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

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.

2018 ◽  
Author(s):  
Aravind Venkatesan ◽  
Gildas Tagny ◽  
Nordine El Hassouni ◽  
Imene Chentli ◽  
Valentin Guignon ◽  
...  

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 ◽  
2020 ◽  
pp. 1-29
Author(s):  
Bettina Klimek ◽  
Markus Ackermann ◽  
Martin Brümmer ◽  
Sebastian Hellmann

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.


Author(s):  
Yusuke Tagawa ◽  
Arata Tanaka ◽  
Yuya Minami ◽  
Daichi Namikawa ◽  
Michio Simomura ◽  
...  

Author(s):  
Georg Neubauer

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.


Author(s):  
Andrew Iliadis ◽  
Wesley Stevens ◽  
Jean-Christophe Plantin ◽  
Amelia Acker ◽  
Huw Davies ◽  
...  

This panel focuses on the way that platforms have become key players in the representation of knowledge. Recently, there have been calls to combine infrastructure and platform-based frameworks to understand the nature of information exchange on the web through digital tools for knowledge sharing. The present panel builds and extends work on platform and infrastructure studies in what has been referred to as “knowledge as programmable object” (Plantin, et al., 2018), specifically focusing on how metadata and semantic information are shaped and exchanged in specific web contexts. As Bucher (2012; 2013) and Helmond (2015) show, data portability in the context of web platforms requires a certain level of semantic annotation. Semantic interoperability is the defining feature of so-called "Web 3.0"—traditionally referred to as the semantic web (Antoniou et al, 2012; Szeredi et al, 2014). Since its inception, the semantic web has privileged the status of metadata for providing the fine-grained levels of contextual expressivity needed for machine-readable web data, and can be found in products as diverse as Google's Knowledge Graph, online research repositories like Figshare, and other sources that engage in platformizing knowledge. The first paper in this panel examines the international Schema.org collaboration. The second paper investigates the epistemological implications when platforms organize data sharing. The third paper argues for the use of patents to inform research methodologies for understanding knowledge graphs. The fourth paper discusses private platforms’ extraction and collection of user metadata and the enclosure of data access.


2020 ◽  
Vol 32 ◽  
Author(s):  
Adriano de Oliveira GONÇALVES ◽  
Mark Douglas de Azevedo JACYNTHO
Keyword(s):  

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.


2017 ◽  
Vol 22 (1) ◽  
pp. 21-37 ◽  
Author(s):  
Matthew T. Mccarthy

The web of linked data, otherwise known as the semantic web, is a system in which information is structured and interlinked to provide meaningful content to artificial intelligence (AI) algorithms. As the complex interactions between digital personae and these algorithms mediate access to information, it becomes necessary to understand how these classification and knowledge systems are developed. What are the processes by which those systems come to represent the world, and how are the controversies that arise in their creation, overcome? As a global form, the semantic web is an assemblage of many interlinked classification and knowledge systems, which are themselves assemblages. Through the perspectives of global assemblage theory, critical code studies and practice theory, I analyse netnographic data of one such assemblage. Schema.org is but one component of the larger global assemblage of the semantic web, and as such is an emergent articulation of different knowledges, interests and networks of actors. This articulation comes together to tame the profusion of things, seeking stability in representation, but in the process, it faces and produces more instability. Furthermore, this production of instability contributes to the emergence of new assemblages that have similar aims.


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