Architecture for the Automatic Creation and Enrichment of Ontologies from Linked Data
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Emergent Ontology, Architecture, Linked Data, Alignment, Web Service.
In smart environments (e.g.: smart cities) there are very diverse problems that must be addressed immediately; therefore, these environments must generate knowledge that allows them to respond to those particular needs, taking advantage of information from the context (e.g.: historical data, sensor measurement, problem description, among others). As a proposal for the timely generation of these knowledge bases, in this work an architecture is developed for allows to create and enrich emerging ontologies autonomously, using as input the linked data paradigm, which are data structures that are linked to each other. to serve both human users and other systems within the semantic web. This work specifies the services that offer the ability to generate emerging ontologies according to the problem that arises, seeking to learn the different axioms (concepts or properties) of the structures that the linked data sources used have. Then, these created ontologies are enriched/populated with the information that is extracted from the different linked data sources, to be returned to the requesting system automatically. For the development of this work, the MEDAWEDE methodology is used, which allows specifying this architecture, and conducting the construction of services to consume the sources described as linked data. Its six stages are used from this methodology: i) Specification: to analyze and select the ontological data sources to use. ii) Modeling: to implement the knowledge model of the study area of the ontologies to be generated. iii) Generation: to carry out the process of transformation, filtering, and integration of the data in the generated ontology. iv) Linking: to associate the data from the generated ontology with the knowledge from the linked data sets. v) Publication: to make the generated ontology available in the different standard formats. The exploitation stage is considered because it is dedicated to defining interfaces to access the ontology. The article also presents a case study focused on showing the process of generating an emerging ontology in the area of the Covid-19 pandemic, where the information available on the Internet is used through pre-existing ontologies and linked data sources.
T. R. Gruber, N. Guarino y R. Poli, "Formal ontology in conceptual analysis and knowledge representation," capítulo "Towards principles for the design of ontologies used for knowledge sharing" en Conceptual Analysis and Knowledge Representation, 1993.
I. Osman, S. B. Yahia, and G. Diallo, "Ontology integration: approaches and challenging issues," Information Fusion, vol. 71, pp. 38-63, 2021. DOI: https://doi.org/10.1016/j.inffus.2021.01.007
A. González-Eras, R. Dos Santos, J. Aguilar, and A. Lopez, "Ontological engineering for the definition of a COVID-19 pandemic ontology," Informatics in Medicine Unlocked, vol. 28, 100816, 2022. DOI: https://doi.org/10.1016/j.imu.2021.100816
O. El Bacha, O. Jmad, Y. El Bouzekri El Idrissi y N. Hmina, “Exploiting Open Data to Improve the Business Intelligence & Business Discovery Experience”. no 27 In Proceedings of the 2nd international Conference on Big Data, Cloud and Applications, (New York), pp 1– DOI: https://doi.org/10.1145/3090354.3090382
, March 2017.
A. Degbelo, "A snapshot of ontology evaluation criteria and strategies," in Proceedings of the 13th International Conference on Semantic Systems, septiembre de 2017, pp. 1-8. DOI: https://doi.org/10.1145/3132218.3132219
N. Guarino (Ed.), Formal ontology in information systems: Proceedings of the first international conference (FOIS'98), June 6-8, Trento, Italy, vol. 46, IOS press, 1998.
N. Piedra, J. Chicaiza, E. Cadme y R. Guaya, "Una aproximación basada en Linked Data para la detección de potenciales redes de colaboración científica a partir de la anotación semántica de producción científica: Piloto aplicado con producción científica de investigadores ecuatorianos," Maskana, vol. 5, 2014.
T. Rodríguez, R. D. Santos y J. Aguilar, "Metodología para el desarrollo de aplicaciones Web utilizando datos enlazados," in Conferencia Nacional de Computación, Informática Y Sistemas (CoNCISa 2017), vol. 5, pp. 978-980, 2017.
O. Hartig y A. Langegger, "A database perspective on consuming linked data on the web," Datenbank-Spektrum, vol. 10, pp. 57-66, octubre de 2010. DOI: https://doi.org/10.1007/s13222-010-0021-7
D. Fensel y C. Bussler, "The web service modeling framework WSMF," Electronic Commerce Research and Applications, vol. 1, no. 2, pp. 113-137, 2002. DOI: https://doi.org/10.1016/S1567-4223(02)00015-7
F. H. Vera-Rivera, E. Puerto, H. Astudillo y C. M. Gaona, "Microservices backlog–A genetic programming technique for identification and evaluation of microservices from user stories," IEEE Access, vol. 9, pp. 117178-117203, 2021. DOI: https://doi.org/10.1109/ACCESS.2021.3106342
B. Benatallah, F. Casati, and F. Toumani, "Analysis and Management of Web Service Protocols," in P. Atzeni, W. Chu, H. Lu, S. Zhou, and T. W. Ling (Eds.), Conceptual Modeling – ER 2004, vol. 3288, Lecture Notes in Computer Science, Springer, Berlin, Heidelberg. DOI: https://doi.org/10.1007/978-3-540-30464-7_40
M. Sánchez, J. Aguilar y E. Exposito, "Integración SOA-MAS en ambientes inteligentes," Dyna, vol. 85, no. 206, pp. 268-282, 2018. DOI: https://doi.org/10.15446/dyna.v85n206.68671
A. Alba, A. Coden, A. L. Gentile, D. Gruhl, P. Ristoski y S. Welch, “Multi-lingual concept extraction with linked data and human-in-the-loop”, no 24 In Proceedings of the Knowledge Capture Conference, pp. 1-8, (New York), December 2017. DOI: https://doi.org/10.1145/3148011.3148021
J. M. V. Carrero y E. Puerto, "GeoMotor: Design with nature. Recognition of geometries using a convolutional neural-network approach (CNN)," in ICGG 2020-Proceedings of the 19th International Conference on Geometry and Graphics, Springer International Publishing, 2021, pp. 916-919. DOI: https://doi.org/10.1007/978-3-030-63403-2_84
A. Dimou, T. De Nies, R. Verborgh, E. Mannens, P. Mechant y R. Van de Walle, "Automated metadata generation for Linked Data generation and publishing workflows," in Proceedings of LDOW2016, CEUR-WS.org, 2016, pp. 1-10.
S. Bischof, C. Martin, A. Polleres y P. Schneider, "Collecting, integrating, enriching and republishing open city data as linked data," in The Semantic Web-ISWC 2015: 14th International Semantic Web Conference, Bethlehem, PA, USA, October 11-15, 2015, Proceedings, Part II, vol. 14, pp. 57-75, Springer International Publishing. DOI: https://doi.org/10.1007/978-3-319-25010-6_4
M. Booshehri y P. Luksch, "Towards adding linked data to ontology learning layers," in Proceedings of the 16th International Conference on Information Integration and Web-based Applications & Services, diciembre de 2014, pp. 401-409. DOI: https://doi.org/10.1145/2684200.2684312
L. Zhao y R. Ichise, "Ontology integration for linked data," Journal on Data Semantics, vol. 3, pp. 237-254, 2014. DOI: https://doi.org/10.1007/s13740-014-0041-9
R. Dos Santos, J. Aguilar, and E. Puerto, "A Meta-Learning Architecture based on Linked Data," in Proc. XLVII Latin American Computing Conference (CLEI), 2021. DOI: https://doi.org/10.1109/CLEI53233.2021.9640223
In smart environments (e.g.: smart cities) there are very diverse problems that must be addressed immediately; therefore, these environments must generate knowledge that allows them to respond to those particular needs, taking advantage of information from the context (e.g.: historical data, sensor measurement, problem description, among others). As a proposal for the timely generation of these knowledge bases, in this work an architecture is developed for allows to create and enrich emerging ontologies autonomously, using as input the linked data paradigm, which are data structures that are linked to each other. to serve both human users and other systems within the semantic web. This work specifies the services that offer the ability to generate emerging ontologies according to the problem that arises, seeking to learn the different axioms (concepts or properties) of the structures that the linked data sources used have. Then, these created ontologies are enriched/populated with the information that is extracted from the different linked data sources, to be returned to the requesting system automatically. For the development of this work, the MEDAWEDE methodology is used, which allows specifying this architecture, and conducting the construction of services to consume the sources described as linked data. Its six stages are used from this methodology: i) Specification: to analyze and select the ontological data sources to use. ii) Modeling: to implement the knowledge model of the study area of the ontologies to be generated. iii) Generation: to carry out the process of transformation, filtering, and integration of the data in the generated ontology. iv) Linking: to associate the data from the generated ontology with the knowledge from the linked data sets. v) Publication: to make the generated ontology available in the different standard formats. The exploitation stage is considered because it is dedicated to defining interfaces to access the ontology. The article also presents a case study focused on showing the process of generating an emerging ontology in the area of the Covid-19 pandemic, where the information available on the Internet is used through pre-existing ontologies and linked data sources.
T. R. Gruber, N. Guarino y R. Poli, "Formal ontology in conceptual analysis and knowledge representation," capítulo "Towards principles for the design of ontologies used for knowledge sharing" en Conceptual Analysis and Knowledge Representation, 1993.
I. Osman, S. B. Yahia, and G. Diallo, "Ontology integration: approaches and challenging issues," Information Fusion, vol. 71, pp. 38-63, 2021. DOI: https://doi.org/10.1016/j.inffus.2021.01.007
A. González-Eras, R. Dos Santos, J. Aguilar, and A. Lopez, "Ontological engineering for the definition of a COVID-19 pandemic ontology," Informatics in Medicine Unlocked, vol. 28, 100816, 2022. DOI: https://doi.org/10.1016/j.imu.2021.100816
O. El Bacha, O. Jmad, Y. El Bouzekri El Idrissi y N. Hmina, “Exploiting Open Data to Improve the Business Intelligence & Business Discovery Experience”. no 27 In Proceedings of the 2nd international Conference on Big Data, Cloud and Applications, (New York), pp 1– DOI: https://doi.org/10.1145/3090354.3090382
, March 2017.
A. Degbelo, "A snapshot of ontology evaluation criteria and strategies," in Proceedings of the 13th International Conference on Semantic Systems, septiembre de 2017, pp. 1-8. DOI: https://doi.org/10.1145/3132218.3132219
N. Guarino (Ed.), Formal ontology in information systems: Proceedings of the first international conference (FOIS'98), June 6-8, Trento, Italy, vol. 46, IOS press, 1998.
N. Piedra, J. Chicaiza, E. Cadme y R. Guaya, "Una aproximación basada en Linked Data para la detección de potenciales redes de colaboración científica a partir de la anotación semántica de producción científica: Piloto aplicado con producción científica de investigadores ecuatorianos," Maskana, vol. 5, 2014.
T. Rodríguez, R. D. Santos y J. Aguilar, "Metodología para el desarrollo de aplicaciones Web utilizando datos enlazados," in Conferencia Nacional de Computación, Informática Y Sistemas (CoNCISa 2017), vol. 5, pp. 978-980, 2017.
O. Hartig y A. Langegger, "A database perspective on consuming linked data on the web," Datenbank-Spektrum, vol. 10, pp. 57-66, octubre de 2010. DOI: https://doi.org/10.1007/s13222-010-0021-7
D. Fensel y C. Bussler, "The web service modeling framework WSMF," Electronic Commerce Research and Applications, vol. 1, no. 2, pp. 113-137, 2002. DOI: https://doi.org/10.1016/S1567-4223(02)00015-7
F. H. Vera-Rivera, E. Puerto, H. Astudillo y C. M. Gaona, "Microservices backlog–A genetic programming technique for identification and evaluation of microservices from user stories," IEEE Access, vol. 9, pp. 117178-117203, 2021. DOI: https://doi.org/10.1109/ACCESS.2021.3106342
B. Benatallah, F. Casati, and F. Toumani, "Analysis and Management of Web Service Protocols," in P. Atzeni, W. Chu, H. Lu, S. Zhou, and T. W. Ling (Eds.), Conceptual Modeling – ER 2004, vol. 3288, Lecture Notes in Computer Science, Springer, Berlin, Heidelberg. DOI: https://doi.org/10.1007/978-3-540-30464-7_40
M. Sánchez, J. Aguilar y E. Exposito, "Integración SOA-MAS en ambientes inteligentes," Dyna, vol. 85, no. 206, pp. 268-282, 2018. DOI: https://doi.org/10.15446/dyna.v85n206.68671
A. Alba, A. Coden, A. L. Gentile, D. Gruhl, P. Ristoski y S. Welch, “Multi-lingual concept extraction with linked data and human-in-the-loop”, no 24 In Proceedings of the Knowledge Capture Conference, pp. 1-8, (New York), December 2017. DOI: https://doi.org/10.1145/3148011.3148021
J. M. V. Carrero y E. Puerto, "GeoMotor: Design with nature. Recognition of geometries using a convolutional neural-network approach (CNN)," in ICGG 2020-Proceedings of the 19th International Conference on Geometry and Graphics, Springer International Publishing, 2021, pp. 916-919. DOI: https://doi.org/10.1007/978-3-030-63403-2_84
A. Dimou, T. De Nies, R. Verborgh, E. Mannens, P. Mechant y R. Van de Walle, "Automated metadata generation for Linked Data generation and publishing workflows," in Proceedings of LDOW2016, CEUR-WS.org, 2016, pp. 1-10.
S. Bischof, C. Martin, A. Polleres y P. Schneider, "Collecting, integrating, enriching and republishing open city data as linked data," in The Semantic Web-ISWC 2015: 14th International Semantic Web Conference, Bethlehem, PA, USA, October 11-15, 2015, Proceedings, Part II, vol. 14, pp. 57-75, Springer International Publishing. DOI: https://doi.org/10.1007/978-3-319-25010-6_4
M. Booshehri y P. Luksch, "Towards adding linked data to ontology learning layers," in Proceedings of the 16th International Conference on Information Integration and Web-based Applications & Services, diciembre de 2014, pp. 401-409. DOI: https://doi.org/10.1145/2684200.2684312
L. Zhao y R. Ichise, "Ontology integration for linked data," Journal on Data Semantics, vol. 3, pp. 237-254, 2014. DOI: https://doi.org/10.1007/s13740-014-0041-9
R. Dos Santos, J. Aguilar, and E. Puerto, "A Meta-Learning Architecture based on Linked Data," in Proc. XLVII Latin American Computing Conference (CLEI), 2021. DOI: https://doi.org/10.1109/CLEI53233.2021.9640223