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

Evidence-based lean logic profiles for conceptual data modelling languages

Multiple logic-based reconstruction of conceptual data modelling languages such as EER, UML Class Diagrams, and ORM exists. They mainly cover various fragments of the languages and none are formalised such that the logic applies simultaneously for all three modelling language families as unifying mechanism. This hampers interchangeability, interoperability, and tooling support. In addition, due to the lack of a systematic design process of the logic used for the formalisation, hidden choices permeate the formalisations that have rendered them incompatible. We aim to address these problems, first, by structuring the logic design process in a methodological way. We generalise and extend the DSL design process to apply to logic language design more generally and, in particular, by incorporating an ontological analysis of language features in the process. Second, availing of this extended process, of evidence gathered of language feature usage, and of computational complexity insights from Description Logics (DL), we specify logic profiles taking into account the ontological commitments embedded in the languages. The profiles characterise the minimum logic structure needed to handle the semantics of conceptual models, enabling the development of interoperability tools. There is no known DL language that matches exactly the features of those profiles and the common core is small (in the tractable ALNI). Although hardly any inconsistencies can be derived with the profiles, it is promising for scalable runtime use of conceptual data models

Ontology-driven knowledge based autonomic management for telecommunication networks : theory, implementation, and applications

Current telecommunication networks are heterogeneous, with devices manufactured by different vendors, operating on di↵erent protocols, and recorded by databases with different schemas. This heterogeneity has resulted in current network managements system becoming enormously complicated and often relying on human intervention. Knowledge based network management, which relies on a universally accepted knowledge base of the network, has been discussed extensively as a promising solution for autonomic network management. To build an autonomic network management system, a universally-shared and machine interpretable knowledge base is required which describes the resources inside the telecommunication system. Semantic web technologies, especially ontologies, have been used for many years in building autonomic knowledge based systems in Artificial Intelligence. There is a pressing need for a standard ontology to enable technology agnostic, autonomic control in telecommunication networks. Network clients need to describe the resource they require, while resource providers need to describe the resource they can provide. With semantic technologies, the data inside complex hybrid networks can be treated as a distributed knowledge graph, where an SQL-like language – SPARQL is ready to search, locate, and configure a node or link of the network. The goal of this thesis is two-fold. The first goal is to build a formal, machine interpretable information model for the current heterogeneous networks. Thus, we propose an ontology, describing resources inside the hybrid telecommunication networks with different technology domains. This ontology follows the Device-Interface-Link pattern, which we identified during the modelling process for networks within different technology domains. The second goal is to develop a system that can use this ontology to build a knowledge base automatically and enable autonomic reasoning over it. We develop a Semantic Enabled Autonomic management system of software defined NETworks (SEANET), a lightweight, plug-and-play, technology-independent solution for knowledge-based autonomic network management that uses the proposed ontology. SEANET abstracts details of network management into a formally defined knowledge graph augmented by inference rules. SEANET’s architecture consists of three components: a knowledge base generator, a SPARQL engine, and an open API. With the open API developed, SEANET enables users without knowledge of Semantic Web or telecommunication networks to develop semantic-intelligent applications on their production networks. Use cases of the proposed ontology and system are demonstrated in the thesis, ranging from network management task and social applications