Search (13 results, page 1 of 1)

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Abstract

Purpose The purpose of this paper is to identify the concepts, component parts and relationships between vocabularies, linked data and knowledge graphs (KGs) from the perspectives of data and knowledge transitions. Design/methodology/approach This paper uses conceptual analysis methods. This study focuses on distinguishing concepts and analyzing composition and intercorrelations to explore data and knowledge transitions. Findings Vocabularies are the cornerstone for accurately building understanding of the meaning of data. Vocabularies provide for a data-sharing model and play an important role in supporting the semantic expression of linked data and defining the schema layer; they are also used for entity recognition, alignment and linkage for KGs. KGs, which consist of a schema layer and a data layer, are presented as cubes that organically combine vocabularies, linked data and big data. Originality/value This paper first describes the composition of vocabularies, linked data and KGs. More importantly, this paper innovatively analyzes and summarizes the interrelatedness of these factors, which comes from frequent interactions between data and knowledge. The three factors empower each other and can ultimately empower the Semantic Web.

Date

22. 1.2021 14:24:32

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Abstract

While thousands of ontologies exist on the web, a unified sys-tem for handling online ontologies - in particular with respect to discov-ery, versioning, access, quality-control, mappings - has not yet surfacedand users of ontologies struggle with many challenges. In this paper, wepresent an online ontology interface and augmented archive called DB-pedia Archivo, that discovers, crawls, versions and archives ontologies onthe DBpedia Databus. Based on this versioned crawl, different features,quality measures and, if possible, fixes are deployed to handle and sta-bilize the changes in the found ontologies at web-scale. A comparison toexisting approaches and ontology repositories is given.

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Date

22. 5.2021 12:43:05

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Abstract

The lack of standardization in the production, organization and dissemination of information in documentation centers and institutions alike, as a result from the digitization of collections and their availability on the internet has called for integration efforts. The sheer availability of multimedia content has fostered the development of many distinct and, most of the time, independent metadata standards for its description. This study aims at presenting and comparing the existing standards of metadata, vocabularies and ontologies for multimedia annotation and also tries to offer a synthetic overview of its main strengths and weaknesses, aiding efforts for semantic integration and enhancing the findability of available multimedia resources on the web. We also aim at unveiling the characteristics that could, should and are perhaps not being highlighted in the characterization of multimedia resources.

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Abstract

This paper describes an approach to path-finding in the intelligent graphs, with vertices being intelligent agents. A possible implementation of this approach is described, based on logical inference in distributed frame hierarchy. Presented approach can be used for implementing distributed intelligent information systems that include automatic navigation and path generation in hypertext, which can be used, for example in distance education, as well as for organizing intelligent web catalogues with flexible ontology-based information retrieval.

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Abstract

In the last few years, the size of Linked Open Data (LOD) describing artworks, in general or domain-specific Knowledge Graphs (KGs), is gradually increasing. This provides (art-)historians and Cultural Heritage professionals with a wealth of information to explore. Specifically, structured data about iconographical and iconological (icon) aspects, i.e. information about the subjects, concepts and meanings of artworks, are extremely valuable for the state-of-the-art of computational tools, e.g. content recognition through computer vision. Nevertheless, a data quality evaluation for art domains, fundamental for data reuse, is still missing. The purpose of this study is filling this gap with an overview of art-historical data quality in current KGs with a focus on the icon aspects. Design/methodology/approach This study's analyses are based on established KG evaluation methodologies, adapted to the domain by addressing requirements from art historians' theories. The authors first select several KGs according to Semantic Web principles. Then, the authors evaluate (1) their structures' suitability to describe icon information through quantitative and qualitative assessment and (2) their content, qualitatively assessed in terms of correctness and completeness. Findings This study's results reveal several issues on the current expression of icon information in KGs. The content evaluation shows that these domain-specific statements are generally correct but often not complete. The incompleteness is confirmed by the structure evaluation, which highlights the unsuitability of the KG schemas to describe icon information with the required granularity. Originality/value The main contribution of this work is an overview of the actual landscape of the icon information expressed in LOD. Therefore, it is valuable to cultural institutions by providing them a first domain-specific data quality evaluation. Since this study's results suggest that the selected domain information is underrepresented in Semantic Web datasets, the authors highlight the need for the creation and fostering of such information to provide a more thorough art-historical dimension to LOD.

Theme

Semantic Web

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Abstract

Traditionally connected to philosophy, the term ontology is increasingly related to information systems areas. Some researchers consider the approaches of the two disciplinary contexts to be completely different. Others consider that, although different, they should talk to each other, as both seek to answer similar questions. With the extensive literature on this topic, we intend to contribute to the understanding of the use of the term ontology in current research and which references support this use. An exploratory study was developed with a mixed methodology and a sample collected from the Web of Science of articles publishe in 2018. The results show the current prevalence of computer science in studies related to ontology and also of Gruber's view suggesting ontology as kind of conceptualization, a dominant view in that field. Some researchers, particularly in the field of biomedicine, do not adhere to this dominant view but to another one that seems closer to ontological study in the philosophical context. The term ontology, in the context of information systems, appears to be consolidating with a meaning different from the original, presenting traces of the process of "metaphorization" in the transfer of the term between the two fields of study.

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Abstract

The purpose of this paper is to provide a critical analysis from an ethical perspective of how the concept of indigenous wayfinding and voyaging is mapped in knowledge representation, organization and discovery systems. Design/methodology/approach In this study, the Dewey Decimal Classification, the Library of Congress Subject Headings, the Library of Congress Classifications systems and the Web of Science citation database were methodically examined to determine how these systems represent and facilitate the discovery of indigenous knowledge of wayfinding and voyaging. Findings The analysis revealed that there was no dedicated representation of the indigenous practices of wayfinding and voyaging in the major knowledge representation, organization and discovery systems. By scattering indigenous practice across various, often very broad and unrelated classes, coherence in the record is disrupted, resulting in misrepresentation of these indigenous concepts. Originality/value This study contributes to a relatively limited research literature on representation and organization of indigenous knowledge of wayfinding and voyaging. This study calls to foster a better understanding and appreciation for the rich knowledge that indigenous cultures provide for an enlightened society.

Object

Web of Science

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Content

# Community action on individual ontologies We would like to call on all ontology maintainers and consumers to help us increase the average star rating of the web of ontologies by fixing and improving its ontologies. You can easily check an ontology at https://archivo.dbpedia.org/info. If you are an ontology maintainer just release a patched version - archivo will automatically pick it up 8 hours later. If you are a user of an ontology and want your consumed data to become FAIRer, please inform the ontology maintainer about the issues found with Archivo. The star rating is very basic and only requires fixing small things. However, theimpact on technical and legal usability can be immense.
# Community action on all ontologies (quality, FAIRness, conformity) Archivo is extensible and allows contributions to give consumers a central place to encode their requirements. We envision fostering adherence to standards and strengthening incentives for publishers to build a better (FAIRer) web of ontologies. 1. SHACL (https://www.w3.org/TR/shacl/, co-edited by DBpedia's CTO D. Kontokostas) enables easy testing of ontologies. Archivo offers free SHACL continuous integration testing for ontologies. Anyone can implement their SHACL tests and add them to the SHACL library on Github. We believe that there are many synergies, i.e. SHACL tests for your ontology are helpful for others as well. 2. We are looking for ontology experts to join DBpedia and discuss further validation (e.g. stars) to increase FAIRness and quality of ontologies. We are forming a steering committee and also a PC for the upcoming Vocarnival at SEMANTiCS 2021. Please message hellmann@informatik.uni-leipzig.de <mailto:hellmann@informatik.uni-leipzig.de>if you would like to join. We would like to extend the Archivo platform with relevant visualisations, tests, editing aides, mapping management tools and quality checks.
# How does Archivo work? Each week Archivo runs several discovery algorithms to scan for new ontologies. Once discovered Archivo checks them every 8 hours. When changes are detected, Archivo downloads and rates and archives the latest snapshot persistently on the DBpedia Databus. # Archivo's mission Archivo's mission is to improve FAIRness (findability, accessibility, interoperability, and reusability) of all available ontologies on the Semantic Web. Archivo is not a guideline, it is fully automated, machine-readable and enforces interoperability with its star rating. - Ontology developers can implement against Archivo until they reach more stars. The stars and tests are designed to guarantee the interoperability and fitness of the ontology. - Ontology users can better find, access and re-use ontologies. Snapshots are persisted in case the original is not reachable anymore adding a layer of reliability to the decentral web of ontologies.

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Abstract

This contribution presents the principal features of ontologies, drawing special attention to the comparison between ontologies and the different kinds of know­ledge organization systems (KOS). The focus is on the semantic richness exhibited by ontologies, which allows the creation of a great number of relationships between terms. That establishes ontologies as the most evolved type of KOS. The concepts of "conceptualization" and "formalization" and the key components of ontologies are described and discussed, along with upper and domain ontologies and special typologies, such as bibliographical ontologies and biomedical ontologies. The use of ontologies in the digital libraries environment, where they have replaced thesauri for query expansion in searching, and the role they are playing in the Semantic Web, especially for semantic interoperability, are sketched.

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Abstract

The article identifies the core literature available on flood ontologies and presents a review on these ontologies from various perspectives like its purpose, type, design methodologies, ontologies (re)used, and also their focus on specific flood disaster phases. The study was conducted in two stages: i) literature identification, where the systematic literature review methodology was employed; and, ii) ontological review, where the parametric approach was applied. The study resulted in a set of fourteen papers discussing the flood ontology (FO). The ontological review revealed that most of the flood ontologies were task ontologies, formal, modular, and used web ontology language (OWL) for their representation. The most (re)used ontologies were SWEET, SSN, Time, and Space. METHONTOLOGY was the preferred design methodology, and for evaluation, application-based or data-based approaches were preferred. The majority of the ontologies were built around the response phase of the disaster. The unavailability of the full ontologies somewhat restricted the current study as the structural ontology metrics are missing. But the scientific community, the developers, of flood disaster management systems can refer to this work for their research to see what is available in the literature on flood ontology and the other major domains essential in building the FO.

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Abstract

This study considers the expressiveness (that is the expressive power or expressivity) of different types of Knowledge Organization Systems (KOS) and discusses its potential to be machine-processable in the context of the Semantic Web. For this purpose, the theoretical foundations of KOS are reviewed based on conceptualizations introduced by the Functional Requirements for Subject Authority Data (FRSAD) and the Simple Knowledge Organization System (SKOS); natural language processing techniques are also implemented. Applying a comparative analysis, the dataset comprises a thesaurus (Eurovoc), a subject headings system (LCSH) and a classification scheme (DDC). These are compared with an ontology (CIDOC-CRM) by focusing on how they define and handle concepts and relations. It was observed that LCSH and DDC focus on the formalism of character strings (nomens) rather than on the modelling of semantics; their definition of what constitutes a concept is quite fuzzy, and they comprise a large number of complex concepts. By contrast, thesauri have a coherent definition of what constitutes a concept, and apply a systematic approach to the modelling of relations. Ontologies explicitly define diverse types of relations, and are by their nature machine-processable. The paper concludes that the potential of both the expressiveness and machine processability of each KOS is extensively regulated by its structural rules. It is harder to represent subject headings and classification schemes as semantic networks with nodes and arcs, while thesauri are more suitable for such a representation. In addition, a paradigm shift is revealed which focuses on the modelling of relations between concepts, rather than the concepts themselves.

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Date

20. 1.2015 18:30:22