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2. Building conceptual spaces for exploring and linking biomedical resources

Author

Berlanga, R., Jimenez-Ruiz, E., and Nebot, V.

Subjects
Computer Science - Information Retrieval, J.3
Abstract

The establishment of links between data (e.g., patient records) and Web resources (e.g., literature) and the proper visualization of such discovered knowledge is still a challenge in most Life Science domains (e.g., biomedicine). In this paper we present our contribution to the community in the form of an infrastructure to annotate information resources, to discover relationships among them, and to represent and visualize the new discovered knowledge. Furthermore, we have also implemented a Web-based prototype tool which integrates the proposed infrastructure., Comment: in Adrian Paschke, Albert Burger, Andrea Splendiani, M. Scott Marshall, Paolo Romano: Proceedings of the 3rd International Workshop on Semantic Web Applications and Tools for the Life Sciences, Berlin,Germany, December 8-10, 2010

Published
2010

3. The Management and Integration of Biomedical Knowledge: Application in the Health-e-Child Project (Position Paper)

Author

Jimenez-Ruiz, E., Berlanga, R., Sanz, I., McClatchey, R., Danger, R., Manset, D., Paraire, J., and Rios, A.

Subjects
Computer Science - Databases, H.2.4, J.3
Abstract

The Health-e-Child project aims to develop an integrated healthcare platform for European paediatrics. In order to achieve a comprehensive view of childrens health, a complex integration of biomedical data, information, and knowledge is necessary. Ontologies will be used to formally define this domain knowledge and will form the basis for the medical knowledge management system. This paper introduces an innovative methodology for the vertical integration of biomedical knowledge. This approach will be largely clinician-centered and will enable the definition of ontology fragments, connections between them (semantic bridges) and enriched ontology fragments (views). The strategy for the specification and capture of fragments, bridges and views is outlined with preliminary examples demonstrated in the collection of biomedical information from hospital databases, biomedical ontologies, and biomedical public databases., Comment: 6 pages; 2 figures. Proceedings of the 1st International Workshop on Ontology content and evaluation in Enterprise

Published
2006

4. MammoTab: a giant and comprehensive dataset for Semantic Table Interpretation

Author

Efthymiou, V, Jiménez-Ruiz, E, Chen, J, Cutrona, V, Hassanzadeh, O, Sequeda, J, Srinivas, K, Abdelmageed, N, Hulsebos, M, Marzocchi, M, Cremaschi, M, Pozzi, R, Avogadro, R, Palmonari, M, Efthymiou, V, Jiménez-Ruiz, E, Chen, J, Cutrona, V, Hassanzadeh, O, Sequeda, J, Srinivas, K, Abdelmageed, N, Hulsebos, M, Marzocchi, M, Cremaschi, M, Pozzi, R, Avogadro, R, and Palmonari, M

Abstract

In this paper, we present MammoTab, a dataset composed of 1M Wikipedia tables extracted from over 20M Wikipedia pages and annotated through Wikidata. The lack of this kind of datasets in the state- of-the-art makes MammoTab a good resource for testing and training Semantic Table Interpretation approaches. The dataset has been designed to cover several key challenges, such as disambiguation, homonymy, and NIL-mentions. The dataset has been evaluated using MTab, one of the best approaches of the SemTab challenge.

Published
2023

5. Results of the Ontology Alignment Evaluation Initiative 2022

Author

Pour, MAN, Algergawy, A, Buche, P, Castro, LJ, Chen, J, Dong, H, Fallatah, O, Faria, D, Fundulaki, I, Hertling, S, He, Y, Horrocks, I, Huschka, M, Ibanescu, L, Jiménez-Ruiz, E, Karam, N, Laadhar, A, Lambrix, P, Li, H, Li, Y, Michel, F, Nasr, E, Paulheim, H, Pesquita, C, Saveta, T, Shvaiko, P, Trojahn, C, Verhey, C, Wu, M, Yaman, B, Zamazal, O, and Zhou, L

Abstract

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 by 18 participants. This paper is an overall presentation of that campaign.

Published
2023

6. OntoPath: A Language for Retrieving Ontology Fragments

Author

Jiménez-Ruiz, E., Berlanga, R., Nebot, V., Sanz, I., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Meersman, Robert, editor, and Tari, Zahir, editor

Published
2007
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7. Results of SemTab 2021

Author

Cutrona, V., Chen, J., Vasilis Efthymiou, Hassanzadeh, O., Jiménez-Ruiz, E., Sequeda, J., Srinivas, K., Abdelmageed, N., Hulsebos, M., Oliveira, D., and Pesquita, C.

Subjects
QA75
Abstract

SemTab 2021 was the third edition of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching, successfully collocated with the 20th International Semantic Web Conference (ISWC) and the 16th Ontology Matching (OM) Workshop. SemTab provides a common framework to conduct a systematic evaluation of state-of-the-art systems.

Published
2022

8. Results of the Ontology Alignment Evaluation Initiative 2022

Author

Pour, M. A. N., Algergawy, A., Buche, P., Castro, L. J., Chen, J., Dong, H., Fallatah, O., Faria, D., Fundulaki, I., Hertling, S., He, Y., Horrocks, I., Huschka, M., Ibanescu, L., Jiménez-Ruiz, E., Karam, N., Laadhar, A., Lambrix, Patrick, Li, H., Li, Y., Michel, F., Nasr, E., Paulheim, H., Pesquita, C., Saveta, T., Shvaiko, P., Trojahn, C., Verhey, C., Wu, M., Yaman, B., Zamazal, O., Zhou, L., Pour, M. A. N., Algergawy, A., Buche, P., Castro, L. J., Chen, J., Dong, H., Fallatah, O., Faria, D., Fundulaki, I., Hertling, S., He, Y., Horrocks, I., Huschka, M., Ibanescu, L., Jiménez-Ruiz, E., Karam, N., Laadhar, A., Lambrix, Patrick, Li, H., Li, Y., Michel, F., Nasr, E., Paulheim, H., Pesquita, C., Saveta, T., Shvaiko, P., Trojahn, C., Verhey, C., Wu, M., Yaman, B., Zamazal, O., and Zhou, L.

Abstract

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 by 18 participants. This paper is an overall presentation of that campaign. © 2022 Copyright for this paper by its authors.

Published
2022

9. MammoTab: a giant and comprehensive dataset for Semantic Table Interpretation

Author

Efthymiou, V, Jiménez-Ruiz, E, Chen, J, Cutrona, V, Hassanzadeh, O, Sequeda, J, Srinivas, K, Abdelmageed, N, Hulsebos, M, Marzocchi, M, Cremaschi, M, Pozzi, R, Avogadro, R, Palmonari, M, Efthymiou, V, Jiménez-Ruiz, E, Chen, J, Cutrona, V, Hassanzadeh, O, Sequeda, J, Srinivas, K, Abdelmageed, N, Hulsebos, M, Marzocchi, M, Cremaschi, M, Pozzi, R, Avogadro, R, and Palmonari, M

Abstract

In this paper, we present MammoTab, a dataset composed of 1M Wikipedia tables extracted from over 20M Wikipedia pages and annotated through Wikidata. The lack of this kind of datasets in the state- of-the-art makes MammoTab a good resource for testing and training Semantic Table Interpretation approaches. The dataset has been designed to cover several key challenges, such as disambiguation, homonymy, and NIL-mentions. The dataset has been evaluated using MTab, one of the best approaches of the SemTab challenge.

Published
2022

11. Tough Tables: Carefully Evaluating Entity Linking for Tabular Data

Author

Pan J.Z.,Tamma V.,d'Amato C.,Janowicz K.,Fu B.,Polleres A.,Seneviratne O.,Kagal L., Cutrona, V, Bianchi, F, Jiménez-Ruiz, E, Palmonari, M, Pan J.Z.,Tamma V.,d'Amato C.,Janowicz K.,Fu B.,Polleres A.,Seneviratne O.,Kagal L., Cutrona, V, Bianchi, F, Jiménez-Ruiz, E, and Palmonari, M

Abstract

Table annotation is a key task to improve querying the Web and support the Knowledge Graph population from legacy sources (tables). Last year, the SemTab challenge was introduced to unify different efforts to evaluate table annotation algorithms by providing a common interface and several general-purpose datasets as a ground truth. The SemTab dataset is useful to have a general understanding of how these algorithms work, and the organizers of the challenge included some artificial noise to the data to make the annotation trickier. However, it is hard to analyze specific aspects in an automatic way. For example, the ambiguity of names at the entity-level can largely affect the quality of the annotation. In this paper, we propose a novel dataset to complement the datasets proposed by SemTab. The dataset consists of a set of high-quality manually-curated tables with non-obviously linkable cells, i.e., where values are ambiguous names, typos, and misspelled entity names not appearing in the current version of the SemTab dataset. These challenges are particularly relevant for the ingestion of structured legacy sources into existing knowledge graphs. Evaluations run on this dataset show that ambiguity is a key problem for entity linking algorithms and encourage a promising direction for future work in the field.

Published
2020

12. Results of SemTab 2020

Author

Ernesto Jiménez-Ruiz, Oktie Hassanzadeh, Vasilis Efthymiou, Jiaoyan Chen, Kavitha Srinivas, Vincenzo Cutrona, Jiménez-Ruiz, E, Hassanzadeh, O, Efthymiou, V, Chen, J, Srinivas, K, Cutrona, V, Ernesto Jiménez-Ruiz, Oktie Hassanzadeh, Vasilis Efthymiou, Jiaoyan Chen, Kavitha Srinivas, Vincenzo Cutrona, Jiménez-Ruiz, E, Hassanzadeh, O, Efthymiou, V, Chen, J, Srinivas, K, and Cutrona, V

Abstract

SemTab 2020 was the second edition of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching, successfully collocated with the 19th International Semantic Web Conference (ISWC) and the 15th Ontology Matching (OM) Workshop. SemTab provides a common framework to conduct a systematic evaluation of state-of-the-art systems.

Published
2020

13. MantisTable SE: An efficient approach for the semantic table interpretation

Author

Jiménez-Ruiz, E, Hassanzadeh, O, Efthymiou, V, Chen, J, Srinivas, K, Cutrona, V, Cremaschi, M, Avogadro, R, Barazzetti, A, Chieregato, D, Cremaschi M., Avogadro R., Barazzetti A., Chieregato D., Jiménez-Ruiz, E, Hassanzadeh, O, Efthymiou, V, Chen, J, Srinivas, K, Cutrona, V, Cremaschi, M, Avogadro, R, Barazzetti, A, Chieregato, D, Cremaschi M., Avogadro R., Barazzetti A., and Chieregato D.

Abstract

In this paper, we present a novel unsupervised and automatic approach for Semantic Table Interpretation. The technique presented is performed against DBpedia and Wikidata, and it can be easily adapted to any other Knowledge Graph (KG). Moreover, we provide a tool (LamAPI) that allows to efficiently fetch data needed for Semantic Table Interpretation (STI) tasks from the KG dumps.

Published
2020

18. Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities

Author

Chen, Jiaoyan, Dong, Hang, Hastings, Janna, Jiménez-Ruiz, Ernesto, López, Vanessa, Monnin, Pierre, Pesquita, Catia, Škoda, Petr, and Tamma, Valentina

Subjects
knowledge graphs, life science, knowledge discovery, explainable ai, Electronic computers. Computer science, QA75.5-76.95
Abstract

The term life sciences refers to the disciplines that study living organisms and life processes, and include chemistry, biology, medicine, and a range of other related disciplines. Research efforts in life sciences are heavily data-driven, as they produce and consume vast amounts of scientific data, much of which is intrinsically relational and graph-structured. The volume of data and the complexity of scientific concepts and relations referred to therein promote the application of advanced knowledge-driven technologies for managing and interpreting data, with the ultimate aim to advance scientific discovery. In this survey and position paper, we discuss recent developments and advances in the use of graph-based technologies in life sciences and set out a vision for how these technologies will impact these fields into the future. We focus on three broad topics: the construction and management of Knowledge Graphs (KGs), the use of KGs and associated technologies in the discovery of new knowledge, and the use of KGs in artificial intelligence applications to support explanations (explainable AI). We select a few exemplary use cases for each topic, discuss the challenges and open research questions within these topics, and conclude with a perspective and outlook that summarizes the overarching challenges and their potential solutions as a guide for future research.

Published
2023
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19. How Does Knowledge Evolve in Open Knowledge Graphs?

Author

Polleres, Axel, Pernisch, Romana, Bonifati, Angela, Dell'Aglio, Daniele, Dobriy, Daniil, Dumbrava, Stefania, Etcheverry, Lorena, Ferranti, Nicolas, Hose, Katja, Jiménez-Ruiz, Ernesto, Lissandrini, Matteo, Scherp, Ansgar, Tommasini, Riccardo, and Wachs, Johannes

Subjects
kg evolution, temporal kg, versioned kg, dynamic kg, Electronic computers. Computer science, QA75.5-76.95
Abstract

Openly available, collaboratively edited Knowledge Graphs (KGs) are key platforms for the collective management of evolving knowledge. The present work aims t o provide an analysis of the obstacles related to investigating and processing specifically this central aspect of evolution in KGs. To this end, we discuss (i) the dimensions of evolution in KGs, (ii) the observability of evolution in existing, open, collaboratively constructed Knowledge Graphs over time, and (iii) possible metrics to analyse this evolution. We provide an overview of relevant state-of-the-art research, ranging from metrics developed for Knowledge Graphs specifically to potential methods from related fields such as network science. Additionally, we discuss technical approaches - and their current limitations - related to storing, analysing and processing large and evolving KGs in terms of handling typical KG downstream tasks.

Published
2023
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20. Enriching the Human Phenotype Ontology with inferred axioms from textual descriptions

Author

Kudama, S, Berlanga, R, and Jiménez-Ruiz, E

Subjects
QA75, Z665
Abstract

The Human Phenotype Ontology (HP) is a reference vocabulary of human phenotypic abnormalities. HP, apart from the textual information (general definitions, descriptions, synonyms, etc.) of each ontology concept, also provides computer-readable logical definitions (axioms) of terms that will allow human phenotypic abnormalities to be related to entities from anatomy, pathology, bio- chemistry and other areas. In this paper we present a prototype to generate new axiomatic knowledge from the textual descriptions of each HP term. The proto- type (i) detects terms in the textual descriptions and not found in the given logical expressions, (ii) generates pair combinations of those terms, (iii) builds triples after detecting the most probable relation between the pair of terms using a sta- tistical model and, finally, (iv) suggests the most probable triples to the user so she can decide which ones can be added to the original axioms.

Published
2018

21. We divide, you conquer: From large-scale ontology alignment to manageable subtasks with a lexical index and neural embeddings

Author

Jiménez-Ruiz, E., Agibetov, A., Matthias Samwald, and Cross, V.

Subjects
QA75, Z665
Abstract

Large ontologies still pose serious challenges to state-of-the-art on-tology alignment systems. In this paper we present an approach that combines alexical index, a neural embedding model and locality modules to effectively di-vide an input ontology matching task into smaller and more tractable matchingsubtasks. We have conducted a comprehensive evaluation using the datasets ofthe Ontology Alignment Evaluation Initiative. The results are encouraging andsuggest that the proposed methods are adequate in practice and can be integratedwithin the workflow of state-of-the-art systems.

Published
2018

22. Demo: Enabling semantic access to static and streaming distributed data with optique

Author

Kharlamov, E, Brandt, S, Giese, M, Jiménez-Ruiz, E, Kotidis, Y, Lamparter, S, Mailis, T, Neuenstadt, C, Özçep, Pinkel, C, Soylu, A, Svingos, C, Zheleznyakov, D, Horrocks, I, Ioannidis, Y, Möller, R, and Waaler, A

Abstract

Real-time processing of data coming from multiple heterogeneous data streams and static databases is a typical task in many industrial scenarios such as diagnostics of large machines. A complex diagnostic task may require a collection of up to hundreds of queries over such data. Although many of these queries retrieve data of the same kind, such as temperature measurements, they access structurally different data sources. In this work, we show how Semantic Technologies implemented in our system OPTIQUE can simplify such complex diagnostics by providing an abstraction layer- ontology-that integrates heterogeneous data. In a nutshell, OPTIQUE allows complex diagnostic tasks to be expressed with just a few high-level semantic queries, which can be easily formulated with our visual query formulation system. OPTIQUE can then automatically enrich these queries, translate them into a large collection of low-level data queries, and finally optimise and efficiently execute the collection in a heavily distributed environment.

Published
2017

23. Ontology Based Data Access in Statoil

Author

Kharlamov, E. Hovland, D. Skjæveland, M.G. Bilidas, D. Jiménez-Ruiz, E. Xiao, G. Soylu, A. Lanti, D. Rezk, M. Zheleznyakov, D. Giese, M. Lie, H. Ioannidis, Y. Kotidis, Y. Koubarakis, M. Waaler, A.

Abstract

Ontology Based Data Access (OBDA) is a prominent approach to query databases which uses an ontology to expose data in a conceptually clear manner by abstracting away from the technical schema-level details of the underlying data. The ontology is ‘connected’ to the data via mappings that allow to automatically translate queries posed over the ontology into data-level queries that can be executed by the underlying database management system. Despite a lot of attention from the research community, there are still few instances of real world industrial use of OBDA systems. In this work we present data access challenges in the data-intensive petroleum company Statoil and our experience in addressing these challenges with OBDA technology. In particular, we have developed a deployment module to create ontologies and mappings from relational databases in a semi-automatic fashion; a query processing module to perform and optimise the process of translating ontological queries into data queries and their execution over either a single DB of federated DBs; and a query formulation module to support query construction for engineers with a limited IT background. Our modules have been integrated in one OBDA system, deployed at Statoil, integrated with Statoil's infrastructure, and evaluated with Statoil's engineers and data. © 2017 Elsevier B.V.

Published
2017

26. Towards shared hypothesis testing in the biomedical domain

Author

Asan Agibetov, Jiménez-Ruiz, E., Solimando, A., Guerrini, G., Patanè, G., and Spagnuolo, M.

Subjects
Biomedical ontology, Hypothesis testing, Incomplete knowledge, Computer Science (all), biomedical ontology, hypothesis testing, incomplete knowledge
Abstract

Evidence-based hypothesis testing assumes the existence of a causal chain between the facts. By studying the propagation of evidenced facts in the causal chain (hypothesis) we gain new insights on the progression of a disease. In practice, a hypothesis cannot always be substantiated with a complete asserted knowledge (inability to collect the required evidence), yet it is possible to test a hypothesis with missing knowledge with a lower confidence. In this work we propose a method to perform evidence-based hypothesis testing in the biomedical domain, such that specialists can evaluate confidence of their hypothesis and communicate their findings. We assume that a hypothesis is formalized in an OWL 2 EL ontology and the KB contains incomplete asserted knowledge (ABox). We extract a causal chain from an ontology and represent it as a DAG (node - fact, arc - causal relationship). Users assign importance weights to the facts which they think are more important to support the hypothesis. Evaluation of the hypothesis confidence is then done by computing a weighted sum of fact confidences over the directed path in the DAG (corresponding to the causal chain).

Published
2015

27. Results of the Ontology Alignment Evaluation Initiative 2014

Author

Dragisic, Z., Eckert, K., Euzenat, J., Faria, D., Alfio Ferrara, Granada, R., Ivanova, V., Jiménez-Ruiz, E., Kempf, A. O., Lambrix, P., Montanelli, S., Paulheim, H., Ritze, D., Shvaiko, P., Solimo, A., Trojahn, C., Zamazal, O., Grau, B. C., Department of Computer and Information Science - Linköping University, Linköping University (LIU), Institut für Informatik [Mannheim], Universität Mannheim [Mannheim], Computer mediated exchange of structured knowledge (EXMO), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire d'Informatique de Grenoble (LIG), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF), Universidade de Lisboa (ULISBOA), Università degli Studi di Milano [Milano] (UNIMI), Pontifícia Universidade Católica do Rio Grande do Sul [Porto Alegre] (PUCRS), Department of Computer Science [Oxford], University of Oxford [Oxford], Leibniz-Institute for the Social Sciences [Mannheim] (GESIS ), Informatica Trentina [Trento], Dipartimento di Informatica e Scienze dell'Informazione (DISI), Università di Genova, MEthodes et ingénierie des Langues, des Ontologies et du DIscours (IRIT-MELODI), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Université Toulouse - Jean Jaurès (UT2J), Vytsoka Skola Ekonomicka v Praze (VSE), Vysoká škola ekonomická v Praze, European Project: 238975,EC:FP7:INFRA,FP7-INFRASTRUCTURES-2008-2,SEALS(2009), Université Joseph Fourier - Grenoble 1 (UJF)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Université Joseph Fourier - Grenoble 1 (UJF)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Università degli studi di Milano [Milano], Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Universität Mannheim, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire d'Informatique de Grenoble (LIG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Universidade de Lisboa = University of Lisbon (ULISBOA), Università degli Studi di Milano = University of Milan (UNIMI), Pontifical Catholic University of Rio Grande do Sul (PUC-RS), University of Oxford, Leibniz-Institute for the Social Sciences [Mannheim] (GESIS), Università degli studi di Genova = University of Genoa (UniGe), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Institut National Polytechnique de Toulouse - INPT (FRANCE), Centre National de la Recherche Scientifique - CNRS (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), Institut National de Recherche en Informatique et en Automatique (Inria), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS), and Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)

Subjects
[INFO.INFO-TT]Computer Science [cs]/Document and Text Processing, Traitement du texte et du document, [INFO.INFO-OH]Computer Science [cs]/Other [cs.OH], OAEI, Ontology Alignment Evaluation Initiative, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

dragisic2014a; International audience; Ontology matching consists of finding correspondences between semantically related entities of two ontologies. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. These test cases can use ontologies of different nature (from simple thesauri to expressive OWL ontologies) and use different modalities, e.g., blind evaluation, open evaluation and consensus. OAEI 2014 offered 7 tracks with 9 test cases followed by 14 participants. Since 2010, the campaign has been using a new evaluation modality which provides more automation to the evaluation. This paper is an overall presentation of the OAEI 2014 campaign.

Published
2014

29. Enabling semantic access to static and streaming distributed data with optique

Author

Kharlamov, E., primary, Brandt, S., additional, Giese, M., additional, Jiménez-Ruiz, E., additional, Kotidis, Y., additional, Lamparter, S., additional, Mailis, T., additional, Neuenstadt, C., additional, Özçep, Ö., additional, Pinkel, C., additional, Soylu, A., additional, Svingos, C., additional, Zheleznyakov, D., additional, Horrocks, I., additional, Ioannidis, Y., additional, Möller, R., additional, and Waaler, A., additional

Published
2016
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30. The Bayesian ontology reasoner is born!

Author

Dumontier, M, Glimm, B, Gonçalves, RS, Horridge, M, Jiménez-Ruiz, E, Matentzoglu, N, Parsia, B, Stamou, GB, Stoilos, G, Ceylan, I, Mendez, J, Peñaloza, R, Dumontier, M, Glimm, B, Gonçalves, RS, Horridge, M, Jiménez-Ruiz, E, Matentzoglu, N, Parsia, B, Stamou, GB, Stoilos, G, Ceylan, I, Mendez, J, and Peñaloza, R

Abstract

Bayesian ontology languages are a family of probabilistic ontology languages that allow to encode probabilistic information over the axioms of an ontology with the help of a Bayesian network. The Bayesian ontology language BEL is an extension of the lightweight Description Logic (DL) EL within the above-mentioned framework. We present the system BORN that implements the probabilistic subsumption problem for BEL.

Published
2015

31. Optique 1.0: Semantic Access to Big Data: The Case of Norwegian Petroleum Directorate's Fact Pages

Author

Kharlamov, E., Giese, M., Jiménez-Ruiz, E., Skjæveland, M. G., Soylu, A., Zheleznyakov, D., Bagosi, T., Console, M., Haase, P., Ian Horrocks, Marciuska, S., Pinkel, C., Rodriguez-Muro, M., Ruzzi, M., Santarelli, V., Savo, D. F., Sengupta, K., Schmidt, M., Thorstensen, E., Trame, J., and Waaler, A.

Subjects
Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni
Published
2013

34. The Optique Project: Towards OBDA Systems for Industry (Short Paper)

Author

Calvanese, D, Giese, M, Haase, P, Horrocks, I, Hubauer, T, Ioannidis, Y, Jiménez−Ruiz, E, Kharlamov, E, Kllapi, H, Klüwer, J, Koubarakis, M, Lamparter, S, Möller, R, Neuenstadt, C, Nordtveit, T, Özcep, Ö, ­driguez−MurRoo, M, Roshchin, M, Ruzzi, M, Savo, F, Schmidt, M, Soylu, A, Waaler, A, and Zheleznyakov, D

Published
2013

36. Optique: Towards OBDA systems for industry

Author

Kharlamov, E. Jiménez-Ruiz, E. Zheleznyakov, D. Bilidas, D. Giese, M. Haase, P. Horrocks, I. Kllapi, H. Koubarakis, M. Özçep, Ö. Rodríguez-Muro, M. Rosati, R. Schmidt, M. Schlatte, R. Soylu, A. Waaler, A.

Abstract

The recently started EU FP7-funded project Optique will develop an end-to-end OBDA system providing scalable end-user access to industrial Big Data stores. This paper presents an initial architectural specification for the Optique system along with the individual system components. © Springer-Verlag 2013.

Published
2013

38. The HermiT OWL Reasoner

Author

Horrocks, I, Motik, B, Wang, Z, Yatskevich, M, and Jiménez-Ruiz, E

Abstract

HermiT is the only reasoner we know of that fully supports the OWL 2 standard, and that correctly reasons about properties as well as classes. It is based on a novel "hypertableau" calculus that addresses performance problems due to nondeterminism and model size-the primary sources of complexity in state-of-the-art OWL reasoners. HermiT also incorporates a number of novel optimizations, including an optimized ontology classification procedure. Our tests show that HermiT performs well compared to existing tableau reasoners and is often much faster when classifying complex ontologies.

Published
2012

43. Aplicación de nuevas técnicas docentes en la asignatura Sistemas Cliente/Servidor

Author

Corchuelo Gil, Rafael, Jiménez Rodríguez, María José, Romero Ternero, María del Carmen, Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos, Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII), Universidad de Sevilla. Departamento de Tecnología Electrónica, Jiménez Ruiz, E., Llido, D., Berlanga, R., Rajadell, O., Corchuelo Gil, Rafael, Jiménez Rodríguez, María José, Romero Ternero, María del Carmen, Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos, Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII), Universidad de Sevilla. Departamento de Tecnología Electrónica, Jiménez Ruiz, E., Llido, D., Berlanga, R., and Rajadell, O.

Abstract

En este trabajo mostramos nuestras experiencias en la aplicación de metodologías de aprendizaje cooperativo y basado en proyectos en la asignatura Sistemas Cliente/Servidor en los cursos académicos 2008/2009 y 2009/2010.

Published
2011

46. OntoPath: A Language for Retrieving Ontology Fragments.

Author

Hutchison, David, Kanade, Takeo, Kittler, Josef, Kleinberg, Jon M., Mattern, Friedemann, Mitchell, John C., Naor, Moni, Nierstrasz, Oscar, Pandu Rangan, C., Steffen, Bernhard, Sudan, Madhu, Terzopoulos, Demetri, Tygar, Doug, Vardi, Moshe Y., Weikum, Gerhard, Meersman, Robert, Tari, Zahir, Jiménez-Ruiz, E., Berlanga, R., and Nebot, V.

Abstract

In this work we introduce a novel retrieval language, named OntoPath, for specifying and retrieving relevant ontology fragments. This language is intended to extract customized self-standing ontologies from very large, general-purpose ones. Through OntoPath, users can specify the desired detail level in the concept taxonomies as well as the properties between concepts that are required by the target applications. The syntax and aims of OntoPath resemble XPath's in that they are simple enough to be handled by non-expert users and they are designed to be included in other XML-based applications (e.g. transformations sheets, semantic annotation of web services, etc.). OntoPath has been implemented on the top of the graph-based database G, for which a Protégé OWL plug-in has been designed to access and retrieve ontology fragments. [ABSTRACT FROM AUTHOR]

Published
2007
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48. Limiting logical violations in ontology alignment through negotiation

Author

Jiménez-Ruiz, E., Terence Payne, Solimando, A., and Tamma, V.

Abstract

Ontology alignment (also called ontology matching) is the process of identifying correspondences between entities in different, possibly heterogeneous, ontologies. Traditional ontology alignment techniques rely on the full disclosure of the ontological models; however, within open and opportunistic environments, such approaches may not always be pragmatic or even acceptable (due to privacy concerns). Several studies have focussed on collaborative, decentralised approaches to ontology alignment, where agents negotiate the acceptability of single correspondences acquired from past encounters, or try to ascertain novel correspondences on the fly. However, such approaches can lead to logical violations that may undermine their utility. In this paper, we extend a dialogical approach to correspondence negotiation, whereby agents not only exchange details of possible correspondences, but also identify potential violations to the consistency and conservativity principles. We present a formal model of the dialogue, and show how agents can repair logical violations during the dialogue by invoking a correspondence repair, thus negotiating and exchanging repair plans. We illustrate this opportunistic alignment mechanism with an example and we empirically show that allowing agents to strategically reject or weaken correspondences when these cause violations does not degrade the effectiveness of the alignment computed, whilst reducing the number of residual violations.

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