scholarly journals Special Issue on the Curative Power of Medical Data

Data ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 85 ◽  
Author(s):  
Daniela Gîfu ◽  
Diana Trandabăț ◽  
Kevin Cohen ◽  
Jingbo Xia
Keyword(s):  
Language Processing ◽  
Community Involvement ◽  
Clinical Information ◽  
Medical Data ◽  
Biomedical Data ◽  
Special Issue ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Wide Range ◽  
Language Technologies

With the massive amounts of medical data made available online, language technologies have proven to be indispensable in processing biomedical and molecular biology literature, health data or patient records. With huge amount of reports, evaluating their impact has long ceased to be a trivial task. Linking the contents of these documents to each other, as well as to specialized ontologies, could enable access to and the discovery of structured clinical information and could foster a major leap in natural language processing and in health research. The aim of this Special Issue, “Curative Power of Medical Data” in Data, is to gather innovative approaches for the exploitation of biomedical data using semantic web technologies and linked data by developing a community involvement in biomedical research. This Special Issue contains four surveys, which include a wide range of topics, from the analysis of biomedical articles writing style, to automatically generating tests from medical references, constructing a Gold standard biomedical corpus or the visualization of biomedical data.

SEMCL

2010 ◽  
Vol 1 (3) ◽  
pp. 1-19 ◽  
Author(s):  
Weisen Guo ◽  
Steven B. Kraines
Keyword(s):  
Semantic Web ◽  
Natural Language ◽  
Knowledge Sharing ◽  
Language Processing ◽  
Global Knowledge ◽  
Semantic Web Technologies ◽  
Natural Languages ◽  
Web Technologies ◽  
Language Knowledge ◽  
Cross Language

To promote global knowledge sharing, one should solve the problem that knowledge representation in diverse natural languages restricts knowledge sharing effectively. Traditional knowledge sharing models are based on natural language processing (NLP) technologies. The ambiguity of natural language is a problem for NLP; however, semantic web technologies can circumvent the problem by enabling human authors to specify meaning in a computer-interpretable form. In this paper, the authors propose a cross-language semantic model (SEMCL) for knowledge sharing, which uses semantic web technologies to provide a potential solution to the problem of ambiguity. Also, this model can match knowledge descriptions in diverse languages. First, the methods used to support searches at the semantic predicate level are given, and the authors present a cross-language approach. Finally, an implementation of the model for the general engineering domain is discussed, and a scenario describing how the model implementation handles semantic cross-language knowledge sharing is given.

Semantic Web of Things for Industry 4.0

Semantic Web ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 885-886
Author(s):  
Dhavalkumar Thakker ◽  
Pankesh Patel ◽  
Muhammad Intizar Ali ◽  
Tejal Shah
Keyword(s):  
Semantic Web ◽  
Industry 4.0 ◽  
State Of The Art ◽  
The State ◽  
Special Issue ◽  
Semantic Web Technologies ◽  
Web Of Things ◽  
Web Technologies

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.

Applications, Methodologies, and Technologies for Linked Open Data

2020 ◽  
Vol 16 (3) ◽  
pp. 53-69
Author(s):  
Cecilia Avila-Garzon
Keyword(s):  
Semantic Web ◽  
Open Data ◽  
Linked Open Data ◽  
Business Culture ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Wide Range ◽  
Research And Education ◽  
User Friendly ◽  
Culture Education

Advances in semantic web technologies have rocketed the volume of linked data published on the web. In this regard, linked open data (LOD) has long been a topic of great interest in a wide range of fields (e.g. open government, business, culture, education, etc.). This article reports the results of a systematic literature review on LOD. 250 articles were reviewed for providing a general overview of the current applications, technologies, and methodologies for LOD. The main findings include: i) most of the studies conducted so far focus on the use of semantic web technologies and tools applied to contexts such as biology, social sciences, libraries, research, and education; ii) there is a lack of research with regard to a standardized methodology for managing LOD; and iii) a plenty of tools can be used for managing LOD, but most of them lack of user-friendly interfaces for querying datasets.

Applying Semantic Web Technologies to Car Repairs

2011 ◽  
pp. 924-942
Author(s):  
Martin Bryan ◽  
Jay Cousins
Keyword(s):  
Semantic Web ◽  
Single Point ◽  
Online Resources ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
European Single Market ◽  
Wide Range ◽  
Shared Language ◽  
Information Sets ◽  
Multiple Languages

Vehicle repair organizations, especially those involved in providing roadside assistance, have to be able to handle a wide range of vehicles produced by different manufacturers. Each manufacturer has its own vocabulary for describing components, faults, symptoms, etc, which is maintained in multiple languages. To search online resources to find repair information on vehicles anywhere within the European Single Market, the vocabularies used to describe different makes and models of vehicles need to be integrated. The European Commission MYCAREVENT research project brought together European vehicle manufacturers, vehicle repair organisations, diagnostic tool manufacturers and IT specialists, including Semantic Web technologists, to study how to link together the wide range of information sets they use to identify faults and repair vehicles. MYCAREVENT has shown that information sets can be integrated and accessed through a service portal by using an integrated vocabulary. The integrated vocabulary provides a ‘shared language’ for the project, a reference terminology to which the disparate terminologies of organisations participating in the project can be mapped. This lingua franca facilitates a single point of access to disparate sets of information.

scholarly journals Editorial: Special issue on Semantic Web for Cultural Heritage

Semantic Web ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 163-167
Author(s):  
Antonis Bikakis ◽  
Eero Hyvönen ◽  
Stéphane Jean ◽  
Béatrice Markhoff ◽  
Alessandro Mosca
Keyword(s):  
Semantic Web ◽  
Cultural Heritage ◽  
Linked Data ◽  
Wide Spectrum ◽  
Special Issue ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Editorial Special Issue ◽  
Major Application ◽  
Application Fields

Cultural Heritage and Digital Humanities have become major application fields of Linked Data and Semantic Web technologies. This editorial introduces the special issue of the Semantic Web (SWJ) journal on Semantic Web for Cultural Heritage. In total 30 submissions for the call of papers were received, of which 11 were selected for publication. The papers cover a wide spectrum of modelled topics related to language, reading and writing, narratives, historical events and cultural artefacts, while describing reusable methodologies and tools for cultural data management. This issue indicates and demonstrates the high potential of Semantic Web technologies for applications in the Cultural Heritage domain.

scholarly journals BEE : a web service for biomedical entity exploration

2020 ◽  
Author(s):  
Jin-uk Jung ◽  
Jin-Muk Lim ◽  
Hyunwhan Joe ◽  
Hong-Gee Kim
Keyword(s):  
Query Language ◽  
Drug Repositioning ◽  
Query Languages ◽  
Biomedical Data ◽  
Semantic Web Technologies ◽  
Human Phenotype ◽  
Web Technologies ◽  
Efficient Management ◽  
Life Phenomena ◽  
Relationship Of

Recently there has been a trend in bioinformatics to produce and manage large quantities of data to better explain complex life phenomena through relationship and interactions among biomedical entities. This increase in data leads to a need for more efficient management and searching capabilities. As a result, Semantic Web technologies have been applied to biomedical data. To use these technologies, users have to learn a query language such as SPARQL in order to ask complex queries such as ‘What are the drugs associated with the disease breast carcinoma and Osteoporosis but not the gene ESR1’. BEE was developed to overcome the limitations and difficulties of learning such query languages. Our proposed system provides an intuitive and effective query interface based on natural language. Our system is a heterogeneous biomedical entity query system based on pathway, drug, microRNA, disease and gene datasets from DGIdb, Tarbase, Human Phenotype Ontology and Reactome, Gene Ontology, KEGG gene set of MSigDB. User queries can be joined with union, intersection and negation operators. The system also allows for selected results to be saved and later combined with newly created queries. To the best of our knowledge, BEE is the first system that supports condition search based on the relationship of heterogeneous biomedical entities and is expected to be used in various fields of bioinformatics such as in drug repositioning candidate selection as well as simple knowledge search.

scholarly journals Weaving a Semantic Web of Credibility Reviews for Explainable Misinformation Detection (Extended Abstract)

2021 ◽  
Author(s):  
Ronald Denaux ◽  
Martino Mensio ◽  
Jose Manuel Gomez-Perez ◽  
Harith Alani
Keyword(s):  
Deep Learning ◽  
Semantic Web ◽  
Computational Model ◽  
State Of The Art ◽  
Learning Systems ◽  
Learning Models ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Detection Systems ◽  
Wide Range

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.

Personalizing News Services Using Semantic Web Technologies

2011 ◽  
pp. 261-289 ◽  
Author(s):  
Flavius Frasincar ◽  
Jethro Borsje ◽  
Frederik Hogenboom
Keyword(s):  
Semantic Web ◽  
Knowledge Base ◽  
Language Processing ◽  
Word Sense Disambiguation ◽  
Word Sense ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Web Standards ◽  
Processing Techniques ◽  
News Services

This chapter describes Hermes, a framework for building personalized news services using Semantic Web technologies. The Hermes framework consists of four phases: classification, which categorizes news items with respect to a domain ontology, knowledge base updating, which keeps the knowledge base up-to-date based on the news information, news querying, which allows the user to search the news with concepts of interest, and results presentation, which shows the news results of the search process. Hermes is supported by a framework implementation, the Hermes News Portal, a tool that enables users to have a personalized access to news items. The Hermes framework and its associated implementation aim at advancing the state-of-the-art of semantic approaches for personalized news services by employing Semantic Web standards, exploiting and keeping up-to-date domain information, using advanced natural language processing techniques (e.g., ontology-based gazetteering, word sense disambiguation, etc.), and supporting time-based queries for expressing the desired news items.

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