The Onto-CropBase – A Semantic Web Application for Querying Crops Linked-Data

2016 ◽  
pp. 384-399
Author(s):  
Abba Lawan ◽  
Abdur Rakib ◽  
Natasha Alechina ◽  
Asha Karunaratne
Keyword(s):  
Semantic Web ◽  
Web Application ◽  
Linked Data

scholarly journals Visualization of typed links in Linked Data

2017 ◽  
Vol 70 (2) ◽  
pp. 179-199 ◽  
Author(s):  
Georg Neubauer
Keyword(s):  
World Wide Web ◽  
Semantic Web ◽  
Information Visualization ◽  
Web Application ◽  
Linked Data ◽  
World Wide ◽  
Processing Data ◽  
The World ◽  
Web Of Data ◽  
Practical Guidelines

The main subject of the work is the visualization of typed links in Linked Data. The academic subjects relevant to the paper in general are the Semantic Web, the Web of Data and information visualization. The Semantic Web, invented by Tim Berners-Lee in 2001, was announced as an extension to the World Wide Web (Web 2.0). The actual area of investigation concerns the connectivity of information on the World Wide Web. To be able to explore such interconnections, visualizations are critical requirements as well as a major part of processing data in themselves. In the context of the Semantic Web, representation of information interrelations can be achieved using graphs. The aim of the article is to primarily describe the arrangement of Linked Data visualization concepts by establishing their principles in a theoretical approach. Putting design restrictions into context leads to practical guidelines. By describing the creation of two alternative visualizations of a commonly used web application representing Linked Data as network visualization, their compatibility was tested. The application-oriented part treats the design phase, its results, and future requirements of the project that can be derived from this test.

scholarly journals Mapeamento de Problemas de Qualidade no Linked Data

2015 ◽  
Vol 1 (1) ◽  
pp. 38
Author(s):  
Jessica Oliveira De Souza ◽  
Jose Eduardo Santarem Segundo
Keyword(s):  
Semantic Web ◽  
User Experience ◽  
Web Application ◽  
Linked Data ◽  
Data Sets ◽  
Quality Of Data ◽  
Related Quality ◽  
Primary Means ◽  
Basic Semantic

Since the Semantic Web was created in order to improve the current web user experience, the Linked Data is the primary means in which semantic web application is theoretically full, respecting appropriate criteria and requirements. Therefore, the quality of data and information stored on the linked data sets is essential to meet the basic semantic web objectives. Hence, this article aims to describe and present specific dimensions and their related quality issues.

scholarly journals Making Linked Data accessible for One Health Surveillance with the "One Health Linked Data Toolbox"

2021 ◽  
Vol 4 ◽  
Author(s):  
Taras Günther ◽  
Matthias Filter ◽  
Fernanda Dórea
Keyword(s):  
Semantic Web ◽  
Web Application ◽  
Linked Data ◽  
Data Exchange ◽  
One Health ◽  
Health Surveillance ◽  
Knowledge Model ◽  
Data Interoperability ◽  
The One ◽  
The Web

In times of emerging diseases, data sharing and data integration are of particular relevance for One Health Surveillance (OHS) and decision support. Furthermore, there is an increasing demand to provide governmental data in compliance to the FAIR (Findable, Accessible, Interoperable, Reusable) data principles. Semantic web technologies are key facilitators for providing data interoperability, as they allow explicit annotation of data with their meaning, enabling reuse without loss of the data collection context. Among these, we highlight ontologies as a tool for modeling knowledge in a field, which simplify the interpretation and mapping of datasets in a computer readable medium; and the Resource Description Format (RDF), which allows data to be shared among human and computer agents following this knowledge model. Despite their potential for enabling cross-sectoral interoperability and data linkage, the use and application of these technologies is often hindered by their complexity and the lack of easy-to-use software applications. To overcome these challenges the OHEJP Project ORION developed the Health Surveillance Ontology (HSO). This knowledge model forms a foundation for semantic interoperability in the domain of One Health Surveillance. It provides a solution to add data from the target sectors (public health, animal health and food safety) in compliance with the FAIR principles of findability, accessibility, interoperability, and reusability, supporting interdisciplinary data exchange and usage. To provide use cases and facilitate the accessibility to HSO, we developed the One Health Linked Data Toolbox (OHLDT), which consists of three new and custom-developed web applications with specific functionalities. The first web application allows users to convert surveillance data available in Excel files online into HSO-RDF and vice versa. The web application demonstrates that data provided in well-established data formats can be automatically translated in the linked data format HSO-RDF. The second application is a demonstrator of the usage of HSO-RDF in a HSO triplestore database. In the user interface of this application, the user can select HSO concepts based on which to search and filter among surveillance datasets stored in a HSO triplestore database. The service then provides automatically generated dashboards based on the context of the data. The third web application demonstrates the use of data interoperability in the OHS context by using HSO-RDF to annotate meta-data, and in this way link datasets across sectors. The web application provides a dashboard to compare public data on zoonosis surveillance provided by EFSA and ECDC. The first solution enables linked data production, while the second and third provide examples of linked data consumption, and their value in enabling data interoperability across sectors. All described solutions are based on the open-source software KNIME and are deployed as web service via a KNIME Server hosted at the German Federal Institute for Risk Assessment. The semantic web extension of KNIME, which is based on the Apache Jena Framework, allowed a rapid an easy development within the project. The underlying open source KNIME workflows are freely available and can be easily customized by interested end users. With our applications, we demonstrate that the use of linked data has a great potential strengthening the use of FAIR data in OHS and interdisciplinary data exchange.

scholarly journals MMoOn Core – the Multilingual Morpheme Ontology

Semantic Web ◽  
2020 ◽  
pp. 1-29
Author(s):  
Bettina Klimek ◽  
Markus Ackermann ◽  
Martin Brümmer ◽  
Sebastian Hellmann
Keyword(s):  
Semantic Web ◽  
Linked Data ◽  
Semantic Model ◽  
Lexical Resources ◽  
Domain Specific ◽  
Word Forms ◽  
Language Data ◽  
Core Ontology ◽  
Machine Readable ◽  
Rapid Emergence

In the last years a rapid emergence of lexical resources has evolved in the Semantic Web. Whereas most of the linguistic information is already machine-readable, we found that morphological information is mostly absent or only contained in semi-structured strings. An integration of morphemic data has not yet been undertaken due to the lack of existing domain-specific ontologies and explicit morphemic data. In this paper, we present the Multilingual Morpheme Ontology called MMoOn Core which can be regarded as the first comprehensive ontology for the linguistic domain of morphological language data. It will be described how crucial concepts like morphs, morphemes, word forms and meanings are represented and interrelated and how language-specific morpheme inventories can be created as a new possibility of morphological datasets. The aim of the MMoOn Core ontology is to serve as a shared semantic model for linguists and NLP researchers alike to enable the creation, conversion, exchange, reuse and enrichment of morphological language data across different data-dependent language sciences. Therefore, various use cases are illustrated to draw attention to the cross-disciplinary potential which can be realized with the MMoOn Core ontology in the context of the existing Linguistic Linked Data research landscape.

scholarly journals Use of Linked Data principles for semantic management of scanned documents

2016 ◽  
Vol 28 (2) ◽  
pp. 241-251 ◽  
Author(s):  
Luciane Lena Pessanha Monteiro ◽  
Mark Douglas de Azevedo Jacyntho
Keyword(s):  
Decision Making ◽  
Knowledge Base ◽  
Web Application ◽  
Linked Data ◽  
World Wide ◽  
Decision Making Process ◽  
Whole Process ◽  
The World ◽  
Scanned Documents ◽  
The Web

The study addresses the use of the Semantic Web and Linked Data principles proposed by the World Wide Web Consortium for the development of Web application for semantic management of scanned documents. The main goal is to record scanned documents describing them in a way the machine is able to understand and process them, filtering content and assisting us in searching for such documents when a decision-making process is in course. To this end, machine-understandable metadata, created through the use of reference Linked Data ontologies, are associated to documents, creating a knowledge base. To further enrich the process, (semi)automatic mashup of these metadata with data from the new Web of Linked Data is carried out, considerably increasing the scope of the knowledge base and enabling to extract new data related to the content of stored documents from the Web and combine them, without the user making any effort or perceiving the complexity of the whole process.

Advanced Semantic Web Services for Diet Therapy with Linked Data and Mediation Rules

2014 ◽  
pp. 146-156
Author(s):  
Yusuke Tagawa ◽  
Arata Tanaka ◽  
Yuya Minami ◽  
Daichi Namikawa ◽  
Michio Simomura ◽  
...  
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Linked Data ◽  
Diet Therapy ◽  
Semantic Web Services

scholarly journals Um método para publicação semântica Linked Data de bases de dados convencionais e um estudo de caso real de artigos acadêmicos

2020 ◽  
Vol 32 ◽  
Author(s):  
Adriano de Oliveira GONÇALVES ◽  
Mark Douglas de Azevedo JACYNTHO
Keyword(s):  
Semantic Web ◽  
Linked Data ◽  
De Se

Resumo Este trabalho propõe, por meio de uma metodologia de pesquisa quali-quantitativa, aplicada e experimental, um método para mapeamento e publicação sistemática de uma base relacional existente, segundo os princípios Linked Data, a partir de um estudo de caso de artigos acadêmicos da conferência interna Semana de Integração Acadêmica de uma universidade públicafederal brasileira. O método proposto é resultado de mapeamento do domínio de conhecimento estudado em ontologias Linked Data de referência (Schema.org, Friend of a Friend, Bibliographic Ontology, Semantic Web Conference Ontology, entre outras). O referido método foi aplicado ao banco de dados relacional da conferência, a fim de disponibilizá-lo em formato inteligível por máquinas na Web, estabelecendo-se ainda links semânticos com a famosa fonte de dados DBpedia, por meio de um processo de mashup automatizado. Os resultados obtidos com o método foram bastante satisfatórios, atingindo-se plenamente o objetivo de se publicar uma visão Linked Data sobre os dados relacionais, sem alterá-los. Espera-se, com este trabalho, fomentar a disponibilização de dados semânticos na Web, em consonância com os princípios Linked Data. Assim, contribui-se para a ampla divulgação de conhecimento, impulsionada pela capacidade que a Web Semântica provê às máquinas de interligar, compreender e descobrir informações.

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