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  • 1.
    Abd Nikooie Pour, Mina
    et al.
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Swedish e-Science Research Centre, Linköping, Sweden.
    Tarafder, Prithwish
    Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Konstruktionsmaterial. Linköpings universitet, Tekniska fakulteten.
    Wiberg, Anton
    Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Produktrealisering. Linköpings universitet, Tekniska fakulteten.
    Li, Huanyu
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för datavetenskap, Människocentrerade system.
    Moverare, Johan
    Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Konstruktionsmaterial. Linköpings universitet, Tekniska fakulteten.
    Lambrix, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten. Swedish e-Science Research Centre, Linköping, Sweden.
    PBF-AMP-Onto: an ontology for powder bed fusion additive manufacturing processes2024Inngår i: Proceedings of the First International Workshop on Semantic Materials Science: Harnessing the Power of Semantic Web Technologies in Materials Science: co-located with the 20th International Conference on Semantic Systems (SEMANTiCS 2024) / [ed] Andre Valdestilhas, Huanyu Li, Patrick Lambrix, Harald Sack, Aachen, Germany: CEUR Workshop Proceedings , 2024, s. 2-14Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Additive manufacturing is an innovative production approach aimed at creating products that traditionaltechniques cannot produce with the desired quality and requirements. Throughout the additive manufacturing process, data is either used (such as materials properties, printer characteristics and settings)or generated (such as monitoring data during printing, slicing strategies setting parameters). However, managing such data with complex relationships remains a significant challenge in both research andindustry in the additive manufacturing field. To address this issue, we developed a modular ontology that can be used as the basis for a framework that supports decision-making systems, facilitate semantics-aware data management, and enhance the understanding and optimization of additive manufacturingprocesses. In this paper we focus on one of the state-of-the-art additive manufacturing approaches, i.e., powder bed fusion. To show the use and the feasibility of our approach, we created a knowledge graph for an actual additive manufacturing experiment based on our ontology, and show how queries relevant to domain experts can be answered using this knowledge graph.

  • 2.
    Lambrix, Patrick
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten. The Swedish e-Science Research Centre, Linköping University, Sweden; Department of Building Engineering, Energy Systems and Sustainability Science, University of Gävle, Sweden.
    Armiento, Rickard
    Linköpings universitet, Institutionen för fysik, kemi och biologi, Teoretisk Fysik. Linköpings universitet, Tekniska fakulteten. The Swedish e-Science Research Centre, Linköping University.
    Li, Huanyu
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten. The Swedish e-Science Research Centre, Linköping University.
    Hartig, Olaf
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Abd Nikooie Pour, Mina
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten. The Swedish e-Science Research Centre, Linköping University.
    Li, Ying
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten. The Swedish e-Science Research Centre, Linköping University.
    The materials design ontology2024Inngår i: Semantic Web, ISSN 1570-0844, E-ISSN 2210-4968, Vol. 15, nr 2, s. 481-515Artikkel i tidsskrift (Fagfellevurdert)
    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.

    Fulltekst (pdf)
    fulltext
  • 3.
    Li, Huanyu
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Abd Nikooie Pour, Mina
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Li, Ying
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Lindecrantz, Mikael
    Ragn-Sells AB, Sweden.
    Blomqvist, Eva
    Linköpings universitet, Institutionen för datavetenskap, Interaktiva och kognitiva system. Linköpings universitet, Tekniska fakulteten.
    Lambrix, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten. University of Gävle, Sweden.
    A Survey of General Ontologies for the Cross-Industry Domain of Circular Economy2023Inngår i: WWW '23 Companion: Companion Proceedings of the ACM Web Conference 2023, New York, NY, United States: Association for Computing Machinery (ACM), 2023, s. 731-741Konferansepaper (Fagfellevurdert)
    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.

  • 4.
    Blomqvist, Eva
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Interaktiva och kognitiva system. Linköpings universitet, Tekniska fakulteten.
    Li, Huanyu
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten. Swedish e-Science Research Centre.
    Keskisärkkä, Robin
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för datavetenskap, Interaktiva och kognitiva system.
    Lindecrantz, Mikael
    Ragn-Sells AB, Sweden.
    Abd Nikooie Pour, Mina
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Swedish e-Science Research Centre.
    Li, Ying
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Swedish e-Science Research Centre.
    Lambrix, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten. Swedish e-Science Research Centre.
    Cross-domain Modelling - A Network of Core Ontologies for the Circular Economy2023Inngår i: 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 , 2023Konferansepaper (Fagfellevurdert)
    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.

  • 5.
    Abd Nikooie Pour, Mina
    et al.
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Swedish e-Science Research Centre, Sweden.
    Li, Huanyu
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten. Swedish e-Science Research Centre, Sweden.
    Armiento, Rickard
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för fysik, kemi och biologi, Teoretisk Fysik. Swedish e-Science Research Centre, Sweden.
    Lambrix, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten. Swedish e-Science Research Centre, Sweden; University of Gävle, Sweden.
    Phrase2Onto: A Tool to Support Ontology Extension2023Inngår i: 27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems (KES 2023) / [ed] Robert Howlett, Elsevier, 2023, s. 1415-1424Konferansepaper (Fagfellevurdert)
    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.

  • 6.
    Abd Nikooie Pour, Mina
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    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
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Li, Huanyu
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Li, Ying
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    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 20232023Inngår i: 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, s. 97-139Konferansepaper (Fagfellevurdert)
  • 7.
    Norell, David
    et al.
    Linköpings universitet.
    Kröger, Oscar
    Linköpings universitet.
    Melin, Oscar
    Linköpings universitet.
    Abd Nikooie Pour, Mina
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Li, Ying
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Pattern Extraction from Controlled Exits in Ice Hockey2022Inngår i: Linköping Hockey Analytics Conference: LINHAC 2022 / [ed] Patrick Lambrix, Niklas Carlsson, Mikael Vernblom, Linköping University , 2022, s. 134-139Konferansepaper (Annet vitenskapelig)
  • 8.
    Abd Nikooie Pour, Mina
    et al.
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik.
    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
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska högskolan. Högskolan i Gävle.
    Li, Huanyu
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Li, Ying
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik.
    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 20222022Inngår i: 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, s. 84-128Konferansepaper (Fagfellevurdert)
    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

  • 9.
    Abd Nikooie Pour, Mina
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Li, Huanyu
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Armiento, Rickard
    Linköpings universitet, Institutionen för fysik, kemi och biologi, Teoretisk Fysik. Linköpings universitet, Tekniska fakulteten.
    Lambrix, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten. Högskolan i Gävle, Gävle, Sweden.
    A First Step towards a Tool for Extending Ontologies2021Inngår i: 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, s. 1-12Konferansepaper (Fagfellevurdert)
    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.

  • 10.
    Abd Nikooie Pour, Mina
    et al.
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik.
    Li, Huanyu
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Armiento, Rickard
    Linköpings universitet, Institutionen för fysik, kemi och biologi, Teoretisk Fysik. Linköpings universitet, Tekniska fakulteten.
    Lambrix, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska högskolan.
    A First Step towards Extending the Materials Design Ontology2021Inngår i: 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, s. 1-11Konferansepaper (Fagfellevurdert)
    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.

    Fulltekst (pdf)
    fulltext
  • 11.
    Abd Nikooie Pour, Mina
    et al.
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik.
    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
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska högskolan. University of Gävle, Sweden.
    Li, Huanyu
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Li, Ying
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik.
    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 20212021Inngår i: 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, s. 62-108Konferansepaper (Fagfellevurdert)
    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.

  • 12.
    Abd Nikooie Pour, Mina
    et al.
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik.
    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
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska högskolan.
    Li, Huanyu
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Li, Ying
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik.
    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 20202020Inngår i: 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, s. 92-138Konferansepaper (Fagfellevurdert)
    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. 

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