Formalizing enrichment mechanisms for bibliographic ontologies in the Semantic Web

This paper presents an analysis of current limitations to the reuse of bibliographic data in the Semantic Web and a research proposal towards solutions to overcome them. The limitations identified derive from the insufficient convergence between existing bibliographic ontologies and the principles and techniques of linked open data (LOD); lack of a common conceptual framework for a diversity of standards often used together; reduced use of links to external vocabularies and absence of Semantic Web mechanisms to formalize relationships between vocabularies, as well as limitations of Semantic Web languages for the requirements of bibliographic data interoperability. A proposal is advanced to investigate the hypothesis of creating a reference model and specifying a superontology to overcome the misalignments found, as well as the use of SHACL (Shapes Constraint Language) to solve current limitations of RDF languages.info:eu-repo/semantics/acceptedVersio

From the web of bibliographic data to the web of bibliographic meaning: structuring, interlinking and validating ontologies on the semantic web

Bibliographic data sets have revealed good levels of technical interoperability observing the principles and good practices of linked data. However, they have a low level of quality from the semantic point of view, due to many factors: lack of a common conceptual framework for a diversity of standards often used together, reduced number of links between the ontologies underlying data sets, proliferation of heterogeneous vocabularies, underuse of semantic mechanisms in data structures, "ontology hijacking" (Feeney et al., 2018), point-to-point mappings, as well as limitations of semantic web languages for the requirements of bibliographic data interoperability. After reviewing such issues, a research direction is proposed to overcome the misalignments found by means of a reference model and a superontology, using Shapes Constraint Language (SHACL) to solve current limitations of RDF languages.info:eu-repo/semantics/acceptedVersio

Semantic enrichment of knowledge sources supported by domain ontologies

This thesis introduces a novel conceptual framework to support the creation of knowledge representations based on enriched Semantic Vectors, using the classical vector space model approach extended with ontological support. One of the primary research challenges addressed here relates to the process of formalization and representation of document contents, where most existing approaches are limited and only take into account the explicit, word-based information in the document. This research explores how traditional knowledge representations can be enriched through incorporation of implicit information derived from the complex relationships (semantic associations) modelled by domain ontologies with the addition of information presented in documents. The relevant achievements pursued by this thesis are the following: (i) conceptualization of a model that enables the semantic enrichment of knowledge sources supported by domain experts; (ii) development of a method for extending the traditional vector space, using domain ontologies; (iii) development of a method to support ontology learning, based on the discovery of new ontological relations expressed in non-structured information sources; (iv) development of a process to evaluate the semantic enrichment; (v) implementation of a proof-of-concept, named SENSE (Semantic Enrichment kNowledge SourcEs), which enables to validate the ideas established under the scope of this thesis; (vi) publication of several scientific articles and the support to 4 master dissertations carried out by the department of Electrical and Computer Engineering from FCT/UNL. It is worth mentioning that the work developed under the semantic referential covered by this thesis has reused relevant achievements within the scope of research European projects, in order to address approaches which are considered scientifically sound and coherent and avoid “reinventing the wheel”.European research projects - CoSpaces (IST-5-034245), CRESCENDO (FP7-234344) and MobiS (FP7-318452

Bibliographic ontologies and the semantic web: limitations and research proposals

A literatura sobre dados e ontologias bibliográficos na Web Semântica identifica problemas, não ao nível das instâncias de dados ou da sua publicação em conjuntos isolados, mas sim relativamente às ontologias que descrevem os conceitos que lhe estão subjacentes, com reflexo na qualidade da interoperabilidade semântica e na partilha de ontologias entre sistemas. Aborda-se a adequação à Web Semântica dos modelos conceptuais e limitações de FRBR - Functional Requirements for Bibliographic Records (IFLA 1998, 2018) ; a ausência de enquadramento conceptual comum; a insuficiência de mecanismos semânticos; a baixa e deficiente reutilização de vocabulários externos; e a inadequação das metodologias de mapeamento aplicadas. Apresenta-se um projeto de investigação que propõe uma solução para os problemas semânticos de partilha de ontologias, através da criação de um modelo de referência conceptualmente enquadrador e de uma ontologia de referência que funcione como instrumento de relacionamento semântico de alto nível e de validação de dados, recorrendo à linguagem SHACL - Shapes Constraint Language (KNUBLAUCH e KONTOKOSTAS, 2017).info:eu-repo/semantics/publishedVersio

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

A Knowledge Graph Based Integration Approach for Industry 4.0

The fourth industrial revolution, Industry 4.0 (I40) aims at creating smart factories employing among others Cyber-Physical Systems (CPS), Internet of Things (IoT) and Artificial Intelligence (AI). Realizing smart factories according to the I40 vision requires intelligent human-to-machine and machine-to-machine communication. To achieve this communication, CPS along with their data need to be described and interoperability conflicts arising from various representations need to be resolved. For establishing interoperability, industry communities have created standards and standardization frameworks. Standards describe main properties of entities, systems, and processes, as well as interactions among them. Standardization frameworks classify, align, and integrate industrial standards according to their purposes and features. Despite being published by official international organizations, different standards may contain divergent definitions for similar entities. Further, when utilizing the same standard for the design of a CPS, different views can generate interoperability conflicts. Albeit expressive, standardization frameworks may represent divergent categorizations of the same standard to some extent, interoperability conflicts need to be resolved to support effective and efficient communication in smart factories. To achieve interoperability, data need to be semantically integrated and existing conflicts conciliated. This problem has been extensively studied in the literature. Obtained results can be applied to general integration problems. However, current approaches fail to consider specific interoperability conflicts that occur between entities in I40 scenarios. In this thesis, we tackle the problem of semantic data integration in I40 scenarios. A knowledge graphbased approach allowing for the integration of entities in I40 while considering their semantics is presented. To achieve this integration, there are challenges to be addressed on different conceptual levels. Firstly, defining mappings between standards and standardization frameworks; secondly, representing knowledge of entities in I40 scenarios described by standards; thirdly, integrating perspectives of CPS design while solving semantic heterogeneity issues; and finally, determining real industry applications for the presented approach. We first devise a knowledge-driven approach allowing for the integration of standards and standardization frameworks into an Industry 4.0 knowledge graph (I40KG). The standards ontology is used for representing the main properties of standards and standardization frameworks, as well as relationships among them. The I40KG permits to integrate standards and standardization frameworks while solving specific semantic heterogeneity conflicts in the domain. Further, we semantically describe standards in knowledge graphs. To this end, standards of core importance for I40 scenarios are considered, i.e., the Reference Architectural Model for I40 (RAMI4.0), AutomationML, and the Supply Chain Operation Reference Model (SCOR). In addition, different perspectives of entities describing CPS are integrated into the knowledge graphs. To evaluate the proposed methods, we rely on empirical evaluations as well as on the development of concrete use cases. The attained results provide evidence that a knowledge graph approach enables the effective data integration of entities in I40 scenarios while solving semantic interoperability conflicts, thus empowering the communication in smart factories

Semantic adaptability for the systems interoperability

In the current global and competitive business context, it is essential that enterprises adapt their knowledge resources in order to smoothly interact and collaborate with others. However, due to the existent multiculturalism of people and enterprises, there are different representation views of business processes or products, even inside a same domain. Consequently, one of the main problems found in the interoperability between enterprise systems and applications is related to semantics. The integration and sharing of enterprises knowledge to build a common lexicon, plays an important role to the semantic adaptability of the information systems. The author proposes a framework to support the development of systems to manage dynamic semantic adaptability resolution. It allows different organisations to participate in a common knowledge base building, letting at the same time maintain their own views of the domain, without compromising the integration between them. Thus, systems are able to be aware of new knowledge, and have the capacity to learn from it and to manage its semantic interoperability in a dynamic and adaptable way. The author endorses the vision that in the near future, the semantic adaptability skills of the enterprise systems will be the booster to enterprises collaboration and the appearance of new business opportunities

Social and Semantic Contexts in Tourist Mobile Applications

The ongoing growth of the World Wide Web along with the increase possibility of access information through a variety of devices in mobility, has defi nitely changed the way users acquire, create, and personalize information, pushing innovative strategies for annotating and organizing it. In this scenario, Social Annotation Systems have quickly gained a huge popularity, introducing millions of metadata on di fferent Web resources following a bottom-up approach, generating free and democratic mechanisms of classi cation, namely folksonomies. Moving away from hierarchical classi cation schemas, folksonomies represent also a meaningful mean for identifying similarities among users, resources and tags. At any rate, they suff er from several limitations, such as the lack of specialized tools devoted to manage, modify, customize and visualize them as well as the lack of an explicit semantic, making di fficult for users to bene fit from them eff ectively. Despite appealing promises of Semantic Web technologies, which were intended to explicitly formalize the knowledge within a particular domain in a top-down manner, in order to perform intelligent integration and reasoning on it, they are still far from reach their objectives, due to di fficulties in knowledge acquisition and annotation bottleneck. The main contribution of this dissertation consists in modeling a novel conceptual framework that exploits both social and semantic contextual dimensions, focusing on the domain of tourism and cultural heritage. The primary aim of our assessment is to evaluate the overall user satisfaction and the perceived quality in use thanks to two concrete case studies. Firstly, we concentrate our attention on contextual information and navigation, and on authoring tool; secondly, we provide a semantic mapping of tags of the system folksonomy, contrasted and compared to the expert users' classi cation, allowing a bridge between social and semantic knowledge according to its constantly mutual growth. The performed user evaluations analyses results are promising, reporting a high level of agreement on the perceived quality in use of both the applications and of the speci c analyzed features, demonstrating that a social-semantic contextual model improves the general users' satisfactio

requirements and use cases

In this report, we introduce our initial vision of the Corporate Semantic Web as the next step in the broad field of Semantic Web research. We identify requirements of the corporate environment and gaps between current approaches to tackle problems facing ontology engineering, semantic collaboration, and semantic search. Each of these pillars will yield innovative methods and tools during the project runtime until 2013. Corporate ontology engineering will improve the facilitation of agile ontology engineering to lessen the costs of ontology development and, especially, maintenance. Corporate semantic collaboration focuses the human-centered aspects of knowledge management in corporate contexts. Corporate semantic search is settled on the highest application level of the three research areas and at that point it is a representative for applications working on and with the appropriately represented and delivered background knowledge. We propose an initial layout for an integrative architecture of a Corporate Semantic Web provided by these three core pillars