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  • 1.
    Abd Nikooie Pour, Mina
    et al.
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, Database and information techniques.
    Algergawy, Alsayed
    Friedrich Schiller University Jena, Germany.
    Amardeilh, Florence
    Elzeard.co, Paris, France.
    Amini, Reihaneh
    Data Semantics (DaSe) Laboratory, Kansas State University, USA.
    Fallatah, Omaima
    Information School, The University of Sheffield, Sheffield, UK.
    Faria, Daniel
    LASIGE, Faculdade de Ciencias, Universidade de Lisboa, Portugal .
    Fundulaki, Irini
    Institute of Computer Science-FORTH, Heraklion, Greece.
    Harrow, Ian
    Pistoia Alliance Inc., USA.
    Hertling, Sven
    University of Mannheim, Germany.
    Hitzler, Pascal
    Data Semantics (DaSe) Laboratory, Kansas State University, USA.
    Huschka, Martin
    Fraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut, EMI, Germany.
    Ibanescu, Liliana
    AgroParisTech, UMR MIA-Paris/INRAE, France.
    Jimenez-Ruiz, Ernesto
    City, University of London, UK and Department of Informatics, University of Oslo, Norway.
    Karam, Naouel
    Fraunhofer FOKUS, Berlin, Germany and Institute for Applied Informatics (InfAI), University of Leipzig, Germany.
    Laadhar, Amir
    Department of Computer Science, Aalborg University, Denmark.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology. University of Gävle, Sweden.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Li, Ying
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, Database and information techniques.
    Michel, Franck
    University Cote d’Azur, CNRS, Inria, France.
    Nasr, Engy
    Freiburg Galaxy Team, University of Freiburg, Germany.
    Paulheim, Heiko
    University of Mannheim, Germany.
    Pesquita, Catia
    LASIGE, Faculdade de Ciencias, Universidade de Lisboa, Portugal .
    Portisch, Jan
    University of Mannheim, Germany.
    Roussey, Catherine
    INRAE Centre Clermont-ARA, laboratoire TSCF, France.
    Saveta, Tzanina
    Institute of Computer Science-FORTH, Heraklion, Greece.
    Shvaiko, Pavel
    Trentino Digitale SpA, Trento, Italy.
    Splendiani, Andrea
    Pistoia Alliance Inc., USA.
    Trojahn, Cassia
    IRIT & Universite Toulouse II, Toulouse, France .
    Vatascinova, Jana
    Prague University of Economics and Business, Czech Republic.
    Yaman, Beyza
    ADAPT Centre, Dublin City University, Ireland.
    Zamazal, Ondrej
    Prague University of Economics and Business, Czech Republic.
    Zhou, Lu
    Data Semantics (DaSe) Laboratory, Kansas State University, USA.
    Results of theOntology Alignment Evaluation Initiative 20212021In: Proceedings of the 16th International Workshop on Ontology Matching: co-located with the 20th International Semantic Web Conference (ISWC 2021) / [ed] Pavel Shvaiko, Jérôme Euzenat, Ernesto Jiménez-Ruiz, Oktie Hassanzadeh, Cássia Trojahn, CEUR Workshop proceedings , 2021, p. 62-108Conference paper (Refereed)
    Abstract [en]

    The Ontology Alignment Evaluation Initiative (OAEI) aims at comparing ontology matching systems on precisely defined test cases. These test cases can be based on ontologies of different levels of complexity and use different evaluation modalities (e.g., blind evaluation, open evaluation, or consensus). The OAEI 2021 campaign offered 13 tracks and was attended by 21 participants.This paper is an overall presentation of that campaign.

  • 2.
    Abd Nikooie Pour, Mina
    et al.
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, Database and information techniques.
    Algergawy, Alsayed
    Friedrich Schiller University Jena, Germany.
    Amini, Reihaneh
    Kansas State University, USA.
    Faria, Daniel
    BioData.pt, INESC-ID, Lisbon, Portugal.
    Fundulaki, Irini
    Institute of Computer Science-FORTH, Heraklion, Greece.
    Harrow, Ian
    Pistoia Alliance Inc., USA.
    Hertling, Sven
    University of Mannheim, Germany.
    Jimenez-Ruiz, Ernesto
    City, University of London, UK, and , University of Oslo, Norway.
    Jonquet, Clement
    LIRMM, University of Montpellier & CNRS, France.
    Karam, Naouel
    Fraunhofer FOKUS, Berlin, Germany.
    Khiat, Abderrahmane
    Fraunhofer IAIS, Sankt Augustin, Germany.
    Laadhar, Amir
    LIRMM, University of Montpellier & CNRS, France.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Li, Ying
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, Database and information techniques.
    Hitzler, Pascal
    Kansas State University, USA.
    Paulheim, Heiko
    University of Mannheim, Germany.
    Pesquita, Catia
    Universidade de Lisboa, Portugal.
    Saveta, Tzanina
    Institute of Computer Science-FORTH, Heraklion, Greece.
    Shvaiko, Pavel
    TasLab, Trentino Digitale SpA, Trento, Italy.
    Splendiani, Andrea
    Pistoia Alliance Inc., USA.
    Thieblin, Elodie
    Logilab, France.
    Trojahn, Cassia
    IRIT & Universite Toulouse II, Toulouse, France.
    Vatascinova, Jana
    University of Economics, Prague, Czech Republic.
    Yaman, Beyza
    Dublin City University, Ireland.
    Zamazal, Ondrej
    University of Economics, Prague, Czech Republic.
    Zhou, Lu
    Kansas State University, USA.
    Results of theOntology Alignment Evaluation Initiative 20202020In: Proceedings of the 15th International Workshop on Ontology Matching: co-located with the 19th International Semantic Web Conference (ISWC 2020) / [ed] Pavel Shvaiko, Jérôme Euzenat, Ernesto Jiménez-Ruiz, Oktie Hassanzadeh, Cássia Trojahn, Aachen, Germany: CEUR Workshop proceedings , 2020, p. 92-138Conference paper (Refereed)
    Abstract [en]

    The Ontology Alignment Evaluation Initiative (OAEI) aims at comparing ontology matching systems on precisely defined test cases. These test cases can be based on ontologies of different levels of complexity and use different evaluation modalities (e.g., blind evaluation, open evaluation, or consensus).The OAEI 2020 campaign offered 12 tracks with 36 test cases, and was attended by 19 participants. This paper is an overall presentation of that campaign. 

  • 3.
    Abd Nikooie Pour, Mina
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Algergawy, Alsayed
    Heinz Nixdorf Chair for Distributed Information Systems, Friedrich Schiller University Jena, Germany; Chair of Data and Knowledge Engineering, University of Passau, Germany.
    Buche, Patrice
    UMR IATE, INRAE, University of Montpellier, France.
    Castro, Leyla J.
    ZB MED Information Centre for Life Sciences, Germany.
    Chen, Jiaoyan
    Department of Computer Science, The University of Manchester, UK.
    Coulet, Adrien
    Inria Paris, France; Centre de Recherche des Cordeliers, Inserm, Université Paris Cité, Sorbonne Université, France.
    Cufi, Julien
    UMR IATE, INRAE, University of Montpellier, France.
    Dong, Hang
    Department of Computer Science, University of Oxford, UK.
    Fallatah, Omaima
    Department of Data Science, Umm Al-Qura University, Saudi Arabia.
    Faria, Daniel
    INESC-ID / IST, University of Lisbon, Portugal.
    Fundulaki, Irini
    Institute of Computer Science-FORTH, Heraklion, Greece.
    Hertling, Sven
    Data and Web Science Group, University of Mannheim, Germany.
    He, Yuan
    Department of Computer Science, University of Oxford, UK.
    Horrocks, Ian
    Department of Computer Science, University of Oxford, UK.
    Huschka, Martin
    Fraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut, EMI, Germany.
    Ibanescu, Liliana
    Université Paris-Saclay, INRAE, AgroParisTech, UMR MIA Paris-Saclay, France.
    Jain, Sarika
    National Institute of Technology Kurukshetra, India.
    Jiménez-Ruiz, Ernesto
    City, University of London, UK; SIRIUS, University of Oslo, Norway.
    Karam, Naouel
    Institute for Applied Informatics, University of Leipzig, Germany.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Li, Ying
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Monnin, Pierre
    University Côte d’Azur, Inria, CNRS, I3S, France.
    Nasr, Engy
    Albert Ludwig University of Freiburg, Germany.
    Paulheim, Heiko
    Data and Web Science Group, University of Mannheim, Germany.
    Pesquita, Catia
    LASIGE, Faculdade de Ciências, Universidade de Lisboa, Portugal.
    Saveta, Tzanina
    Institute of Computer Science-FORTH, Heraklion, Greece.
    Shvaiko, Pavel
    Trentino Digitale SpA, Trento, Italy.
    Sousa, Guilherme
    Institut de Recherche en Informatique de Toulouse, France.
    Trojahn, Cássia
    Institut de Recherche en Informatique de Toulouse, France.
    Vatascinova, Jana
    Prague University of Economics and Business, Czech Republic.
    Wu, Mingfang
    Australian Research Data Commons.
    Yaman, Beyza
    ADAPT Centre, Trinity College Dublin.
    Zamazal, Ondřej
    Prague University of Economics and Business, Czech Republic.
    Zhou, Lu
    Flatfee Corp, USA.
    Results of the Ontology Alignment Evaluation Initiative 20232023In: Proceedings of the 18th International Workshop on Ontology Matching co-located with the 22nd International Semantic Web Conference (ISWC 2023), Athens, Greece, November 7, 2023. / [ed] Pavel Shvaiko, Jérôme Euzenat, Ernesto Jiménez-Ruiz, Oktie Hassanzadeh, Cássia Trojahn, CEUR Workshop Proceedings , 2023, Vol. 3591, p. 97-139Conference paper (Refereed)
  • 4.
    Abd Nikooie Pour, Mina
    et al.
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, Database and information techniques.
    Algergawy, Alsayed
    Heinz Nixdorf Chair for Distributed Information Systems, Friedrich Schiller University Jena, Germany.
    Buche, Patrice
    UMR IATE, INRAE, University of Montpellier, France.
    Castro, Leyla J.
    ZB MED Information Centre for Life Sciences, Germany.
    Chen, Jiaoyan
    Department of Computer Science, The University of Manchester, UK.
    Dong, Hang
    Department of Computer Science, University of Oxford, UK.
    Fallatah, Omaima
    Information School, The University of Sheffield, Sheffield, UK.
    Faria, Daniel
    University of Lisbon, Portugal.
    Fundulaki, Irini
    Institute of Computer Science-FORTH, Heraklion, Greece.
    Hertling, Sven
    Data and Web Science Group, University of Mannheim, Germany.
    He, Yuan
    Department of Computer Science, University of Oxford, UK.
    Horrocks, Ian
    Department of Computer Science, University of Oxford, UK.
    Huschka, Martin
    Fraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut, EMI, Germany.
    Ibanescu, Liliana
    Universite Paris-Saclay, INRAE, AgroParisTech, UMR MIA Paris-Saclay, France.
    Jimenez-Ruiz, Ernesto
    City, University of London, UK & SIRIUS, University of Oslo, Norway.
    Karam, Naouel
    Fraunhofer FOKUS & Institute for Applied Informatics, University of Leipzig, Germany.
    Laadhar, Amir
    University of Stuttgart, Germany.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology. Högskolan i Gävle.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Li, Ying
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, Database and information techniques.
    Michel, Franck
    University Cote d’Azur, CNRS, Inria.
    Nasr, Engy
    Albert Ludwig University of Freiburg, Germany.
    Paulheim, Heiko
    Data and Web Science Group, University of Mannheim, Germany.
    Pesquita, Catia
    LASIGE, Faculdade de Ciencias, Universidade de Lisboa, Portugal.
    Saveta, Tzanina
    Institute of Computer Science-FORTH, Heraklion, Greece.
    Shvaiko, Pavel
    Trentino Digitale SpA, Trento, Italy.
    Trojahn, Cassia
    Institut de Recherche en Informatique de Toulouse, France.
    Verhey, Chantelle
    World Data System, International Technology Office, USA.
    Wu, Mingfang
    Australian Research Data Commons.
    Yaman, Beyza
    ADAPT Centre, Trinity College Dublin.
    Zamazal, Ondrej
    Prague University of Economics and Business, Czech Republic.
    Zhou, Lu
    TigerGraph, Inc. USA.
    Results of the Ontology Alignment EvaluationInitiative 20222022In: Proceedings of the 17th International Workshop on Ontology Matching (OM 2022): co-located with the 21th International Semantic Web Conference (ISWC 2022) / [ed] Pavel Shvaiko, Jerome Euzenat, Ernesto Jimenez-Ruiz, Oktie Hassanzadeh, Cassia Trojahn, CEUR Workshop Proceedings , 2022, p. 84-128Conference paper (Refereed)
    Abstract [en]

    The Ontology Alignment Evaluation Initiative (OAEI) aims at comparing ontology matching systems on precisely defined test cases. These test cases can be based on ontologies of different levels of complexity and use different evaluation modalities. The OAEI 2022 campaign offered 14 tracks and was attended by18 participants. This paper is an overall presentation of that campaign

  • 5.
    Abd Nikooie Pour, Mina
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Armiento, Rickard
    Linköping University, Department of Physics, Chemistry and Biology, Theoretical Physics. Linköping University, Faculty of Science & Engineering.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. Högskolan i Gävle, Gävle, Sweden.
    A First Step towards a Tool for Extending Ontologies2021In: Proceedings of the Sixth International Workshop on the Visualization and Interaction for Ontologies and Linked Data: co-located with the 20th International Semantic Web Conference (ISWC 2021) / [ed] Patrick Lambrix, Catia Pesquita, Vitalis Wiens, CEUR Workshop proceedings , 2021, p. 1-12Conference paper (Refereed)
    Abstract [en]

    Ontologies have been proposed as a means towards making data FAIR (Findable, Accessible, Interoperable, Reusable). This has attracted much interest in several communities and ontologies are being developed. However, to obtain good results when using ontologies in semantically-enabled applications, the ontologies need to be of high quality. One of the quality aspects is that the ontologies should be as complete as possible. In this paper we propose a first version of a tool that supports users in extending ontologies using a phrase-based approach.  To demonstrate the usefulness of our proposed tool, we exemplify the use by extending the Materials Design Ontology.

  • 6.
    Abd Nikooie Pour, Mina
    et al.
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, Database and information techniques.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Armiento, Rickard
    Linköping University, Department of Physics, Chemistry and Biology, Theoretical Physics. Linköping University, Faculty of Science & Engineering.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    A First Step towards Extending the Materials Design Ontology2021In: Workshop on Domain Ontologies for Research Data Management in Industry Commons of Materials and Manufacturing - DORIC-MM 2021 / [ed] S Chiacchiera, MT Horsch, J Francisco Morgado, G Goldbeck, 2021, p. 1-11Conference paper (Refereed)
    Abstract [en]

    Ontologies have been proposed as a means towards making data FAIR (Findable, Accessible, Interoperable, Reusable) and has recently attracted much interest in the materials science community. Ontologies for this domain are being developed and one such effort is the Materials Design Ontology. However, to obtain good results when using ontologies in semantically-enabled applications, the ontologies need to be of high quality. One of the quality aspects is that the ontologies should be as complete as possible. In this paper we show preliminary results regarding extending the Materials Design Ontology using a phrase-based topic model.

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  • 7.
    Abd Nikooie Pour, Mina
    et al.
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, Database and information techniques. Swedish e-Science Research Centre, Sweden.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. Swedish e-Science Research Centre, Sweden.
    Armiento, Rickard
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Physics, Chemistry and Biology, Theoretical Physics. Swedish e-Science Research Centre, Sweden.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. Swedish e-Science Research Centre, Sweden; University of Gävle, Sweden.
    Phrase2Onto: A Tool to Support Ontology Extension2023In: 27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems (KES 2023) / [ed] Robert Howlett, Elsevier, 2023, p. 1415-1424Conference paper (Refereed)
    Abstract [en]

    Due to importance of data FAIRness (Findable, Accessible, Interoperable, Reusable), ontologies as a means to make data FAIR have attracted more and more attention in different communities and are being used in semantically-enabled applications. However, to obtain good results while using ontologies in these applications, high quality ontologies are needed of which completeness is one of the important aspects. An ontology lacking information can lead to missing results. In this paper we present a tool, Phrase2Onto, that supports users in extending ontologies to make the ontologies more complete. It is particularly suited for ontology extension using a phrase-based topic model approach, but the tool can support any extension approach where a user needs to make decisions regarding the appropriateness of using phrases to define new concepts. We describe the functionality of the tool and a user study using Pizza Ontology. The user study showed  a good usability of the system and high task completion. Further, we report on a real application where we extend the Materials Design Ontology.

  • 8.
    Achichi, Manel
    et al.
    Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier (LIRMM), France; University of Montpellier, France.
    Cheatham, Michelle
    Wright State University, USA.
    Dragisic, Zlatan
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Euzenat, Jerome
    INRIA, France; University Grenoble Alpes, Grenoble, France.
    Faria, Daniel
    Instituto Gulbenkian de Ciencia, Lisbon, Portugal.
    Ferrara, Alfio
    Universita degli studi di Milano, Italy.
    Flouris, Giorgos
    Institute of Computer Science-FORTH, Heraklion, Greece.
    Fundulaki, Irini
    Institute of Computer Science-FORTH, Heraklion, Greece.
    Harrow, Ian
    Pistoia Alliance Inc., USA.
    Ivanova, Valentina
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Jimenez-Ruiz, Ernesto
    University of Oslo, Norway.
    Kolthoff, Kristian
    University of Mannheim, Germany.
    Kuss, Elena
    University of Mannheim, Germany.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Leopold, Henrik
    Vrije Universiteit Amsterdam, Netherlands.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Meilicke, Christian
    University of Mannheim, Germany.
    Mohammadi, Majid
    Technical University of Delft, Netherlands.
    Montanelli, Stefano
    Universita degli studi di Milano, Italy.
    Pesquita, Catia
    Universidade de Lisboa, Portugal.
    Saveta, Tzanina
    Institute of Computer Science-FORTH, Heraklion, Greece.
    Shvaiko, Pavel
    Informatica Trentina, Trento, Italy.
    Splendiani, Andrea
    Pistoia Alliance Inc., USA.
    Stuckenschmidt, Heiner
    University of Mannheim, Germany.
    Thieblin, Elodie
    Institut de Recherche en Informatique de Toulouse (IRIT), France; Universite Toulouse II, Toulouse, France.
    Todorov, Konstantin
    Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier (LIRMM), France; University of Montpellier, France.
    Trojahn, Cassia
    Institut de Recherche en Informatique de Toulouse (IRIT); Universite Toulouse II, Toulouse, France.
    Zamazal, Ondrej
    University of Economics, Prague, Czech Republic.
    Results of the Ontology Alignment Evaluation Initiative 20172017In: Proceedings of the 12th International Workshop on Ontology Matching co-located with the 16th International Semantic Web Conference (ISWC 2017) / [ed] Pavel Shvaiko, Jerome Euzenat, Ernesto Jimenez-Ruiz, Michelle Cheatham, Oktie Hassanzadeh, Aachen, Germany: CEUR Workshop Proceedings , 2017, p. 61-113Conference paper (Refereed)
  • 9.
    Achichi, Manel
    et al.
    LIRMM, University of Montpellier, France.
    Cheatham, Michelle
    Wright State University, USA.
    Dragisic, Zlatan
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Euzenat, Jerome
    INRIA, France; Univ. Grenoble Alpes, Grenoble, France.
    Faria, Daniel
    Instituto Gulbenkian de Ciencia, Lisbon, Portugal.
    Ferrara, Alfio
    Universita degli studi di Milano, Italy.
    Flouris, Giorgos
    Institute of Computer Science-FORTH, Heraklion, Greece.
    Fundulaki, Irini
    Institute of Computer Science-FORTH, Heraklion, Greece.
    Harrow, Ian
    Pistoia Alliance Inc., USA.
    Ivanova, Valentina
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Jiménez-Ruiz, Ernesto
    University of Oslo, Norway; University of Oxford, UK.
    Kuss, Elena
    University of Mannheim, Germany.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Leopold, Henrik
    Vrije Universiteit Amsterdam, The Netherlands.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Meilicke, Christian
    University of Mannheim, Germany.
    Montanelli, Stefano
    Universita degli studi di Milano, Italy.
    Pesquita, Catia
    Universidade de Lisboa, Portugal.
    Saveta, Tzanina
    Institute of Computer Science-FORTH, Heraklion, Greece.
    Shvaiko, Pavel
    TasLab, Informatica Trentina, Trento, Italy.
    Splendiani, Andrea
    Novartis Institutes for Biomedical Research, Basel, Switzerland.
    Stuckenschmidt, Heiner
    University of Mannheim, Germany.
    Todorov, Konstantin
    LIRMM, University of Montpellier, France.
    Trojahn, Cassia
    IRIT, Toulouse, France; Université Toulouse II, Toulouse, France.
    Zamazal, Ondřej
    University of Economics, Prague, Czech Republic.
    Results of the Ontology Alignment Evaluation Initiative 20162016In: Proceedings of the 11th International Workshop on Ontology Matching, Aachen, Germany: CEUR Workshop Proceedings , 2016, p. 73-129Conference paper (Refereed)
  • 10.
    Algergawy, Alsayed
    et al.
    Friedrich Schiller University Jena, Germany.
    Cheatham, Michelle
    Wright State University, USA.
    Faria, Daniel
    Instituto Gulbenkian de Ciencia, Lisbon, Portugal.
    Ferrara, Alfio
    Universita degli studi di Milano, Italy.
    Fundulaki, Irina
    FORTH, Greece.
    Harrow, Ian
    Pistoia Alliance Inc., USA.
    Hertling, Sven
    University of Mannheim, Germany.
    Jimenez-Ruiz, Ernesto
    Alan Turing Institute, London, UK; University of Oslo, Norway.
    Karam, Naouel
    Fraunhofer FOKUS, Berlin, Germany.
    Khiat, Abderrahman
    Freie Universität Berlin, Germany.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Montanelli, Stefano
    Universita degli studi di Milano, Italy.
    Paulheim, Heiko
    University of Mannheim, Germany.
    Pesquita, Catia
    Universidade de Lisboa, Portugal.
    Saveta, Tzanina
    FORTH, Greece.
    Schmidt, Daniela
    Pontifical Catholic University of Rio Grande do Sul, Brazil.
    Shvaiko, Pavel
    Trentino Digitale SpA, Trento, Italy.
    Splendiani, Andrea
    Pistoia Alliance Inc., USA.
    Thiéblin, Elodie
    IRIT, France; Université Toulouse II, Toulouse, France.
    Trojahn, Cassia
    IRIT, France; Université Toulouse II, Toulouse, France.
    Vatascinova, Jana
    University of Economics, Prague, Czech Republic.
    Zamazal, Ondrej
    University of Economics, Prague, Czech Republic.
    Zhou, Lu
    Wright State University, USA.
    Results of the Ontology Alignment Evaluation Initiative 20182018In: Proceedings of the 13th International Workshop on Ontology Matching: co-located with the 17th International Semantic Web Conference (ISWC 2018) / [ed] Pavel Shvaiko, Jérôme Euzenat, Ernesto Jiménez-Ruiz, Michelle Cheatham, Oktie Hassanzadeh, Aachen, Germany: CEUR Workshop Proceedings , 2018, Vol. 2288, p. 76-116Conference paper (Refereed)
    Abstract [en]

    The Ontology Alignment Evaluation Initiative (OAEI) aims at comparing ontology matching systems on precisely defined test cases. These test cases can be based on ontologies of different levels of complexity (from simple thesauri to expressive OWL ontologies) and use different evaluation modalities (e.g., blind evaluation, open evaluation, or consensus). The OAEI 2018 campaign offered 12 tracks with 23 test cases, and was attended by 19 participants. This paper is an overall presentation of that campaign.

  • 11.
    Algergawy, Alsayed
    et al.
    Friedrich Schiller University Jena, Germany .
    Faria, Daniel
    BioData.pt, INESC-ID, Lisbon, Portugal .
    Ferrara, Alfio
    Universita degli studi di Milano, Italy .
    Fundulaki, Irini
    Institute of Computer Science-FORTH, Heraklion, Greece .
    Harrow, Ian
    Pistoia Alliance Inc., USA .
    Hertling, Sven
    University of Mannheim, Germany .
    Jimenez-Ruiz, Ernesto
    City University of London, UK and University of Oslo, Norway .
    Karam, Naouel
    Fraunhofer FOKUS, Berlin, Germany .
    Khiat, Abderrahmane
    Fraunhofer IAIS, Sankt Augustin, Bonn, Germany.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Montanelli, Stefano
    Universita degli studi di Milano, Italy .
    Paulheim, Heiko
    University of Mannheim, Germany.
    Pesquita, Catia
    LASIGE, Faculdade de Ciencias, Universidade de Lisboa, Portugal .
    Saveta, Tzanina
    Institute of Computer Science-FORTH, Heraklion, Greece .
    Shvaiko, Pavel
    TasLab, Trentino Digitale SpA, Trento, Italy .
    Splendiani, Andrea
    Pistoia Alliance Inc., USA.
    Thieblin, Elodie
    IRIT & Universite Toulouse II, Toulouse, France .
    Trojahn, Cassia
    IRIT & Universite Toulouse II, Toulouse, France .
    Vatascinova, Jana
    University of Economics, Prague, Czech Republic .
    Zamazal, Ondrej
    University of Economics, Prague, Czech Republic .
    Zhou, Lu
    Kansas State University, USA .
    Results of the Ontology Alignment Evaluation Initiative 20192019In: Proceedings of the 14th International Workshop on Ontology Matchingco-located with the 18th International Semantic Web Conference (ISWC 2019) / [ed] Pavel Shvaiko, Jérôme Euzenat, Ernesto Jiménez-Ruiz, Oktie Hassanzadeh, Cássia Trojahn,, Aachen: CEUR Workshop Proceedings , 2019, p. 46-85Conference paper (Refereed)
    Abstract [en]

    The Ontology Alignment Evaluation Initiative (OAEI) aims at comparing ontology matching systems on precisely defined test cases. These test cases can be based on ontologies of different levels of complexity (from simple thesauri to expressive OWL ontologies) and use different evaluation modalities (e.g., blind evaluation,open evaluation, or consensus). The OAEI2019 campaign offered 11 tracks with 29 test cases, and was attended by 20 participants. This paper is an overall presentation of that campaign.

  • 12.
    Blomqvist, Eva
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. Swedish e-Science Research Centre.
    Keskisärkkä, Robin
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, Human-Centered systems.
    Lindecrantz, Mikael
    Ragn-Sells AB, Sweden.
    Abd Nikooie Pour, Mina
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, Database and information techniques. Swedish e-Science Research Centre.
    Li, Ying
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, Database and information techniques. Swedish e-Science Research Centre.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. Swedish e-Science Research Centre.
    Cross-domain Modelling - A Network of Core Ontologies for the Circular Economy2023In: Proceedings of the 14th Workshop on Ontology Design and Patterns (WOP 2023): co-located with the 22nd International Semantic Web Conference (ISWC 2023) / [ed] Raghava Mutharaju, Agnieszka Ławrynowicz, Pramit Bhattacharyya, Eva Blomqvist, Luigi Asprino, Gunjan Singh, Aachen, Germany: CEUR Workshop Proceedings , 2023Conference paper (Refereed)
    Abstract [en]

    Circular Economy (CE) aims to reduce value loss and avoid waste by extending the life of products,components, and materials. Circular value networks (CVN), i.e. networks of actors realising partsof the CE, are often complex and involving a multitude of actors, such as suppliers, manufacturers,recyclers, and end-users, from different industry sectors. In addition, the networks enable and managevarious flows of resources, energy, information and value. To set up and operate such networks, datasharing is essential, however, one of the main challenges is semantic interoperability, and as a resultdata are difficult to understand, integrate, and use. Ontologies support semantic interoperability, andcan represent domain knowledge and enable stakeholders to communicate. However, the knowledgedomains involved are many, including sustainability, materials, products, manufacturing, and logistics,where well-established ontologies already exist. In addition, these domains need to be connected torelevant industry sectors. In order to bridge these domains we propose a set of core ontology modules,allowing to express links between existing ontologies as well as filling gaps related to core CE concepts.

  • 13.
    Dragisic, Zlatan
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Ivanova, Valentina
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Experiences from the Anatomy track in the Ontology Alignment Evaluation Initiative2017In: Journal of Biomedical Semantics, E-ISSN 2041-1480, Vol. 8, article id 56Article, review/survey (Refereed)
    Abstract [en]

    Background: One of the longest running tracks in the Ontology Alignment Evaluation Initiative is the Anatomy track which focuses on aligning two anatomy ontologies. The Anatomy track was started in 2005. In 2005 and 2006 the task in this track was to align the Foundational Model of Anatomy and the OpenGalen Anatomy Model. Since 2007 the ontologies used in the track are the Adult Mouse Anatomy and a part of the NCI Thesaurus. Since 2015 the data in the Anatomy track is also used in the Interactive track of the Ontology Alignment Evaluation Initiative.

    Results: In this paper we focus on the Anatomy track in the years 2007-2016 and the Anatomy part of the Interactive track in 2015-2016. We describe the data set and the changes it went through during the years. Further, we give an overview of all systems that participated in the track and the techniques they have used. We discuss the performance results of the systems and summarize the general trends.

    Conclusions: About 50 systems have participated in the Anatomy track. Many different techniques were used. The most popular matching techniques are string-based strategies and structure-based techniques. Many systems also use auxiliary information. The quality of the alignment has increased for the best performing systems since the beginning of the track and more and more systems check the coherence of the proposed alignment and implement a repair strategy.Further, interacting with an oracle is beneficial.

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  • 14.
    Fu, Bo
    et al.
    California State University Long Beach, USA.
    Lambrix, PatrickLinköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.Li, HuanyuLinköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.Nunes, SusanaLASIGE, Faculdade de Ciências, University of Lisbon, Portugal.Pesquita, CatiaLASIGE, Faculdade de Ciências, University of Lisbon, Portugal.
    Proceedings of the 8th International Workshop on the Visualization and Interaction for Ontologies, Linked Data and Knowledge Graphs: co-located with the 22nd International Semantic Web Conference (ISWC 2023)2023Conference proceedings (editor) (Refereed)
  • 15.
    Jimenez-Ruiz, Ernesto
    et al.
    The Alan Turing Institute, London, United Kingdom; University of Oslo, Norway.
    Saveta, Tzanina
    Institute of Computer Science - FORTH, Greece.
    Zamazal, Ondrej
    University of Economics, Prague, Czech Republic.
    Hertling, Sven
    University of Mannheim, Germany.
    Röder, Michael
    Paderborn University, Germany.
    Fundulaki, Irini
    Institute of Computer Science - FORTH, Greece.
    Ngonga Ngomo, Axel-Cyrille
    Paderborn University, Germany.
    Sherif, Mohamed Ahmed
    Paderborn University, Germany.
    Annane, Amina
    Ecole nationale Superieure d’Informatique, Alger, Algerie; Université de Montpellier, France.
    Bellahsene, Zohra
    Université de Montpellier, France.
    Ben Yahia, Sadok
    Université de Tunis El Manar. Tunisia.
    Diallo, Gayo
    University of Bordeaux, France.
    Faria, Daniel
    Instituto Gulbenkian de Ciˆencia, Portugal.
    Kachroudi, Marouen
    University of Bordeaux, France.
    Khiat, Abderrahmane
    Freie Universitat Berlin, Germany.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Mackeprang, Maximilian
    Freie Universitat Berlin, Germany.
    Mohammadi, Majid
    Delft University of Technology, The Netherlands.
    Rybinski, Maciej
    University of Malaga, Spain.
    Sowkarthiga Balasubramani, Booma
    University of Illinois at Chicago, USA.
    Trojahn, Cassia
    Institut de Recherche en Informatique de Toulouse, France.
    Introducing the HOBBIT platform into the Ontology Alignment Evaluation Campaign2018In: Proceedings of the 13th International Workshop on Ontology Matching: co-located with the 17th International Semantic Web Conference (ISWC 2018) / [ed] Pavel Shvaiko, Jérôme Euzenat, Ernesto Jiménez-Ruiz, Michelle Cheatham, Oktie Hassanzadeh, Aachen, Germany: CEUR Workshop Proceedings , 2018, Vol. 2288, p. 49-60Conference paper (Refereed)
    Abstract [en]

    This paper describes the Ontology Alignment Evaluation Initiative 2017.5 pre-campaign. Like in 2012, when we transitioned the evaluation to the SEALS platform, we have also conducted a pre-campaign to assess the feasibility of moving to the HOBBIT platform. We report the experiences of this pre-campaign and discuss the future steps for the OAEI.

  • 16.
    Keskisärkkä, Robin
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Cheng, Sijin
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, Database and information techniques.
    Carlsson, Niklas
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    An Ontology for Ice Hockey2019In: ISWC 2019 Satellites: Proceedings of the ISWC 2019 Satellite Tracks (Posters & Demonstrations, Industry, and Outrageous Ideas) co-located with 18th International Semantic Web Conference (ISWC 2019), 2019, p. 13-16Conference paper (Refereed)
    Abstract [en]

    Ice hockey is a highly popular sport that has seen significant increase in the use of sport analytics. To aid in such analytics, most major leagues collect and share increasing amounts of play-by-play data and other statistics. Additionally, some websites specialize in making such data available to the public in user-friendly forms. However, these sites fail to capture the semantic information of the data, and cannot be used to support more complex data requirements. In this paper, we present the design and development of an ice hockey ontology that provides improved knowledge representation, enables intelligent search and information acquisition, and helps when using information from multiple databases. Our ontology is substantially larger than previous ice hockey ontologies (that cover only a small part of the domain) and provides a formal and explicit representation of the ice hockey domain, supports information retrieval, data reuse, and complex performance metrics.

  • 17.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Armiento, Rickard
    Linköping University, Department of Physics, Chemistry and Biology, Theoretical Physics. Linköping University, Faculty of Science & Engineering.
    Delin, Anna
    School of Science and Engineering (SCI) at the Royal Institute of Technology, KTH, Sweden.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Big Semantic Data Processing in the Materials Design Domain2018In: Encyclopedia of Big Data Technologies / [ed] Sherif Sakr and Albert Zomaya, Cham: Springer, 2018Chapter in book (Refereed)
    Abstract [en]

    To speed up the progress in the field of materials design, a number of challenges related to big data need to be addressed. This entry discusses these challenges and shows the semantic technologies that alleviate the problems related to variety, variability, and veracity.

  • 18.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. Swedish e-Science Research Centre; University of Gävle, Gävle, Sweden.
    Armiento, Rickard
    Linköping University, Department of Physics, Chemistry and Biology, Theoretical Physics. Linköping University, Faculty of Science & Engineering. Swedish e-Science Research Centre.
    Delin, Anna
    Swedish e-Science Research Centre; Royal Institute of Technology, Stockholm.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. Swedish e-Science Research Centre.
    FAIR Big Data in the Materials Design Domain2022In: Encyclopedia of Big Data Technologies / [ed] Zomaya A, Taheri J, Sakr S, Cham: Springer, 2022Chapter in book (Refereed)
    Abstract [en]

    To speed up the progress in the field of materials design, a number of challenges related to big data need to be addressed. This entry discusses these challenges and shows the semantic technologies that alleviate the problems related to Variety, Variability, Veracity and FAIRness.

  • 19.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. The Swedish e-Science Research Centre, Linköping University, Sweden; Department of Building Engineering, Energy Systems and Sustainability Science, University of Gävle, Sweden.
    Armiento, Rickard
    Linköping University, Department of Physics, Chemistry and Biology, Theoretical Physics. Linköping University, Faculty of Science & Engineering. The Swedish e-Science Research Centre, Linköping University.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. The Swedish e-Science Research Centre, Linköping University.
    Hartig, Olaf
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Abd Nikooie Pour, Mina
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. The Swedish e-Science Research Centre, Linköping University.
    Li, Ying
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. The Swedish e-Science Research Centre, Linköping University.
    The materials design ontology2024In: Semantic Web, ISSN 1570-0844, E-ISSN 2210-4968, Vol. 15, no 2, p. 481-515Article in journal (Refereed)
    Abstract [en]

    In the materials design domain, much of the data from materials calculations is stored in different heterogeneous databases with different data and access models. Therefore, accessing and integrating data from different sources is challenging. As ontology-based access and integration alleviates these issues, in this paper we address data access and interoperability for computational materials databases by developing the Materials Design Ontology. This ontology is inspired by and guided by the OPTIMADE effort that aims to make materials databases interoperable and includes many of the data providers in computational materials science. In this paper, first, we describe the development and the content of the Materials Design Ontology. Then, we use a topic model-based approach to propose additional candidate concepts for the ontology. Finally, we show the use of the Materials Design Ontology by a proof-of-concept implementation of a data access and integration system for materials databases based on the ontology.

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  • 20. Order onlineBuy this publication >>
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Ontology-Driven Data Access and Data Integration with an Application in the Materials Design Domain2022Doctoral thesis, monograph (Other academic)
    Abstract [en]

    The Semantic Web aims to make data on the web machine-readable by introducing semantics to the data. Ontologies are one of the critical technologies in the Semantic Web. Ontologies, which provide a formal definition of a domain of interest, can play an important role in enabling semantics-aware data access and data integration over heterogeneous data sources. Traditionally, ontology-based data access and integration methods focus on data that follows relational data models. However, in some domains, such as materials design, the models that data follows and the methods by which it is shared differ today. Data may be based on different data models (i.e., relational models and non-relational models) and may be shared in different ways (e.g., as tabular data via SQL queries or API (Application Programming Interface) requests, or as JSON-formatted data via API requests). To address these challenges, conventional ontology-based data access and integration approaches must be adapted. The recently developed GraphQL, a framework for building APIs, is an interesting candidate for providing such an approach, although the use of GraphQL for integration has not yet been studied.

    In this thesis, we propose a GraphQL-based framework for data access and integration. As part of this framework, we propose and implement a novel approach that enables automatic generation of GraphQL servers based on ontologies rather than building them from scratch. The framework is evaluated via experiments based on a synthetic benchmark dataset. Further, we utilize the field of materials design as a target domain to evaluate the feasibility of our framework by showing the use of the framework for the Open Databases Integration for Materials Design (OPTIMADE), which is a community effort aiming to develop a specification for a common API to make materials databases interoperable. At the beginning of this work, no ontologies existed for the domain of computational materials databases. As our approach requires the use of an ontology, we developed one: the Materials Design Ontology (MDO). Furthermore, when new databases are added or new kinds of data are added to existing databases, the coverage of the ontology driving the GraphQL server generation may need to be enlarged. Therefore, we study how ontologies can be extended and propose an approach based on phrase-based topic modeling, formal topical concept analysis and domain expert validation. In addition to extending MDO, we also use this approach to extend two ontologies in the nanotechnology domain.

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    Ontology-Driven Data Access and Data Integration with an Application in the Materials Design Domain
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  • 21.
    Li, Huanyu
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Abd Nikooie Pour, Mina
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Li, Ying
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Lindecrantz, Mikael
    Ragn-Sells AB, Sweden.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. University of Gävle, Sweden.
    A Survey of General Ontologies for the Cross-Industry Domain of Circular Economy2023In: WWW '23 Companion: Companion Proceedings of the ACM Web Conference 2023, New York, NY, United States: Association for Computing Machinery (ACM), 2023, p. 731-741Conference paper (Refereed)
    Abstract [en]

    Circular Economy has the goal to reduce value loss and avoid waste by extending the life span of materials and products, including circulating materials or product parts before they become waste. Circular economy models (e.g., circular value networks) are typically complex and networked, involving different cross-industry domains. In the context of a circular value network, multiple actors, such as suppliers, manufacturers, recyclers, and product end-users, may be involved. In addition, there may be various flows of resources, energy, information and value throughout the network. This means that we face the challenge that the data and information from cross-industry domains in a circular economy model are not built on common ground, and as a result are difficult to understand and use for both humans and machines. Using ontologies to represent domain knowledge can enable actors and stakeholders from different industries in the circular economy to communicate using a common language. The knowledge domains involved include circular economy, sustainability, materials, products, manufacturing, and logistics. The objective of this paper is to investigate the landscape of current ontologies for these domains. This will enable us to in the future explore what existing knowledge can be adapted or used to develop ontologies for circular value networks.

  • 22.
    Li, Huanyu
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Armiento, Rickard
    Linköping University, Department of Physics, Chemistry and Biology, Theoretical Physics. Linköping University, Faculty of Science & Engineering.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    A Method for Extending Ontologies with Application to the Materials Science Domain2019In: Data Science Journal, E-ISSN 1683-1470, Vol. 18, no 1, p. 1-21, article id 50Article in journal (Refereed)
    Abstract [en]

    In the materials science domain the data-driven science paradigm has become the focus since the beginning of the 2000s. A large number of research groups and communities are building and developing data-driven workflows. However, much of the data and knowledge is stored in different heterogeneous data sources maintained by different groups. This leads to a reduced availability of the data and poor interoperability between systems in this domain. Ontology-based techniques are an important way to reduce these problems and a number of efforts have started. In this paper we investigate efforts in the materials science, and in particular in the nanotechnology domain, and show how such ontologies developed by domain experts, can be improved. We use a phrase-based topic model approach and formal topical concept analysis on unstructured text in this domain to suggest additional concepts and axioms for the ontology that should be validated by a domain expert. We describe the techniques and show the usefulness of the approach through an experiment where we extend two nanotechnology ontologies using approximately 600 titles and abstracts.

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  • 23.
    Li, Huanyu
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Armiento, Rickard
    Linköping University, Department of Physics, Chemistry and Biology, Theoretical Physics. Linköping University, Faculty of Science & Engineering.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    An Ontology for the Materials Design Domain2020In: The Semantic Web – ISWC 2020 19th International Semantic Web Conference, Athens, Greece, November 2–6, 2020, Proceedings, Part II / [ed] Jeff Z. Pan, Valentina Tamma, Claudia d’Amato, Krzysztof Janowicz, Bo Fu, Axel Polleres, Oshani Seneviratne, Lalana Kagal, Cham, 2020, p. 212-227Conference paper (Refereed)
    Abstract [en]

    In the materials design domain, much of the data from materials calculations are stored in different heterogeneous databases. Materials databases usually have different data models. Therefore, the users have to face the challenges to find the data from adequate sources and integrate data from multiple sources. Ontologies and ontology-based techniques can address such problems as the formal representation of domain knowledge can make data more available and interoperable among different systems. In this paper, we introduce the Materials Design Ontology (MDO), which defines concepts and relations to cover knowledge in the field of materials design. MDO is designed using domain knowledge in materials science (especially in solid-state physics), and is guided by the data from several databases in the materials design field. We show the application of the MDO to materials data retrieved from well-known materials databases.

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  • 24.
    Li, Huanyu
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Armiento, Rickard
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Physics, Chemistry and Biology, Theoretical Physics.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Extending Ontologies in the Nanotechnology Domain using Topic Models and Formal Topical Concept Analysis on Unstructured Text2019In: ISWC 2019 Satellites: Proceedings of the ISWC 2019 Satellite Tracks (Posters & Demonstrations, Industry, and Outrageous Ideas) co-located with 18th International Semantic Web Conference (ISWC 2019), Technical University of Aachen , 2019, p. 5-8Conference paper (Refereed)
    Abstract [en]

    In the data-driven workflows in the materials science domain, much of the data and knowledge is stored in different heterogeneous data sources maintained by different groups. This leads to a reduced availability of the data and poor interoperability between systems in this domain. Ontology-based techniques are an important way to reduce these problems and a number of efforts have started. In this paper, we use a phrase-based topic model approach and formal topical concept analysis on unstructured text in this domain to suggest additional concepts and axioms for the ontology that should be validated by a domain expert.

    Download full text (pdf)
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  • 25.
    Li, Huanyu
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered Systems. Linköping University, Faculty of Science & Engineering.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. Swedish e-Science Research Centre.
    Initial and Experimental Ontology Alignment Results in the Circular Economy Domain2024Conference paper (Refereed)
    Abstract [en]

    The Circular Economy (CE) domain has a nature of connecting and linking multiple cross-industry domains (e.g., manufacturing and materials) aiming to reduce value loss and avoid waste by building and implementing CE models (i.e., circular value networks) across these domains. In recent years, ontologies have been recognized as a key for representing domain knowledge in CE. Both CE-specific and domain-specific ontologies exist, with more continuously emerging. Matching CE-related ontologies can generate alignments that enhance the interoperability and reusability of such ontologies.In this paper, we present our initial efforts and findings in matching ontologies within the CE domain.

  • 26.
    Li, Huanyu
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Dragisic, Zlatan
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. Sectra.
    Faria, Daniel
    Gulbenkian Science Institute, Portugal.
    Ivanova, Valentina
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. RISE Research Institutes of Sweden.
    Jiménez-Ruiz, Ernesto
    City, University of London, UK, and The Alan Turing Institute, London, and Department of Informatics, University of Oslo, Norway.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Pesquita, Catia
    LaSIGE, Faculdade de Ciências, Universidade de Lisboa, Portugal,.
    User validation in ontology alignment: functional assessment and impact2019In: Knowledge engineering review (Print), ISSN 0269-8889, E-ISSN 1469-8005, Vol. 34, article id e15Article in journal (Refereed)
    Abstract [en]

    User validation is one of the challenges facing the ontology alignment community, as there are limits to the quality of the alignments produced by automated alignment algorithms. In this paper, we present a broad study on user validation of ontology alignments that encompasses three distinct but inter-related aspects: the profile of the user, the services of the alignment system, and its user interface. We discuss key issues pertaining to the alignment validation process under each of these aspects and provide an overview of how current systems address them. Finally, we use experiments from the Interactive Matching track of the Ontology Alignment Evaluation Initiative 2015–2018 to assess the impact of errors in alignment validation, and how systems cope with them as function of their services.

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  • 27.
    Li, Huanyu
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. The Swedish e-Science Research Centre, Linköping University.
    Hartig, Olaf
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Armiento, Rickard
    Linköping University, Department of Physics, Chemistry and Biology, Theoretical Physics. Linköping University, Faculty of Science & Engineering. The Swedish e-Science Research Centre, Linköping University.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. The Swedish e-Science Research Centre, Linköping University.
    OBG-gen: Ontology-Based GraphQL Server Generation for Data Integration2023In: Proceedings of the ISWC 2023 Posters, Demos and Industry Tracks: From Novel Ideas to Industrial Practice: co-located with 22nd International Semantic Web Conference (ISWC 2023) / [ed] Irini Fundulaki, Kouji Kozaki, Daniel Garijo, Jose Manuel Gomez-Perez, 2023Conference paper (Refereed)
    Abstract [en]

    A GraphQL server contains two building blocks: (1) a GraphQL schema defining the types of data objects that can be requested; (2) resolver functions fetching the relevant data from underlying data sources. GraphQL can be used for data integration if the GraphQL schema provides an integrated view of data from multiple data sources, and the resolver functions are implemented accordingly.However, there does not exist a semantics-aware approach to use GraphQL for data integration.We proposed a framework using GraphQL for data integration in which a global domain ontology informs the generation of a GraphQL server. Furthermore, we implemented a prototype of this framework, OBG-gen. In this paper, we demonstrate OBG-gen in a real-world data integration scenario in the materials design domain and in  a synthetic benchmark scenario.

  • 28.
    Li, Huanyu
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. The Swedish e-Science Research Centre, Linköping University, Sweden.
    Hartig, Olaf
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Armiento, Rickard
    Linköping University, Department of Physics, Chemistry and Biology, Theoretical Physics. Linköping University, Faculty of Science & Engineering. The Swedish e-Science Research Centre, Linköping University, Sweden.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. The Swedish e-Science Research Centre, Linköping University, Sweden;Department of Building Engineering, Energy Systems and Sustainability Science, University of Gävle, Sweden.
    Ontology-based GraphQL server generation for data access and data integration2024In: Semantic Web, ISSN 1570-0844, E-ISSN 2210-4968, p. 1-37Article in journal (Refereed)
    Abstract [en]

    In a GraphQL Web API, a so-called GraphQL schema defines the types of data objects that can be queried, and so-called resolver functions are responsible for fetching the relevant data from underlying data sources. Thus, we can expect to use GraphQL not only for data access but also for data integration, if the GraphQL schema reflects the semantics of data from multiple data sources, and the resolver functions can obtain data from these data sources and structure the data according to the schema. However, there does not exist a semantics-aware approach to employ GraphQL for data integration. Furthermore, there are no formal methods for defining a GraphQL API based on an ontology.In this work, we introduce a framework for using GraphQL in which a global domain ontology informs the generation of a GraphQL server that answers requests by querying heterogeneous data sources.The core of this framework consists of an algorithm to generate a GraphQL schema based on an ontology and a generic resolver function based on semantic mappings. We provide a prototype, OBG-gen, of this framework, and we evaluate our approach over a real-world data integration scenario in the materials design domain and two synthetic benchmark scenarios (Linköping GraphQL Benchmark and GTFS-Madrid-Bench). The experimental results of our evaluation indicate that: (i) our approach is feasible to generate GraphQL servers for data access and integration over heterogeneous data sources, thus avoiding a manual construction of GraphQL servers, and (ii) our data access and integration approach is general and applicable to different domains where data is shared or queried via different ways.

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    fulltext
  • 29.
    Li, Huanyu
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. Swedish e-Science Research Centre.
    BadmintONTO: A Badminton Domain Ontology2024Conference paper (Refereed)
    Abstract [en]

    In different sports fields, collecting play-by-play data has become significant for data analysis, as seen in sports like baseball, basketball, ice hockey and football. Badminton remains a relatively new domain in terms of systematically collecting game play data (i.e., play-by-play or shot-by-shot) with only some recently published datasets online. While the game play data provides some detailed information about matches, it lacks rich semantics for complex information retrieval and data analysis. Consequently, the data cannot be used for applications where semantics are needed. This paper introduces a badminton domain ontology - BadmintONTO, along with its illustrative usages to showcase the capability of this ontology to represent basic domain knowledge and to annotate play-by-play data. 

  • 30.
    Matentzoglu, Nicolas
    et al.
    Semanticly, Athens, Greece.
    Braun, Ian
    Critical Path Institute, Tucson, AZ 85718, USA.
    Caron, Anita R.
    European Bioinformatics Institute (EMBL-EBI), Hinxton, UK.
    Goutte-Gattat, Damien
    University of Cambridge, Cambridge, CB2 3DY, UK.
    Gyori, Benjamin M.
    Harvard Medical School, Boston, MA 02115, USA.
    Harris, Nomi L.
    Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
    Hartley, Emily
    Critical Path Institute, Tucson, AZ 85718, USA.
    Hegde, Harshad B.
    Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
    Hertling, Sven
    Data and Web Science Group, University of Mannheim, Germany.
    Hoyt, Charles Tapley
    Harvard Medical School, Boston, MA 02115, USA.
    Kim, HyeongSik
    Robert Bosch LLC.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. The Swedish e-Science Research Centre, Linköping University.
    McLaughlin, James
    European Bioinformatics Institute (EMBL-EBI), Hinxton, UK.
    Trojahn, Cassia
    Universite Toulouse 2, Toulouse, France.
    Vasilevsky, Nicole
    Critical Path Institute, Tucson, AZ 85718, USA.
    Mungall, Christopher J.
    Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
    A Simple Standard for Ontological Mappings 2023: Updates on data model, collaborations and tooling2023In: Proceedings of the 18th International Workshop on Ontology Matching (OM 2023) co-located with the 22nd International Semantic Web Conference (ISWC 2023) / [ed] Pavel Shvaiko, Jérôme Euzenat, Ernesto Jiménez-Ruiz, Oktie Hassanzadeh, Cássia Trojahn, 2023, Vol. 3591, p. 73-78Conference paper (Refereed)
    Abstract [en]

    The Simple Standard for Ontological Mappings (SSSOM) was first published in December 2021 (v. 0.9). After a number of revisions prompted by community feedback, we have published version 0.15.0 in July 2023. Here we report on the progress made since August 2022, in particular changes to tooling, data model and summary of ongoing standardisation efforts.

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