Reuse of terminological resources for efficient ontological engineering in Life Sciences

This paper is intended to explore how to use terminological resources for ontology engineering. Nowadays there are several biomedical ontologies describing overlapping domains, but there is not a clear correspondence between the concepts that are supposed to be equivalent or just similar. These resources are quite precious but their integration and further development are expensive. Terminologies may support the ontological development in several stages of the lifecycle of the ontology; e.g. ontology integration. In this paper we investigate the use of terminological resources during the ontology lifecycle. We claim that the proper creation and use of a shared thesaurus is a cornerstone for the successful application of the Semantic Web technology within life sciences. Moreover, we have applied our approach to a real scenario, the Health-e-Child (HeC) project, and we have evaluated the impact of filtering and re-organizing several resources. As a result, we have created a reference thesaurus for this project, named HeCTh

Challenges to knowledge representation in multilingual contexts

To meet the increasing demands of the complex inter-organizational processes and the demand for continuous innovation and internationalization, it is evident that new forms of organisation are being adopted, fostering more intensive collaboration processes and sharing of resources, in what can be called collaborative networks (Camarinha-Matos, 2006:03). Information and knowledge are crucial resources in collaborative networks, being their management fundamental processes to optimize. Knowledge organisation and collaboration systems are thus important instruments for the success of collaborative networks of organisations having been researched in the last decade in the areas of computer science, information science, management sciences, terminology and linguistics. Nevertheless, research in this area didn’t give much attention to multilingual contexts of collaboration, which pose specific and challenging problems. It is then clear that access to and representation of knowledge will happen more and more on a multilingual setting which implies the overcoming of difficulties inherent to the presence of multiple languages, through the use of processes like localization of ontologies. Although localization, like other processes that involve multilingualism, is a rather well-developed practice and its methodologies and tools fruitfully employed by the language industry in the development and adaptation of multilingual content, it has not yet been sufficiently explored as an element of support to the development of knowledge representations - in particular ontologies - expressed in more than one language. Multilingual knowledge representation is then an open research area calling for cross-contributions from knowledge engineering, terminology, ontology engineering, cognitive sciences, computational linguistics, natural language processing, and management sciences. This workshop joined researchers interested in multilingual knowledge representation, in a multidisciplinary environment to debate the possibilities of cross-fertilization between knowledge engineering, terminology, ontology engineering, cognitive sciences, computational linguistics, natural language processing, and management sciences applied to contexts where multilingualism continuously creates new and demanding challenges to current knowledge representation methods and techniques. In this workshop six papers dealing with different approaches to multilingual knowledge representation are presented, most of them describing tools, approaches and results obtained in the development of ongoing projects. In the first case, Andrés Domínguez Burgos, Koen Kerremansa and Rita Temmerman present a software module that is part of a workbench for terminological and ontological mining, Termontospider, a wiki crawler that aims at optimally traverse Wikipedia in search of domainspecific texts for extracting terminological and ontological information. The crawler is part of a tool suite for automatically developing multilingual termontological databases, i.e. ontologicallyunderpinned multilingual terminological databases. In this paper the authors describe the basic principles behind the crawler and summarized the research setting in which the tool is currently tested. In the second paper, Fumiko Kano presents a work comparing four feature-based similarity measures derived from cognitive sciences. The purpose of the comparative analysis presented by the author is to verify the potentially most effective model that can be applied for mapping independent ontologies in a culturally influenced domain. For that, datasets based on standardized pre-defined feature dimensions and values, which are obtainable from the UNESCO Institute for Statistics (UIS) have been used for the comparative analysis of the similarity measures. The purpose of the comparison is to verify the similarity measures based on the objectively developed datasets. According to the author the results demonstrate that the Bayesian Model of Generalization provides for the most effective cognitive model for identifying the most similar corresponding concepts existing for a targeted socio-cultural community. In another presentation, Thierry Declerck, Hans-Ulrich Krieger and Dagmar Gromann present an ongoing work and propose an approach to automatic extraction of information from multilingual financial Web resources, to provide candidate terms for building ontology elements or instances of ontology concepts. The authors present a complementary approach to the direct localization/translation of ontology labels, by acquiring terminologies through the access and harvesting of multilingual Web presences of structured information providers in the field of finance, leading to both the detection of candidate terms in various multilingual sources in the financial domain that can be used not only as labels of ontology classes and properties but also for the possible generation of (multilingual) domain ontologies themselves. In the next paper, Manuel Silva, António Lucas Soares and Rute Costa claim that despite the availability of tools, resources and techniques aimed at the construction of ontological artifacts, developing a shared conceptualization of a given reality still raises questions about the principles and methods that support the initial phases of conceptualization. These questions become, according to the authors, more complex when the conceptualization occurs in a multilingual setting. To tackle these issues the authors present a collaborative platform – conceptME - where terminological and knowledge representation processes support domain experts throughout a conceptualization framework, allowing the inclusion of multilingual data as a way to promote knowledge sharing and enhance conceptualization and support a multilingual ontology specification. In another presentation Frieda Steurs and Hendrik J. Kockaert present us TermWise, a large project dealing with legal terminology and phraseology for the Belgian public services, i.e. the translation office of the ministry of justice, a project which aims at developing an advanced tool including expert knowledge in the algorithms that extract specialized language from textual data (legal documents) and whose outcome is a knowledge database including Dutch/French equivalents for legal concepts, enriched with the phraseology related to the terms under discussion. Finally, Deborah Grbac, Luca Losito, Andrea Sada and Paolo Sirito report on the preliminary results of a pilot project currently ongoing at UCSC Central Library, where they propose to adapt to subject librarians, employed in large and multilingual Academic Institutions, the model used by translators working within European Union Institutions. The authors are using User Experience (UX) Analysis in order to provide subject librarians with a visual support, by means of “ontology tables” depicting conceptual linking and connections of words with concepts presented according to their semantic and linguistic meaning. The organizers hope that the selection of papers presented here will be of interest to a broad audience, and will be a starting point for further discussion and cooperation

Vers une description évolutive et une exploration efficace des concepts et des artefacts d'architecture microservices

RÉSUMÉ : L'adoption de l'architecture Microservices (MSA) pour la conception de systèmes logiciels est une tendance en industrie et en recherche. De nature compositionnelle et distribuée, les systèmes basés sur l'architecture Microservices sont composés de services ayant une responsabilité restreinte et bien définie, visant un isolement complet dans une perspective de non-partage de ressources. Les systèmes basés sur des microservices sont souvent classés comme de systèmes « Cloud-Native ». L'adoption de l'architecture Microservices représente un changement de paradigme technologique et managérial comportant des défis, notamment : la taille, la portée et le nombre de services, et leurs interopérabilité et réutilisation. Outre ces défis, la compréhension, l'adoption et l'implémentation des principes fondamentaux de ce style architectural sont des challenges qui impactent la conception d'architectures microservices efficaces et cohérentes. En effet, l'absence d'un large consensus sur certains principes et termes clés de cette architecture mènent à sa mauvaise compréhension et par conséquent à des implémentations incorrectes. Cette absence de consensus est une manifestation concrète de l'immaturité de cette architecture qui mène à des défis lors de la formalisation des connaissances. Également, il manque une méthode uniforme capable de supporter les concepteurs lors de la modélisation des microservices, notamment dans l'agencement des différentes composantes. À cela s'ajoute l'absence de modèles conceptuels pouvant guider les ingénieurs dans les premières phases de conception de ces systèmes. Plusieurs approches ont été utilisées pour la modélisation d'architectures microservices, tels que : formelle et informelle, manuelle et automatique et toutes les combinaisons de ces quatre, mais ces approches ne répondent pas à tous les défis rencontrés par les concepteurs. Pour faciliter la modélisation des microservices et rendre le processus plus efficace, il est nécessaire de développer des approches de conception et de représentation alternatives. Dans cette perspective, nous proposons une approche ontologique capable de répondre autant aux défis de conception que de représentation des architectures microservices. Dans ce mémoire, nous vous présentons nos résultats de recherche dont la principale contribution est une ontologie du domaine des architectures Microservices définie en suivant les principes de logique de description et formalisée en utilisant le langage « Web Ontology Language » (OWL), une technologie clé du Web sémantique. À cette ontologie nous avons donné le nom d'« Ontology of Microservices Architecture Concepts » (OMSAC). OMSAC contient suffisamment de vocabulaire pour décrire les concepts qui définissent l'architecture Microservices et pour représenter les différents artefacts composant ces architectures. Sa structure permet une évolution rapide et est capable de prendre en charge les enjeux liés à l'immaturité actuelle de ces architectures. En tant que technologie d'intelligence artificielle (IA), les ontologies possèdent des capacités de raisonnement avancées auxquelles il est possible d'ajouter d'autres technologies pour les étendre et ainsi répondre à différents besoins. Avec cet objectif, nous avons utilisé OMSAC conjointement avec des techniques d'apprentissage machine pour modéliser et analyser des architectures microservices afin de calculer le degré de similitude entre différents microservices appartenant à différents systèmes. Ce cas d'utilisation d'OMSAC constitue une contribution supplémentaire de notre recherche et renforce les perspectives de recherche dans l'assistance, l'outillage et l'automatisation de la modélisation des architectures microservices. Cette contribution montre également la pertinence de la recherche de mécanismes permettant de faire de l'analytique avancée sur les modèles d'architectures. Dans des travaux de recherche futurs, nous nous intéresserons au développent de ces mécanismes, et planifions la conception d'un assistant intelligent capable de projeter des architectures microservices basées sur les meilleures pratiques et favorisant la réutilisation de microservices existants. Également, nous souhaitons développer un langage dédié afin d'abstraire les syntaxes d'OWL et du langage de requête SPARQL pour faciliter l'utilisation d'OMSAC par les concepteurs, ingénieurs et programmeurs qui ne sont pas familiers avec ces technologies du Web sémantique. -- Mot(s) clé(s) en français : Architectures microservices, ontologies, modélisation de systèmes logiciels, apprentissage automatique. -- ABSTRACT : The use of Microservices Architecture (MSA) for designing software systems has become a trend in industry and research. Adopting MSA represents a technological and managerial shift with challenges including the size, scope, number, interoperability and reuse of microservices, modelling using multi-viewpoints, as well as the adequate understanding, adoption, and implementation of fundamental principles of the Microservices Architecture. Adequately undertaking these challenges is mandatory for designing effective MSA-based systems. In this thesis, we explored an ontological representation of the knowledge concerning the Microservices Architecture domain. This representation is capable of addressing MSA understanding and modelling challenges. As a result of this research, we propose the Ontology of Microservices Architecture Concepts (OMSAC), which is a domain ontology containing enough vocabulary to describe MSA concepts and artifacts and in a form to allow fast evolution and advanced analytical capabilities. -- Mot(s) clé(s) en anglais : Microservices Architecture, Ontologies, Conceptual modelling, machine learning

A MAUT approach for reusing ontologies

Knowledge resource reuse has become a popular approach within the ontology engineering field, mainly because it can speed up the ontology development process, saving time and money and promoting the application of good practices. The NeOn Methodology provides guidelines for reuse. These guidelines include the selection of the most appropriate knowledge resources for reuse in ontology development. This is a complex decision-making problem where different conflicting objectives, like the reuse cost, understandability, integration workload and reliability, have to be taken into account simultaneously. GMAA is a PC-based decision support system based on an additive multi-attribute utility model that is intended to allay the operational difficulties involved in the Decision Analysis methodology. The paper illustrates how it can be applied to select multimedia ontologies for reuse to develop a new ontology in the multimedia domain. It also demonstrates that the sensitivity analyses provided by GMAA are useful tools for making a final recommendation

Shaping Translation: A View from Terminology Research

This article discusses translation-oriented terminology over a time frame that is more or less congruent with META’s life span. Against the backdrop of the place of terminology in shaping professional issues in translation, we initially describe some stages in the process by which terminology has acquired institutional identity in translator training programmes and constituted its knowledge base. We then suggest a framework that seeks to show how theory construction in terminology has contributed to a better understanding of technical texts and their translation. A final section similarly illustrates how this overarching theoretical scheme has driven, or is at least consistent with, products and methods in the translation sector of the so-called language industries.Cet article aborde la terminologie dans l’optique de la traduction (profession, pratique, théorie) durant les cinquante dernières années - période correspondant à la vie de META. Après avoir esquissé ce que le profil contemporain du traducteur doit à la terminologie, l’article examine à tour de rôle: (a) les étapes dans la constitution de cette science des termes, (b) comment cette science a acquis droit de cité dans les programmes de formation des traducteurs, (c) le cadre explicatif contemporain qu’elle propose pour rendre compte des textes techniques et de leur traduction, (d) les retombées de ce cadre pour les secteurs des industries de la langue qui se justifient largement par rapport à la traduction