Digital Heraldry - The State of the Art and New Approaches Based on Semantic Web Technologies

Author(s):  
Torsten Hiltmann ◽  
Thomas Riechert
Semantic Web ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 885-886
Author(s):  
Dhavalkumar Thakker ◽  
Pankesh Patel ◽  
Muhammad Intizar Ali ◽  
Tejal Shah

Welcome to this special issue of the Semantic Web (SWJ) journal. The special issue compiles four technical contributions that significantly advance the state-of-the-art in Semantic Web of Things for Industry 4.0 including the use of Semantic Web technologies and techniques in Industry 4.0 solutions.


Author(s):  
Torsten Priebe

The goal of this chapter is to show how Semantic Web technologies can help build integrative enterprise knowledge portals. Three main areas are identified: content management and metadata, global searching, and the integration of external content and applications. For these three areas the state-of-the-art as well as current research results are discussed. In particular, a metadata-based information retrieval and a context-based port let integration approach are presented. These have been implemented in a research prototype which is introduced in the Internet session at the end of the chapter.


2021 ◽  
Author(s):  
Gillian Byrne ◽  
Lisa Goddard

Semantic Web technologies have immense potential to transform the Internet into a distributed reasoning machine that will not only execute extremely precise searches, but will also have the ability to analyze the data it finds to create new knowledge. This paper examines the state of Semantic Web (also known as Linked Data) tools and infrastructure to determine whether semantic technologies are sufficiently mature for non–expert use, and to identify some of the obstacles to global Linked Data implementation.


Author(s):  
Ronald Denaux ◽  
Martino Mensio ◽  
Jose Manuel Gomez-Perez ◽  
Harith Alani

This paper summarises work where we combined semantic web technologies with deep learning systems to obtain state-of-the art explainable misinformation detection. We proposed a conceptual and computational model to describe a wide range of misinformation detection systems based around the concepts of credibility and reviews. We described how Credibility Reviews (CRs) can be used to build networks of distributed bots that collaborate for misinformation detection which we evaluated by building a prototype based on publicly available datasets and deep learning models.


2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Ana Roxin ◽  
Wahabou Abdou ◽  
William Derigent

AbstractThis paper presents contributions of the ANR McBIM (Communicating Material for BIM) project regarding Digital Building Twins, specifically how Semantic Web technologies allow providing explainable decision-support. Following an introduction stating our understanding of a Digital Building Twin (DBT), namely a lively representation of a buildings' status and environment, we identify five main research domains following the study of main research issues related to DBT. We then present the state-of-the-art and existing standards for digitizing the construction process, Semantic Web technologies, and wireless sensor networks. We further position the main contributions made so far in the ANR McBIM project's context according to this analysis, e.g., sensor placement in the communicating material and explainable decision-support.


2021 ◽  
Author(s):  
Gillian Byrne ◽  
Lisa Goddard

Semantic Web technologies have immense potential to transform the Internet into a distributed reasoning machine that will not only execute extremely precise searches, but will also have the ability to analyze the data it finds to create new knowledge. This paper examines the state of Semantic Web (also known as Linked Data) tools and infrastructure to determine whether semantic technologies are sufficiently mature for non–expert use, and to identify some of the obstacles to global Linked Data implementation.


Author(s):  
Vassileios Tsetsos ◽  
Christos Anagnostopoulos ◽  
Stathes Hadjiefthymiades

In this article, we describe issues related to the development of intelligent and human-centered LBS for indoor environments. We focus on the navigation service. Navigation is probably the most challenging LBS since it involves relatively complex algorithms and many cognitive processes (e.g., combining known paths for reaching unknown destinations, minimizing path length). With the proposed system, we try to incorporate intelligence to navigation services by enriching them with the semantics of users and navigation spaces. Such semantic information is represented and reasoned using state-of-the-art semantic Web technologies (Berners-Lee, Hendler, & Lassila, 2001).


Author(s):  
RAÚL GARCÍA-CASTRO ◽  
ASUNCIÓN GÓMEZ-PÉREZ

Interoperability among different development tools is not a straightforward task since ontology editors rely on specific internal knowledge models which are translated into common formats such as RDF(S). This paper addresses the urgent need for interoperability by providing an exhaustive set of benchmark suites for evaluating RDF(S) import, export and interoperability. It also demonstrates, in an extensive field study, the state-of-the-art of interoperability among six Semantic Web tools. From this field study we have compiled a comprehensive set of practices that may serve as recommendations for Semantic Web tool developers and ontology engineers.


Informatica ◽  
2015 ◽  
Vol 26 (2) ◽  
pp. 221-240 ◽  
Author(s):  
Valentina Dagienė ◽  
Daina Gudonienė ◽  
Renata Burbaitė

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