A Survey of the First 20 Years of Research on Semantic Web and Linked Data

International audienceThis paper is a survey of the research topics in the field of Semantic Web, Linked Data and Web of Data. This study looks at the contributions of this research community over its first twenty years of existence. Compiling several bibliographical sources and bibliometric indicators , we identify the main research trends and we reference some of their major publications to provide an overview of that initial period. We conclude with some perspectives for the future research challenges.Cet article est une étude des sujets de recherche dans le domaine du Web sémantique, des données liées et du Web des données. Cette étude se penche sur les contributions de cette communauté de recherche au cours de ses vingt premières années d'existence. En compilant plusieurs sources bibliographiques et indicateurs bibliométriques, nous identifions les principales tendances de la recherche et nous référençons certaines de leurs publications majeures pour donner un aperçu de cette période initiale. Nous concluons avec une discussion sur les tendances et perspectives de recherche

Ontology Matching: OM-2018: Proceedings of the ISWC Workshop

International audienceno abstrac

Génération automatique d'alignements complexes d'ontologies

Le web de données liées (LOD) est composé de nombreux entrepôts de données. Ces données sont décrites par différents vocabulaires (ou ontologies). Chaque ontologie a une terminologie et une modélisation propre ce qui les rend hétérogènes. Pour lier et rendre les données du web de données liées interopérables, les alignements d'ontologies établissent des correspondances entre les entités desdites ontologies. Il existe de nombreux systèmes d'alignement qui génèrent des correspondances simples, i.e., ils lient une entité à une autre entité. Toutefois, pour surmonter l'hétérogénéité des ontologies, des correspondances plus expressives sont parfois nécessaires. Trouver ce genre de correspondances est un travail fastidieux qu'il convient d'automatiser. Dans le cadre de cette thèse, une approche d'alignement complexe basée sur des besoins utilisateurs et des instances communes est proposée. Le domaine des alignements complexes est relativement récent et peu de travaux adressent la problématique de leur évaluation. Pour pallier ce manque, un système d'évaluation automatique basé sur de la comparaison d'instances est proposé. Ce système est complété par un jeu de données artificiel sur le domaine des conférences.The Linked Open Data (LOD) cloud is composed of data repositories. The data in the repositories are described by vocabularies also called ontologies. Each ontology has its own terminology and model. This leads to heterogeneity between them. To make the ontologies and the data they describe interoperable, ontology alignments establish correspondences, or links between their entities. There are many ontology matching systems which generate simple alignments, i.e., they link an entity to another. However, to overcome the ontology heterogeneity, more expressive correspondences are sometimes needed. Finding this kind of correspondence is a fastidious task that can be automated. In this thesis, an automatic complex matching approach based on a user's knowledge needs and common instances is proposed. The complex alignment field is still growing and little work address the evaluation of such alignments. To palliate this lack, we propose an automatic complex alignment evaluation system. This system is based on instances. A famous alignment evaluation dataset has been extended for this evaluation

Knowledge representation, storage and retrieval for BIM supported building evacuation design

Safe evacuation design is a complex process, which relies on crowd simulation models when assessing the performance of large or complicated building layouts. Current simulation methods and tools lack automation and are limited to geometry when relying on BIM interoperability. The use of semantic web linked data is seen as a step towards integrating and leveraging current digital resources to facilitate intelligent and automatic design capable of knowledge processing. An intelligent software system has been developed which is capable of integrating multiple information sources and which can facilitate fast automatic construction and analysis of crowd simulation models for design decision support. The system includes several developed OWL ontologies and SWRL rules which represent design knowledge from the fire evacuation field, thus being able to process and store data about a multi-disciplinary design field. The work conducted towards the development of the system involved investigation into crowd analysis tools, evacuation and digital building models. The ontology and knowledge operators are presented and discussed, providing insight into future exploration of such methods with the aim of outlining their benefits and limitations. The system and knowledge engineered have been tested using a case study, proving they are capable of fast processing and correct interpretation of model data

THE GOLDEN THREAD OF INFORMATION AND FIRE SAFETY IN CONSTRUCTION: Making our buildings safer through the development of a Robust Design Specification Strategy and BIM Framework Integration.

In this research, the development of a novel expert knowledge based system for fire safety building design specification and compliance is discussed. Its purpose is to create a beneficial design aid that is integrated with building information modelling (BIM), for helping to design and maintain safer buildings, to ease the navigation through a complex regulatory compliance regime and to mitigate risk of various potential contributors. The research reflects on the current status of the UK fire safety regulatory system in the construction industry, key professional competencies and the areas in which risk could be mitigated through the implementation of this technology. Whilst the system developed in this research is based upon the UK regulatory framework and guidance, it is adaptable to any international country building regulations and standards. The high-level system framework has been developed, connecting the expert knowledge based system to the proprietary building information modelling (BIM) software and to both a descriptive and performance based specification system. The additional purpose of BIM integration is to create an auditable fire safety design trail of a digital record for the building throughout its lifecycle, from initial design through to construction and subsequent occupancy. The feasibility of implementing an expert knowledge base system to aid both design, specification, and compliance checking was tested through the development of a system prototype. Connectivity to the building model and specification are critical in ensuring all outputs are both aligned and robust. Data is proposed to be captured within a common data environment (CDE), aligned to the UK BIM framework, thus capturing a ‘golden thread of information’. The outcome from testing of the proposed expert knowledge base system demonstrates strong potential for an effective technological aid to mitigate risk of failure or non-compliance of designed and built assets in respect to fire safety

A new direction for public understanding of science: toward a participant-centered model of science engagement.

Engaging the public with science is not an easy task. When presented, scientific findings, public health recommendations, and other scientific information filter through the personal values, beliefs, and biases of members of the public. Science communicators must contend with these differences in order to be effective in cultivating a public understanding of science. Given the importance of scientific understanding for living well in a complex world, increasing science understanding through science engagement is imperative. The field of public engagement with science is dichotomized by a public information deficit approach and a contextualist approach. The deficit approach prizes the factual content of science, its epistemic authority, and its communication to the public while the contextualist approach recognizes the sociocultural embeddedness of science in society, how science is received by publics, and how local knowledges intersect with science. I contend both approaches are incomplete, and I put forth a synthesis. My approach, the participant-centered model of science engagement, incorporates the factual content of science and its epistemic authority, but in a way that is sensitive to context. I argue for a deliberative democratic approach to public engagement with science and articulate a model inspired by learner-centered approaches to teaching in the formal education literature. I outline and assess six participant-centered strategies along with recommendations for particular practices associated with each

Proceedings of the 15th ISWC workshop on Ontology Matching (OM 2020)

15th International Workshop on Ontology Matching co-located with the 19th International Semantic Web Conference (ISWC 2020)International audienc