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  • 1.
    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)
  • 2.
    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)
  • 3.
    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 & Université Toulouse II, Toulouse, France.
    Trojahn, Cassia
    IRIT & 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.

  • 4.
    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, ISSN 2041-1480, 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.

  • 5.
    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.

  • 6.
    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.

  • 7.
    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.

  • 8.
    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, ISSN 1683-1470, 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.

  • 9.
    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. 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.
    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), CEUR Workshop Proceedings , 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.

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