wordnet, and Geonames. In The Semantic Web - {ISWC} 2016 - 15th International Semantic Web Conference, Kobe, Japan, October 17–21, 2016, Proceedings, Part {II}, 177–185. https://doi.org/10.1007/978-3-319-46547-0_19.

    Google Scholar

    Salatino , A. A., Thanapalasingam , T., Mannocci , A., Osborne , F. & Motta , E.2018. The Computer Science Ontology: A Large-Scale Taxonomy of Research Areas. http://oro.open.ac.uk/55484/.

    Google Scholar

    Santipantakis , G. M. & Vouros , G. A.2014. Constructing E-SHIQ distributed knowledge bases via ontology modularization: the mONTul method. In Proceedings of the 8th International Workshop on Modular Ontologies co-located with the 8th International Conference on Formal Ontology in Information Systems (FOIS 2014), Rio de Janeiro, Brazil, September 22, 2014.http://ceur-ws.org/Vol-1248/WoMO14-Paper1.pdf.

    Google Scholar

    Santipantakis , G. M., Vouros , G. A., Doulkeridis , C., Vlachou , A., Andrienko , G., Andrienko , N., … Martinez , M. G.2017. Specification of semantic trajectories supporting data transformations for analytics. In Proceedings of the 13th International Conference on Semantic Systems – Semantics 2017, 17–24. ACM Press. https://doi.org/10.1145/3132218.3132225.

    Google Scholar

    Santipantakis , G. M., Vouros , G. A., Glenis , A., Doulkeridis , C. & Vlachou , A.2017. The datAcron ontology for semantic trajectories. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10577. LNCS, 26–30. Springer. https://doi.org/10.1007/978-3-319-70407-4_6.

    Google Scholar

    Simperl , E. & Luczak-Rösch , M.2014. Collaborative ontology engineering: a survey. Knowledge Engineering Review, 29(1), 101–131. https://doi.org/10.1017/S0269888913000192.

    Google Scholar

    Stadlhofer , B., Salhofer , P. & Durlacher , A.2013. An overview of ontology engineering methodologies in the context of public administration. SEMAPRO 2013, The Seventh International Conference on Advances in Semantic Processing, (c), 36–42. http://www.thinkmind.org/index.php?view=article&articleid=semapro_2013_2_30_50039.

    Google Scholar

    Stellato , A., Rajbhandari , S., Turbati , A., Fiorelli , M., Caracciolo , C., Lorenzetti , T., … Pazienza , M. T.2015. VocBench: a web application for collaborative development of multilingual thesauri. In European Semantic Web Conference, 38–53.

    Google Scholar

    Sure , Y., Staab , S. & Studer , R.2004. On-To-Knowledge Methodology (OTKM). In S.Staab & R.Studer (eds.), Handbook on Ontologies, 117–132. Springer. https://doi.org/10.1007/978-3-540-24750-0_6.

    Google Scholar

    Tommasini , R., Sedira , Y. A., DellAglio, D., Balduini , M., Ali , M. I., Le Phuoc , D., … Calbimonte , J.-P.2018. VoCaLS: Vocabulary and catalog of linked streams. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11137LNCS, 256–272. https://doi.org/10.1007/978-3-030-00668-6_16.

    Google Scholar

    Tudorache , T., Vendetti , J., & Noy , N. F.2009. Web-Protégé: A lightweight OWL ontology editor for the web. CEUR Workshop Proceedings, 432.

    Google Scholar

    Tzitzikas , Y., Allocca , C., Bekiari , C., Marketakis , Y., Fafalios , P., Doerr , M., … Candela , L.2016. Unifying heterogeneous and distributed information about marine species through the top level ontology MarineTLO. Program, 50(1), 16–40. https://doi.org/10.1108/PROG-10-2014-0072.

    Google Scholar

    Uschold , M., & Gruninger , M.1996. Ontologies: principles, methods and applications. The Knowledge Engineering Review, 11(02), 93. https://doi.org/10.1017/S0269888900007797

    Google Scholar

    Uschold , M. & King , M.1995. Towards a methodology for building ontologies. Artificial Intelligence Applications Institute, 80(July), 275–280. https://doi.org/10.1.1.55.5357.

    Google Scholar

    Vrandečić , D., Pinto , S., Tempich , C. & Sure , Y.2005. The DILIGENT knowledge processes. Journal of Knowledge Management, 9(5), 85–96. https://doi.org/10.1108/13673270510622474.

    Google Scholar

    Welty , C. & Fikes , R.2006. A reusable ontology for fluents in OWL. In Proceedings of the 2006 Conference on Formal Ontology in Information Systems: Proceedings of the Fourth International Conference (FOIS 2006), 226–236. IOS Press. http://dl.acm.org/citation.cfm?id=1566079.1566106.

    Google Scholar

    Wick , M., Vatant , B. & Christophe , B.2015. Geonames ontology. http://www.Geonames.Org/Ontology.

    Google Scholar

    Yadav , U., Singh Narula , G., Duhan , N. & Jain , V.2016. Ontology engineering and development aspects: a survey. International Journal of Education and Management Engineering, 6(3), 9–19. https://doi.org/10.5815/ijeme.2016.03.02.

    Google Scholar

  • Cite this article

    Konstantinos I. Kotis, George A. Vouros, Dimitris Spiliotopoulos. 2020. Ontology engineering methodologies for the evolution of living and reused ontologies: status, trends, findings and recommendations. The Knowledge Engineering Review 35(1), doi: 10.1017/S0269888920000065
    Konstantinos I. Kotis, George A. Vouros, Dimitris Spiliotopoulos. 2020. Ontology engineering methodologies for the evolution of living and reused ontologies: status, trends, findings and recommendations. The Knowledge Engineering Review 35(1), doi: 10.1017/S0269888920000065

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RESEARCH ARTICLE   Open Access    

Ontology engineering methodologies for the evolution of living and reused ontologies: status, trends, findings and recommendations

Abstract: Abstract: The aim of this critical review paper is threefold: (a) to provide an insight on the impact of ontology engineering methodologies (OEMs) to the evolution of living and reused ontologies, (b) to update the ontology engineering (OE) community on the status and trends in OEMs and of their use in practice and (c) to propose a set of recommendations for working ontologists to consider during the life cycle of living, evolved and reused ontologies. The work outlined in this critical review paper has been motivated by the need to address critical issues on keeping ontologies alive and evolving while these are shared in wide communities. It is argued that the engineering of ontologies must follow a well-defined methodology, addressing practical aspects that would allow (sometimes wide) communities of experts and ontologists to reach consensus on developments and keep the evolution of ontologies ‘in track’. In doing so, specific collaborative and iterative tool-supported tasks and phases within a complete and evaluated ontology life cycle are necessary. This way the engineered ontologies can be considered ‘shared, commonly agreed and continuously evolved “live” conceptualizations’ of domains of discourse. Today, in the era of Linked Data and Knowledge Graphs, it is more necessary than ever not to neglect to consider the recommendations that OEMs explicitly and implicitly introduce and their implications to the evolution of living ontologies. This paper reports on the status of OEMs, identifies trends and provides recommendations based on the findings of an analysis that concerns the impact of OEMs to the status of well-known, widely used and representative ontologies.

    • The authors would like to acknowledge the significant contribution of the engineers of the SOs, as well as the authors of their related papers, who actively participated in this review by contributing their feedback on the description of their ontology used for the presented analysis. Specifically, the authors acknowledge the contribution of the following contributors and their collaborating ontologists/authors: Yannis Tzitzikas, John Breslin, Vincenzo Maltese, Antoine Zimmermann, Pascale Gaudet, Armin Haller, Milen Yankulov, Jean-Paul Calbimonte, Mcgibbney Lewis, Antonio de Nikola, Francesco Osborne, Mauro Dragoni, Evangelos Katis, Felipe Arakaki and Oscar Corcho.

    • In addition, we acknowledge the significant contribution of the respectful reviewers, experts in OE, for their valuable comments and suggestions.

    • http://www.geonames.org/

    • https://wordnet.princeton.edu/

    • http://multiwordnet.fbk.eu

    • https://www.google.com/docs/about/

    • cso.kmi.open.ac.uk

    • This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
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    Konstantinos I. Kotis, George A. Vouros, Dimitris Spiliotopoulos. 2020. Ontology engineering methodologies for the evolution of living and reused ontologies: status, trends, findings and recommendations. The Knowledge Engineering Review 35(1), doi: 10.1017/S0269888920000065
    Konstantinos I. Kotis, George A. Vouros, Dimitris Spiliotopoulos. 2020. Ontology engineering methodologies for the evolution of living and reused ontologies: status, trends, findings and recommendations. The Knowledge Engineering Review 35(1), doi: 10.1017/S0269888920000065
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