scholarly journals Agronomic Linked Data (AgroLD): a Knowledge-based System to Enable Integrative Biology in Agronomy

2018 ◽  
Author(s):  
Aravind Venkatesan ◽  
Gildas Tagny ◽  
Nordine El Hassouni ◽  
Imene Chentli ◽  
Valentin Guignon ◽  
...  
Keyword(s):  
Semantic Web ◽  
Plant Disease Resistance ◽  
Linked Data ◽  
Explicit Knowledge ◽  
Heterogeneous Data ◽  
Plant Science ◽  
Research Approach ◽  
Knowledge Based System ◽  
Link Type ◽  
Knowledge Based

AbstractRecent advances in high-throughput technologies have resulted in a tremendous increase in the amount of omics data produced in plant science. This increase, in conjunction with the heterogeneity and variability of the data, presents a major challenge to adopt an integrative research approach. We are facing an urgent need to effectively integrate and assimilate complementary datasets to understand the biological system as a whole. The Semantic Web offers technologies for the integration of heterogeneous data and their transformation into explicit knowledge thanks to ontologies. We have developed the Agronomic Linked Data (AgroLD – www.agrold.org), a knowledge-based system relying on Semantic Web technologies and exploiting standard domain ontologies, to integrate data about plant species of high interest for the plant science community e.g., rice, wheat, arabidopsis. We present some integration results of the project, which initially focused on genomics, proteomics and phenomics. AgroLD is now an RDF (Resource Description Format) knowledge base of 100M triples created by annotating and integrating more than 50 datasets coming from 10 data sources –such as Gramene.org and TropGeneDB– with 10 ontologies –such as the Gene Ontology and Plant Trait Ontology. Our evaluation results show users appreciate the multiple query modes which support different use cases. AgroLD’s objective is to offer a domain specific knowledge platform to solve complex biological and agronomical questions related to the implication of genes/proteins in, for instances, plant disease resistance or high yield traits. We expect the resolution of these questions to facilitate the formulation of new scientific hypotheses to be validated with a knowledge-oriented approach.

Semantic Web, Ontology, and Linked Data

Web Services ◽  
2019 ◽  
pp. 127-148 ◽  
Author(s):  
Anindya Basu
Keyword(s):  
Semantic Web ◽  
Linked Data ◽  
Knowledge Organization ◽  
Human Being ◽  
Data Modelling ◽  
Amount Of Information ◽  
Knowledge Based ◽  
Enormous Amount ◽  
The Future

Enormous amount of information is being produced every day and get consumed according to the needs of human being. Semantic web and ontology represent information which are machine processable and understand the semantics present among the entities. Ontology can be represented as Knowledge Organization and data modelling tool. Librarians are designated as “Information Custodian” or “Knowledge Keepers”. Implication and application of concepts in LIS can play big role in shaping knowledge-based services and mining and inferring them in better way in future. Ontology and semantic web is the future of LIS as speculated by several professionals and experts. This chapter would delineate a basic overview of Semantic Web, Ontology and linked data.

Knowledge-based terminological e‑dictionaries

Terminology ◽  
2019 ◽  
Vol 25 (2) ◽  
pp. 259-290 ◽  
Author(s):  
Christophe Roche ◽  
Rute Costa ◽  
Sara Carvalho ◽  
Bruno Almeida
Keyword(s):  
Semantic Web ◽  
Linked Data ◽  
Theoretical Perspective ◽  
Specific Domain ◽  
Methodological Foundation ◽  
Knowledge Based ◽  
Different Types ◽  
The Creation ◽  
Islamic Archaeology ◽  
Concept Systems

Abstract The advent of the Semantic Web and of the Linked Data initiative have contributed to new perspectives and opportunities regarding terminology work. Among them are the double dimension approach and the theoretical perspective of ontoterminology anchored therein, which explore the synergies resulting from the systematic organisation of both term systems and concept systems. By doing so, they provide a theoretical and methodological foundation underlying the creation of knowledge-based terminological products that can support the conception and development of different types of e‑dictionaries. Within that scope, and based on examples pertaining to two different subject fields, namely endometriosis and Islamic archaeology, this article aims to propose a framework for the creation of a terminological e-dictionary, defined as a reference resource in a specific domain that gathers, structures and describes linguistic data in a systematic way in one, two or more languages, in order to define concepts that are denoted by terms.

Semantic Web, Ontology, and Linked Data

2017 ◽  
pp. 189-217
Author(s):  
Anindya Basu
Keyword(s):  
Semantic Web ◽  
Linked Data ◽  
Knowledge Organization ◽  
Human Being ◽  
Data Modelling ◽  
Amount Of Information ◽  
Knowledge Based ◽  
Enormous Amount ◽  
The Future

Enormous amount of information is being produced every day and get consumed according to the needs of human being. Semantic web and ontology represent information which are machine processable and understand the semantics present among the entities. Ontology can be represented as Knowledge Organization and data modelling tool. Librarians are designated as “Information Custodian” or “Knowledge Keepers”. Implication and application of concepts in LIS can play big role in shaping knowledge-based services and mining and inferring them in better way in future. Ontology and semantic web is the future of LIS as speculated by several professionals and experts. This chapter would delineate a basic overview of Semantic Web, Ontology and linked data.

State of the Art in Semantic Organizational Knowledge

2021 ◽  
pp. 1762-1773
Author(s):  
Mamadou Tadiou Kone
Keyword(s):  
Semantic Web ◽  
Tacit Knowledge ◽  
Knowledge Creation ◽  
Linked Data ◽  
Explicit Knowledge ◽  
State Of The Art ◽  
Organizational Knowledge ◽  
Cultural Knowledge ◽  
Types Of Knowledge ◽  
Embedded Knowledge

This chapter proposes a state-of-the-art survey on the emerging field of Semantic Organizational Knowledge. This concept refers to the technologies of the Semantic Web and Linked Data applied to the principles and procedures of organizational knowledge. Originally, organizational Knowledge is described as the ability of employees of an organization to exercise judgment based on the history and collective understanding of a particular context. Researchers have identified the existence of several types of knowledge in organized contexts including explicit knowledge, tacit knowledge, cultural knowledge, and embedded knowledge. Along these lines, a number of issues must be addressed in order to apply Semantic Web and Linked Data technologies. The main objective of this chapter is to demonstrate that there exists substantial research that supports the use of the Semantic Web or Linked Data technologies to effectively support all aspects of knowledge creation, sharing, distribution, and acquisition.

scholarly journals Agronomic Linked Data (AgroLD): A knowledge-based system to enable integrative biology in agronomy

PLoS ONE ◽  
2018 ◽  
Vol 13 (11) ◽  
pp. e0198270 ◽  
Author(s):  
Aravind Venkatesan ◽  
Gildas Tagny Ngompe ◽  
Nordine El Hassouni ◽  
Imene Chentli ◽  
Valentin Guignon ◽  
...  
Keyword(s):  
Linked Data ◽  
Integrative Biology ◽  
Knowledge Based System ◽  
Knowledge Based

scholarly journals SCALEUS-FD: A FAIR Data Tool for Biomedical Applications

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Arnaldo Pereira ◽  
Rui Pedro Lopes ◽  
José Luís Oliveira
Keyword(s):  
Semantic Web ◽  
Linked Data ◽  
Biomedical Applications ◽  
Semantic Annotation ◽  
Heterogeneous Data ◽  
Full Potential ◽  
Web Tool ◽  
Data Stewardship ◽  
Data Ecosystem ◽  
Rest Api

The Semantic Web and Linked Data concepts and technologies have empowered the scientific community with solutions to take full advantage of the increasingly available distributed and heterogeneous data in distinct silos. Additionally, FAIR Data principles established guidelines for data to be Findable, Accessible, Interoperable, and Reusable, and they are gaining traction in data stewardship. However, to explore their full potential, we must be able to transform legacy solutions smoothly into the FAIR Data ecosystem. In this paper, we introduce SCALEUS-FD, a FAIR Data extension of a legacy semantic web tool successfully used for data integration and semantic annotation and enrichment. The core functionalities of the solution follow the Semantic Web and Linked Data principles, offering a FAIR REST API for machine-to-machine operations. We applied a set of metrics to evaluate its “FAIRness” and created an application scenario in the rare diseases domain.

SPARSE: A symptom-based antipattern retrieval knowledge-based system using Semantic Web technologies

2011 ◽  
Vol 38 (6) ◽  
pp. 7633-7646 ◽  
Author(s):  
Dimitrios L. Settas ◽  
Georgios Meditskos ◽  
Ioannis G. Stamelos ◽  
Nick Bassiliades
Keyword(s):  
Semantic Web ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Knowledge Based System ◽  
Knowledge Based

Semantic Web, Ontology, and Linked Data

2018 ◽  
pp. 24-46 ◽  
Author(s):  
Anindya Basu
Keyword(s):  
Semantic Web ◽  
Linked Data ◽  
Knowledge Organization ◽  
Human Being ◽  
Data Modelling ◽  
Amount Of Information ◽  
Knowledge Based ◽  
Enormous Amount ◽  
The Future

Enormous amount of information is being produced every day and get consumed according to the needs of human being. Semantic web and ontology represent information which are machine processable and understand the semantics present among the entities. Ontology can be represented as Knowledge Organization and data modelling tool. Librarians are designated as “Information Custodian” or “Knowledge Keepers”. Implication and application of concepts in LIS can play big role in shaping knowledge-based services and mining and inferring them in better way in future. Ontology and semantic web is the future of LIS as speculated by several professionals and experts. This chapter would delineate a basic overview of Semantic Web, Ontology and linked data.

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