Linked data/Web des données in areas (2024-03-15)
Manuel Atencia, Jérôme David, Jérôme Euzenat, On the relation between keys and link keys for data interlinking, Semantic web journal 12(4):547-567, 2021
Both keys and their generalisation, link keys, may be used to perform data interlinking, i.e. finding identical resources in different RDF datasets. However, the precise relationship between keys and link keys has not been fully determined yet. A common formal framework encompassing both keys and link keys is necessary to ensure the correctness of data interlinking tools based on them, and to determine their scope and possible overlapping. In this paper, we provide a semantics for keys and link keys within description logics. We determine under which conditions they are legitimate to generate links. We provide conditions under which link keys are logically equivalent to keys. In particular, we show that data interlinking with keys and ontology alignments can be reduced to data interlinking with link keys, but not the other way around.
Ontology alignment, Key, Link key, Data interlinking
Manuel Atencia, Jérôme David, Jérôme Euzenat, Amedeo Napoli, Jérémy Vizzini, Relational concept analysis for circular link key extraction, Deliverable 1.2, ELKER, 57p., December 2021
A link key extraction procedure in case of circular dependencies is presented. It uses relational concept analysis and extends the procedure of Deliverable 1.1. This leads to investigate more closely the semantics of relational concept analysis which is given in terms of fixed points. Extracting all fixed points may offer more link key candidates to consider.
Formal Concept Analysis, Relational Concept Analysis, linked data, link key, data interlinking, Resource Description Framework
Manuel Atencia, Jérôme David, Jérôme Euzenat, Liliana Ibanescu, Nathalie Pernelle, Fatiha Saïs, Élodie Thiéblin, Cássia Trojahn dos Santos, Discovering expressive rules for complex ontology matching and data interlinking, in: Pavel Shvaiko, Jérôme Euzenat, Oktie Hassanzadeh, Ernesto Jiménez-Ruiz, Cássia Trojahn dos Santos (eds), Proc. 14th ISWC workshop on ontology matching (OM), Auckland (NZ), pp199-200, 2020
Ontology matching and data interlinking as distinguished tasks aim at facilitating the interoperability between different knowledge bases. Although the field has fully developed in the last years, most works still focus on generating simple correspondences between entities. These correspondences are however insufficient to fully cover the different types of heterogeneity between the knowledge base and complex correspondences are therefore required. Compared to simple matching, few approaches for complex matching have been proposed, focusing on correspondence patterns or exploiting common instances between the ontologies. Similarly, unsupervised data interlinking approaches (which do not require labelled data samples) have recently been developed. One approach consists in discovering linking rules such as simple keys or conditional keys on unlabelled data. The results have shown that the more expressive the rules, the higher the recall. Even more expressive rules (referential expressions, graph keys, etc.) are rather required, however naive approaches to the discovery of these rules can not be envisaged on large data sets. Existing approaches presuppose either that the data conform to the same ontology or that all possible pairs of properties be examined. Complementary, link keys are a set of pairs of properties that identify the instances of two classes of two RDF datasets. Such, link keys may be directly extracted without the need for an alignment. We introduce here an approach that aims at evaluating the impact of complex correspondences in the task of data interlinking established from the application of keys.
Data interlinking, Ontology matching, Complex correspondence
Manuel Atencia, Jérôme David, Jérôme Euzenat, Amedeo Napoli, Jérémy Vizzini, Link key candidate extraction with relational concept analysis, Discrete applied mathematics 273:2-20, 2020
Linked data aims at publishing data expressed in RDF (Resource Description Framework) at the scale of the worldwide web. These datasets interoperate by publishing links which identify individuals across heterogeneous datasets. Such links may be found by using a generalisation of keys in databases, called link keys, which apply across datasets. They specify the pairs of properties to compare for linking individuals belonging to different classes of the datasets. Here, we show how to recast the proposed link key extraction techniques for RDF datasets in the framework of formal concept analysis. We define a formal context, where objects are pairs of resources and attributes are pairs of properties, and show that formal concepts correspond to link key candidates. We extend this characterisation to the full RDF model including non functional properties and interdependent link keys. We show how to use relational concept analysis for dealing with cyclic dependencies across classes and hence link keys. Finally, we discuss an implementation of this framework.
Formal Concept Analysis, Relational Concept Analysis, Linked data, Link key, Data interlinking, Resource Description Framework
Jérôme Euzenat, A map without a legend: the semantic web and knowledge evolution, Semantic web journal 11(1):63-68, 2020
The current state of the semantic web is focused on data. This is a worthwhile progress in web content processing and interoperability. However, this does only marginally contribute to knowledge improvement and evolution. Understanding the world, and interpreting data, requires knowledge. Not knowledge cast in stone for ever, but knowledge that can seamlessly evolve; not knowledge from one single authority, but diverse knowledge sources which stimulate confrontation and robustness; not consistent knowledge at web scale, but local theories that can be combined. We discuss two different ways in which semantic web technologies can greatly contribute to the advancement of knowledge: semantic eScience and cultural knowledge evolution.
Semantic web, Linked data, Big data, Open data, Knowledge representation, Knowledge, Ontology, Machine learning, Reproducible research, eScience, Cultural evolution
Jérôme Euzenat, Marie-Christine Rousset, Semantic web, in: Pierre Marquis, Odile Papini, Henri Prade (eds), A guided tour of artificial intelligence research, Springer, Berlin (DE), 575p., 2020, pp181-207
The semantic web aims at making web content interpretable. It is no less than offering knowledge representation at web scale. The main ingredients used in this context are the representation of assertional knowledge through graphs, the definition of the vocabularies used in graphs through ontologies, and the connection of these representations through the web. Artificial intelligence techniques and, more specifically, knowledge representation techniques, are put to use and to the test by the semantic web. Indeed, they have to face typical problems of the web: scale, heterogeneity, incompleteness, and dynamics. This chapter provides a short presentation of the state of the semantic web and refers to other chapters concerning those techniques at work in the semantic web.
RDF, OWL, RDF Model, Querying RDF, SPARQL, SPARQL Extensions
Manuel Atencia, Jérôme David, Jérôme Euzenat, Amedeo Napoli, Jérémy Vizzini, A guided walk into link key candidate extraction with relational concept analysis, in: Claudia d'Amato, Lalana Kagal (eds), Proc. on journal track of the International semantic web conference, Auckland (NZ), 2019
Data interlinking is an important task for linked data interoperability. One of the possible techniques for finding links is the use of link keys which generalise relational keys to pairs of RDF models. We show how link key candidates may be directly extracted from RDF data sets by encoding the extraction problem in relational concept analysis. This method deals with non functional properties and circular dependent link key expressions. As such, it generalises those presented for non dependent link keys and link keys over the relational model. The proposed method is able to return link key candidates involving several classes at once.
Formal Concept Analysis, Relational Concept Analysis, Linked data, Link key, Data interlinking, Resource Description Framework
Manuel Atencia, Jérôme David, Jérôme Euzenat, Several link keys are better than one, or extracting disjunctions of link key candidates, in: Proc. 10th ACM international conference on knowledge capture (K-Cap), Marina del Rey (CA US), pp61-68, 2019
Link keys express conditions under which instances of two classes of different RDF data sets may be considered as equal. As such, they can be used for data interlinking. There exist algorithms to extract link key candidates from RDF data sets and different measures have been defined to evaluate the quality of link key candidates individually. For certain data sets, however, it may be necessary to use more than one link key on a pair of classes to retrieve a more complete set of links. To this end, in this paper, we define disjunction of link keys, propose strategies to extract disjunctions of link key candidates from RDF data, and apply existing quality measures to evaluate them. We also report on experiments with these strategies.
Linked data, RDF, Data interlinking, Link key, Antichain
Manuel Atencia, Jérôme Euzenat, Khadija Jradeh, Chan Le Duc, Tableau methods for reasoning with link keys, Deliverable 2.1, ELKER, 32p., 2019
Data interlinking is a critical task for widening and enhancing linked open data. One way to tackle data interlinking is to use link keys, which generalise keys to the case of two RDF datasets described using different ontologies. Link keys specify pairs of properties to compare for finding same-as links between instances of two classes of two different datasets. Hence, they can be used for finding links. Link keys can also be considered as logical axioms just like keys, ontologies and ontology alignments. We introduce the logic ALC+LK extending the description logic ALC with link keys. It may be used to reason and infer entailed link keys that may be more useful for a particular data interlinking task. We show that link key entailment can be reduced to consistency checking without introducing the negation of link keys. For deciding the consistency of an ALC+LK ontology, we introduce a new tableau-based algorithm. Contrary to the classical ones, the completion rules concerning link keys apply to pairs of individuals not directly related. We show that this algorithm is sound, complete and always terminates.
link keys, reasoning, tableau method
Manuel Atencia, Jérôme David, Jérôme Euzenat, Amedeo Napoli, Jérémy Vizzini, Candidate link key extraction with formal concept analysis, Deliverable 1.1, ELKER, 29p., October 2019
A link key extraction procedure using formal concept analysis is described. It is shown to extract all link key candidates.
Formal Concept Analysis, linked data, link key, data interlinking, Resource Description Framework
Jérôme David, Jérôme Euzenat, Jérémy Vizzini, Linkky: Extraction de clés de liage par une adaptation de l'analyse relationnelle de concepts, in: Actes 29e journées francophones sur Ingénierie des connaissances (IC), Nancy (FR), pp271-274, 2018
RDF, Clé de liage, Liage de données, Analyse relationelle de concepts, Analyse formelle de concepts, Network of ontologies
Pieter Pauwels, María Poveda Villalón, Alvaro Sicilia, Jérôme Euzenat, Semantic technologies and interoperability in the built environment, Semantic web journal 9(6):731-734, 2018
The built environment consists of plenty of physical assets with which we interact on a daily basis. In order to improve not only our built environment, but also our interaction with that environment, we would benefit a lot from semantic representations of this environment. This not only includes buildings, but also large infrastructure (bridges, tunnels, waterways, underground systems), and geospatial data. With this special issue, an insight is given into the current state of the art in terms of semantic technologies and interoperability in this built environment. This editorial not only summarizes the content of the Special Issue on Semantic Technologies and interoperability in the Built Environment, it also provides a brief overview of the current state of the art in general in terms of standardisation and community efforts.
Alvaro Sicilia, Pieter Pauwels, Leandro Madrazo, María Poveda Villalón, Jérôme Euzenat (eds), Special Issue on Semantic Technologies and Interoperability in the Build Environment, Semantic web journal (special issue) 9(6):729-855, 2018
Jérôme Euzenat, Extraction de clés de liage de données (résumé étendu), in: Actes 16e conférence internationale francophone sur extraction et gestion des connaissances (EGC), Reims (FR), (Bruno Crémilleux, Cyril de Runz (éds), Actes 16e conférence internationale francophone sur extraction et gestion des connaissances (EGC), Revue des nouvelles technologies de l'information E30, 2016), pp9-12, 2016
De grandes quantités de données sont publiées sur le web des données. Les lier consiste à identifier les mêmes ressources dans deux jeux de données permettant l'exploitation conjointe des données publiées. Mais l'extraction de liens n'est pas une tâche facile. Nous avons développé une approche qui extrait des clés de liage (link keys). Les clés de liage étendent la notion de clé de l'algèbre relationnelle à plusieurs sources de données. Elles sont fondées sur des ensembles de couples de propriétés identifiant les objets lorsqu'ils ont les mêmes valeurs, ou des valeurs communes, pour ces propriétés. On présentera une manière d'extraire automatiquement les clés de liage candidates à partir de données. Cette opération peut être exprimée dans l'analyse formelle de concepts. La qualité des clés candidates peut-être évaluée en fonction de la disponibilité (cas supervisé) ou non (cas non supervisé) d'un échantillon de liens. La pertinence et de la robustesse de telles clés seront illustrées sur un exemple réel.
Maroua Gmati, Manuel Atencia, Jérôme Euzenat, Tableau extensions for reasoning with link keys, in: Pavel Shvaiko, Jérôme Euzenat, Ernesto Jiménez-Ruiz, Michelle Cheatham, Oktie Hassanzadeh, Ryutaro Ichise (eds), Proc. 11th ISWC workshop on ontology matching (OM), Kobe (JP), pp37-48, 2016
Link keys allow for generating links across data sets expressed in different ontologies. But they can also be thought of as axioms in a description logic. As such, they can contribute to infer ABox axioms, such as links, or terminological axioms and other link keys. Yet, no reasoning support exists for link keys. Here we extend the tableau method designed for ALC to take link keys into account. We show how this extension enables combining link keys with terminological reasoning with and without ABox and TBox and generate non trivial link keys.
Link key, Tableau method, Description logics, Semantic web
Tatiana Lesnikova, Jérôme David, Jérôme Euzenat, Cross-lingual RDF thesauri interlinking, in: Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis (eds), Proc. 10th international conference on Language resources and evaluation (LREC), Portoroz (SI), pp2442-2449, 2016
Various lexical resources are being published in RDF. To enhance the usability of these resources, identical resources in different data sets should be linked. If lexical resources are described in different natural languages, then techniques to deal with multilinguality are required for interlinking. In this paper, we evaluate machine translation for interlinking concepts, i.e., generic entities named with a common noun or term. In our previous work, the evaluated method has been applied on named entities. We conduct two experiments involving different thesauri in different languages. The first experiment involves concepts from the TheSoz multilingual thesaurus in three languages: English, French and German. The second experiment involves concepts from the EuroVoc and AGROVOC thesauri in English and Chinese respectively. Our results demonstrate that machine translation can be beneficial for cross-lingual thesauri interlining independently of a dataset structure.
Cross-lingual data interlinking, owl:sameAs, Thesaurus alignment
Adam Sanchez, Tatiana Lesnikova, Jérôme David, Jérôme Euzenat, Instance-level matching, Deliverable 3.2, Lindicle, 20p., September 2016
This paper describes precisely an ontology matching technique based on the extensional definition of a class as set of instances. It first provides a general characterisation of such techniques and, in particular the need to rely on links across data sets in order to compare instances. We then detail the implication intensity measure that has been chosen. The resulting algorithm is implemented and evaluated on XLore, DBPedia, LinkedGeoData and Geospecies.
Instance-based matching, Ontology alignments
Strahil Birov, Simon Robinson, María Poveda Villalón, Mari Carmen Suárez-Figueroa, Raúl García Castro, Jérôme Euzenat, Bruno Fies, Andrea Cavallaro, Jan Peters-Anders, Thanasis Tryferidis, Kleopatra Zoi Tsagkari, Ontologies and datasets for energy measurement and validation interoperability, Deliverable 3.3, Ready4SmartCities, 135p., September 2015
Jérôme David, Jérôme Euzenat, Manuel Atencia, Language-independent link key-based data interlinking, Deliverable 4.1, Lindicle, 21p., March 2015
Links are important for the publication of RDF data on the web. Yet, establishing links between data sets is not an easy task. We develop an approach for that purpose which extracts weak link keys. Link keys extend the notion of a key to the case of different data sets. They are made of a set of pairs of properties belonging to two different classes. A weak link key holds between two classes if any resources having common values for all of these properties are the same resources. An algorithm is proposed to generate a small set of candidate link keys. Depending on whether some of the, valid or invalid, links are known, we define supervised and non supervised measures for selecting the appropriate link keys. The supervised measures approximate precision and recall, while the non supervised measures are the ratio of pairs of entities a link key covers (coverage), and the ratio of entities from the same data set it identifies (discrimination). We have experimented these techniques on two data sets, showing the accuracy and robustness of both approaches.
data interlinking, linked data, link key, candidate link key, coverage, dissimilarity
Jérôme Euzenat, Jérôme David, Angela Locoro, Armen Inants, Context-based ontology matching and data interlinking, Deliverable 3.1, Lindicle, 21p., July 2015
Context-based matching finds correspondences between entities from two ontologies by relating them to other resources. A general view of context-based matching is designed by analysing existing such matchers. This view is instantiated in a path-driven approach that (a) anchors the ontologies to external ontologies, (b) finds sequences of entities (path) that relate entities to match within and across these resources, and (c) uses algebras of relations for combining the relations obtained along these paths. Parameters governing such a system are identified and made explicit. We discuss the extension of this approach to data interlinking and its benefit to cross-lingual data interlinking. First, this extension would require an hybrid algebra of relation that combines relations between individual and classes. However, such an algebra may not be particularly useful in practice as only in a few restricted case it could conclude that two individuals are the same. But it can be used for finding mistakes in link sets.
Context-based data interlinking>, Multilingual data interlinking, Context-based ontology matching, Algebras of relations, Semantic web
Mari Hukkalainen, Matti Hannus, Kalevi Piira, Elina Grahn, Ha Hoang, Andrea Cavallaro, Raúl García Castro, Bruno Fies, Thanasis Tryferidis, Kleopatra Zoi Tsagkari, Jérôme Euzenat, Florian Judex, Daniele Basciotti, Charlotte Marguerite, Ralf-Roman Schmidt, Strahil Birov, Simon Robinson, Georg Vogt, Innovation and research roadmap, Deliverable 5.6, Ready4SmartCities, 63p., September 2015
Tatiana Lesnikova, Jérôme David, Jérôme Euzenat, Algorithms for cross-lingual data interlinking, Deliverable 4.2, Lindicle, 31p., June 2015
Linked data technologies enable to publish and link structured data on the Web. Although RDF is not about text, many RDF data providers publish their data in their own language. Cross-lingual interlinking consists of discovering links between identical resources across data sets in different languages. In this report, we present a general framework for interlinking resources in different languages based on associating a specific representation to each resource and computing a similarity between these representations. We describe and evaluate three methods using this approach: the two first methods are based on gathering virtual documents and translating them and the latter one represent them as bags of identifiers from a multilingual resource (BabelNet).
data interlinking, cross-lingual link discovery, owl:sameAs
Tatiana Lesnikova, Jérôme David, Jérôme Euzenat, Interlinking English and Chinese RDF data using BabelNet, in: Pierre Genevès, Christine Vanoirbeek (eds), Proc. 15th ACM international symposium on Document engineering (DocEng), Lausanne (CH), pp39-42, 2015
Linked data technologies make it possible to publish and link structured data on the Web. Although RDF is not about text, many RDF data providers publish their data in their own language. Cross-lingual interlinking aims at discovering links between identical resources across knowledge bases in different languages. In this paper, we present a method for interlinking RDF resources described in English and Chinese using the BabelNet multilingual lexicon. Resources are represented as vectors of identifiers and then similarity between these resources is computed. The method achieves an F-measure of 88%. The results are also compared to a translation-based method.
Cross-lingual instance linking, Cross-lingual link discovery, owl:sameAs
Jan Peters-Anders, Mari Hukkalainen, Bruno Fies, Strahil Birov, Mathias Weise, Andrea Cavallaro, Jérôme Euzenat, Thanasis Tryferidis, Community description, Deliverable 1.4, Ready4SmartCities, 60p., August 2015
Maria Roşoiu, Jérôme David, Jérôme Euzenat, A linked data framework for Android, in: Elena Simperl, Barry Norton, Dunja Mladenic, Emanuele Della Valle, Irini Fundulaki, Alexandre Passant, Raphaël Troncy (eds), The Semantic Web: ESWC 2012 Satellite Events, Springer Verlag, Heidelberg (DE), 2015, pp204-218
Mobile devices are becoming major repositories of personal information. Still, they do not provide a uniform manner to deal with data from both inside and outside the device. Linked data provides a uniform interface to access structured interconnected data over the web. Hence, exposing mobile phone information as linked data would improve the usability of such information. We present an API that provides data access in RDF, both within mobile devices and from the outside world. This API is based on the Android content provider API which is designed to share data across Android applications. Moreover, it introduces a transparent URI dereferencing scheme, exposing content outside of the device. As a consequence, any application may access data as linked data without any a priori knowledge of the data source.
Mathias Weise, María Poveda Villalón, Raúl García Castro, Jérôme Euzenat, Luz Maria Priego, Bruno Fies, Andrea Cavallaro, Jan Peters-Anders, Kleopatra Zoi Tsagkari, Ontologies and datasets for energy management system interoperability, Deliverable 2.3, Ready4SmartCities, 149p., 2015
Manuel Atencia, Jérôme David, Jérôme Euzenat, Data interlinking through robust linkkey extraction, in: Torsten Schaub, Gerhard Friedrich, Barry O'Sullivan (eds), Proc. 21st european conference on artificial intelligence (ECAI), Praha (CZ), pp15-20, 2014
Links are important for the publication of RDF data on the web. Yet, establishing links between data sets is not an easy task. We develop an approach for that purpose which extracts weak linkkeys. Linkkeys extend the notion of a key to the case of different data sets. They are made of a set of pairs of properties belonging to two different classes. A weak linkkey holds between two classes if any resources having common values for all of these properties are the same resources. An algorithm is proposed to generate a small set of candidate linkkeys. Depending on whether some of the, valid or invalid, links are known, we define supervised and non supervised measures for selecting the appropriate linkkeys. The supervised measures approximate precision and recall, while the non supervised measures are the ratio of pairs of entities a linkkey covers (coverage), and the ratio of entities from the same data set it identifies (discrimination). We have experimented these techniques on two data sets, showing the accuracy and robustness of both approaches.
Strahil Birov, Simon Robinson, María Poveda Villalón, Mari Carmen Suárez-Figueroa, Raúl García Castro, Jérôme Euzenat, Luz Maria Priego, Bruno Fies, Andrea Cavallaro, Jan Peters-Anders, Thanasis Tryferidis, Kleopatra Zoi Tsagkari, Ontologies and datasets for energy measurement and validation interoperability, Deliverable 3.2, Ready4SmartCities, 72p., September 2014
Andrea Cavallaro, Federico Di Gennaro, Jérôme Euzenat, Jan Peters-Anders, Anna Osello, Vision of energy systems for smart cities, Deliverable 5.2, Ready4SmartCities, 35p., November 2014
Jérôme Euzenat, Marie-Christine Rousset, Web sémantique, in: Pierre Marquis, Odile Papini, Henri Prade (éds), L'IA: frontières et applications, Cepadues, Toulouse (FR), 2014,
Le web sémantique ambitionne de rendre le contenu du web accessible au calcul. Il ne s'agit rien moins que de représenter de la connaissance à l'échelle du web. Les principales technologies utilisées dans ce cadre sont: la représentation de connaissance assertionnelle à l'aide de graphes, la définition du vocabulaire de ces graphes à l'aide d'ontologies, la connexion des représentations à travers le web, et leur appréhension pour interpréter la connaissance ainsi exprimée et répondre à des requêtes. Les techniques d'intelligence artificielle, et principalement de représentation de connaissances, y sont donc mises à contribution et à l'épreuve. En effet, elles sont confrontées à des problèmes typiques du web tels que l'échelle, l'hétérogénéité, l'incomplétude, l'incohérence et la dynamique. Ce chapitre propose une courte présentation de l'état du domaine et renvoie aux autres chapitres concernant les technologies mises en oeuvre dans le web sémantique.
RDF, OWL, RDF Model, Querying RDF, SPARQL, SPARQL Extensions
Zhengjie Fan, Jérôme Euzenat, François Scharffe, Learning concise pattern for interlinking with extended version space, in: Dominik l zak, Hung Son Nguyen, Marek Reformat, Eugene Santos (eds), Proc. 13th IEEE/WIC/ACM international conference on web intelligence (WI), Warsaw (PL), pp70-77, 2014
Many data sets on the web contain analogous data which represent the same resources in the world, so it is helpful to interlink different data sets for sharing information. However, finding correct links is very challenging because there are many instances to compare. In this paper, an interlinking method is proposed to interlink instances across different data sets. The input is class correspondences, property correspondences and a set of sample links that are assessed by users as either "positive" or "negative". We apply a machine learning method, Version Space, in order to construct a classifier, which is called interlinking pattern, that can justify correct links and incorrect links for both data sets. We improve the learning method so that it resolves the no-conjunctive-pattern problem. We call it Extended Version Space. Experiments confirm that our method with only 1% of sample links already reaches a high F-measure (around 0.96-0.99). The F-measure quickly converges, being improved by nearly 10% than other comparable approaches.
Raúl García Castro, María Poveda Villalón, Filip Radulovic, Asunción Gómez Pérez, Jérôme Euzenat, Luz Maria Priego, Georg Vogt, Simon Robinson, Strahil Birov, Bruno Fies, Jan Peters-Anders, Strategy for energy measurement and interoperability, Deliverable 3.1, Ready4SmartCities, 28p., January 2014
Tatiana Lesnikova, Jérôme David, Jérôme Euzenat, Interlinking English and Chinese RDF data sets using machine translation, in: Johanna Völker, Heiko Paulheim, Jens Lehmann, Harald Sack, Vojtech Svátek (eds), Proc. 3rd ESWC workshop on Knowledge discovery and data mining meets linked open data (Know@LOD), Hersounisos (GR), 2014
Data interlinking is a difficult task particularly in a multilingual environment like the Web. In this paper, we evaluate the suitability of a Machine Translation approach to interlink RDF resources described in English and Chinese languages. We represent resources as text documents, and a similarity between documents is taken for similarity between resources. Documents are represented as vectors using two weighting schemes, then cosine similarity is computed. The experiment demonstrates that TF*IDF with a minimum amount of preprocessing steps can bring high results.
Semantic web, Cross-lingual link discovery, Cross-lingual instance linking, owl:sameAs
Mari Sepponen, Matti Hannus, Kalevi Piira, Andrea Cavallaro, Raúl García Castro, Bruno Fies, Thanasis Tryferidis, Kleopatra Zoi Tsagkari, Jérôme Euzenat, Florian Judex, Daniele Basciotti, Charlotte Marguerite, Ralf-Roman Schmidt, Strahil Birov, Simon Robinson, Georg Vogt, Draft of innovation and research roadmap, Deliverable 5.3, Ready4SmartCities, 47p., November 2014
Mathias Weise, María Poveda Villalón, Mari Carmen Suárez-Figueroa, Raúl García Castro, Jérôme Euzenat, Luz Maria Priego, Bruno Fies, Andrea Cavallaro, Jan Peters-Anders, Kleopatra Zoi Tsagkari, Ontologies and datasets for energy management system interoperability, Deliverable 2.2, Ready4SmartCities, 72p., October 2014
Zhengjie Fan, Thin Dong Ngoc Nguyen, Jérôme Euzenat, Fayçal Hamdi, François Scharffe, Dataset interlinking module, Deliverable 4.2, Datalift, 34p., 2013
This report presents the second version of the interlinking module for the
Datalift platform as well as strategies for future developments.
data interlinking, linked data, instance matching
Luz Maria Priego, Jérôme Euzenat, Raúl García Castro, María Poveda Villalón, Filip Radulovic, Mathias Weise, Strategy for Energy Management System Interoperability, Deliverable 2.1, Ready4SmartCities, 25p., December 2013
The goal of the Ready4SmartCities project is to support energy data interoperability in the context of SmartCities. It keeps a precise focus on building and urban data. Work package 2 is more specifically concerned with identifying the knowledge and data resources available or needed, that support energy management system interoperability. This deliverable defines the strategy to be used in WP2 for achieving its goal. It is made of two parts: identifying domains and stakeholders specific to the WP2 activity and the methodology used in WP2 and WP3.
Jérôme David, Jérôme Euzenat, Maria Roşoiu, Linked data from your pocket, in: Christophe Guéret, Stefan Schlobach, Florent Pigout (eds), Proc. 1st ESWC workshop on downscaling the semantic web, Hersounissos (GR), pp6-13, 2012
The paper describes a lightweight general purpose RDF framework for Android. It allows to deal uniformly with RDF, whether it comes from the web or from applications inside the device. It extends the Android content provider framework and introduces a transparent URI dereferencing scheme allowing for exposing device content as linked data.
Jérôme David, Jérôme Euzenat, Maria Roşoiu, Mobile API for linked data, Deliverable 6.3, Datalift, 19p., 2012
This report presents a mobile API for manipulating linked data under the Android platform.
mobile, API, linked data, content provider
Jérôme Euzenat, A modest proposal for data interlinking evaluation, in: Pavel Shvaiko, Jérôme Euzenat, Anastasios Kementsietsidis, Ming Mao, Natalya Noy, Heiner Stuckenschmidt (eds), Proc. 7th ISWC workshop on ontology matching (OM), Boston (MA US), pp234-235, 2012
Data interlinking is a very important topic nowadays. It is sufficiently similar to ontology matching that comparable evaluation can be overtaken. However, it has enough differences, so that specific evaluations may be designed. We discuss such variations and design.
Data interlinking, Evaluation, Benchmark, Blocking, Instance matching
François Scharffe, Ghislain Atemezing, Raphaël Troncy, Fabien Gandon, Serena Villata, Bénédicte Bucher, Fayçal Hamdi, Laurent Bihanic, Gabriel Képéklian, Franck Cotton, Jérôme Euzenat, Zhengjie Fan, Pierre-Yves Vandenbussche, Bernard Vatant, Enabling linked data publication with the Datalift platform, in: Proc. AAAI workshop on semantic cities, Toronto (ONT CA), 2012
As many cities around the world provide access to raw public data along the Open Data movement, many questions arise concerning the accessibility of these data. Various data formats, duplicate identifiers, heterogeneous metadata schema descriptions, and diverse means to access or query the data exist. These factors make it difficult for consumers to reuse and integrate data sources to develop innovative applications. The Semantic Web provides a global solution to these problems by providing languages and protocols for describing and accessing datasets. This paper presents Datalift, a framework and a platform helping to lift raw data sources to semantic interlinked data sources.
Jérôme Euzenat, L'intelligence du web: l'information utile à portée de lien, Bulletin de l'AFIA 72:13-16, 2011
Jérôme Euzenat, Nathalie Abadie, Bénédicte Bucher, Zhengjie Fan, Houda Khrouf, Michael Luger, François Scharffe, Raphaël Troncy, Dataset interlinking module, Deliverable 4.2, Datalift, 32p., 2011
This report presents the first version of the interlinking module for the Datalift platform as well as strategies for future developments.
data interlinking, linked data, instance matching
François Scharffe, Jérôme Euzenat, MeLinDa: an interlinking framework for the web of data, Research report 7641, INRIA, Grenoble (FR), 21p., July 2011
The web of data consists of data published on the web in such a way that they can be interpreted and connected together. It is thus critical to establish links between these data, both for the web of data and for the semantic web that it contributes to feed. We consider here the various techniques developed for that purpose and analyze their commonalities and differences. We propose a general framework and show how the diverse techniques fit in the framework. From this framework we consider the relation between data interlinking and ontology matching. Although, they can be considered similar at a certain level (they both relate formal entities), they serve different purposes, but would find a mutual benefit at collaborating. We thus present a scheme under which it is possible for data linking tools to take advantage of ontology alignments.
Semantic web, Data interlinking, Instance matching, Ontology alignment, Web of data
François Scharffe, Jérôme Euzenat, Linked data meets ontology matching: enhancing data linking through ontology alignments, in: Proc. 3rd international conference on Knowledge engineering and ontology development (KEOD), Paris (FR), pp279-284, 2011
The Web of data consists of publishing data on the Web in such a way that they can be connected together and interpreted. It is thus critical to establish links between these data, both for the Web of data and for the Semantic Web that it contributes to feed. We consider here the various techniques which have been developed for that purpose and analyze their commonalities and differences. This provides a general framework that the diverse data linking systems instantiate. From this framework we consider the relation between data linking and ontology matching activities. Although, they can be considered similar at a certain level (they both relate formal entities), they serve different purposes: one acts at the schema level and the other at the instance level. However, they would find a mutual benefit at collaborating. We thus present a scheme under which it is possible for data linking tools to take advantage of ontology alignments. We present the features of expressive alignment languages that allows linking specifications to reuse ontology alignments in a natural way.
Semantic web, Linked data, Data linking, Ontology alignment, Ontology matching, Entity reonciliation, Object consolidation
Jérôme David, Jérôme Euzenat, Linked data from your pocket: The Android RDFContentProvider, in: Proc. 9th demonstration track on international semantic web conference (ISWC), Shanghai (CN), pp129-132, 2010
François Scharffe, Jérôme Euzenat, Méthodes et outils pour lier le web des données, in: Actes 17e conférenceAFIA-AFRIF sur reconnaissance des formes et intelligence artificielle (RFIA), Caen (FR), pp678-685, 2010
Le web des données consiste à publier des données sur le web de telle sorte qu'elles puissent être interprétées et connectées entre elles. Il est donc vital d'établir les liens entre ces données à la fois pour le web des données et pour le web sémantique qu'il contribue à nourrir. Nous proposons un cadre général dans lequel s'inscrivent les différentes techniques utilisées pour établir ces liens et nous montrons comment elles s'y insèrent. Nous proposons ensuite une architecture permettant d'associer les différents systèmes de liage de données et de les faire collaborer avec les systèmes développés pour la mise en correspondance d'ontologies qui présente de nombreux points communs avec la découverte de liens.
Semantic web, Data interlinking, Instance matching, Ontology alignment, Web of data