scholarly journals Visualization of Graph Structured Data of Semantic Web in Life Sciences

2020 ◽  
Vol 40 (156) ◽  
pp. 19-24
Author(s):  
Toshiaki KATAYAMA
Keyword(s):  
Semantic Web ◽  
Life Sciences ◽  
Structured Data

scholarly journals Wikidata: A platform for data integration and dissemination for the life sciences and beyond

2015 ◽  
Author(s):  
Elvira Mitraka ◽  
Andra Waagmeester ◽  
Sebastian Burgstaller-Muehlbacher ◽  
Lynn M Schriml ◽  
Andrew I Su ◽  
...  
Keyword(s):  
Semantic Web ◽  
Data Integration ◽  
Semantic Network ◽  
Life Sciences ◽  
Structured Data ◽  
Data Resource ◽  
Semantic Data ◽  
The World ◽  
Data Commons

Wikidata is an open, Semantic Web-compatible database that anyone can edit. This ′data commons′ provides structured data for Wikipedia articles and other applications. Every article on Wikipedia has a hyperlink to an editable item in this database. This unique connection to the world′s largest community of volunteer knowledge editors could help make Wikidata a key hub within the greater Semantic Web. The life sciences, as ever, faces crucial challenges in disseminating and integrating knowledge. Our group is addressing these issues by populating Wikidata with the seeds of a foundational semantic network linking genes, drugs and diseases. Using this content, we are enhancing Wikipedia articles to both increase their quality and recruit human editors to expand and improve the underlying data. We encourage the community to join us as we collaboratively create what can become the most used and most central semantic data resource for the life sciences and beyond.

Editorial: Semantic Web for Life Sciences

2006 ◽  
Author(s):  
Michael Schroeder ◽  
Eric Neumann
Keyword(s):  
Semantic Web ◽  
Life Sciences

scholarly journals YeastHub: a semantic web use case for integrating data in the life sciences domain

2005 ◽  
Vol 21 (Suppl 1) ◽  
pp. i85-i96 ◽  
Author(s):  
K.-H. Cheung ◽  
K. Y. Yip ◽  
A. Smith ◽  
R. deKnikker ◽  
A. Masiar ◽  
...  
Keyword(s):  
Semantic Web ◽  
Life Sciences ◽  
Use Case ◽  
Web Use

scholarly journals SciNetS Search : Inference Search over an Integrated Life-sciences Database Based on the Semantic Web

2010 ◽  
Author(s):  
Tetsuro Toyoda ◽  
Norio Kobayashi ◽  
Manabu Ishii ◽  
Yuko Yoshida ◽  
Yuko Makita ◽  
...  
Keyword(s):  
Semantic Web ◽  
Life Sciences ◽  
Inference Search

Semantic web: golden era of information

2018 ◽  
Vol 7 (2.8) ◽  
pp. 436
Author(s):  
Prakhar Agarwal ◽  
Shivani Jain
Keyword(s):  
Semantic Web ◽  
Information Search ◽  
Review Paper ◽  
Development Project ◽  
Structured Data ◽  
Common Language ◽  
End User ◽  
Ontology Language ◽  
Shared Language ◽  
Definition Of

Semantic Web is the extension of existing web that allows well defined expressions for the meaning of information which can be understood by computers and people both. In this paper we are doing study on semantic and is our review paper. Semantic web is a recommended development project by W3C (World Wide Web Consortium) which focuses on the enhancing of information search by keeping the facts in structured form using eXtensible Mark-up Language (XML) and marked in such a way that it can be understand by the system. To make the development of semantic web promising, new international standard is developed for exchanging of ontologies called OWL Web Ontology language. In XML we just provide tag of the model and store data in the hierarchy without its meaning, that’s why the computer cannot be able to process the data but in Semantic Web user can provide with a definition so that the computer can better recognize its meaning and provide with the better displaying of information. A crux of semantic web is that it works on the definition of the ontologies. Ontologies are responsible for re-usability and sharing of information. Semantic Web provides with a shared language which has stored data in the non-ending linking of distinct databases which provides data related to the real world objects. RDF is a common language for semantic web and is responsible for the collection of data on web and assembles different database from diverse sources and SPARQL is there for linking of databases for unifying documents. Thus, semantic web is the well-structured data web that relates all the data that present on the web and understands them to provide the exact display requested by the end user.

scholarly journals Semantic Web technologies for the big data in life sciences

2014 ◽  
Vol 8 (4) ◽  
pp. 192-201 ◽  
Author(s):  
Hongyan Wu ◽  
Atsuko Yamaguchi
Keyword(s):  
Big Data ◽  
Semantic Web ◽  
Life Sciences ◽  
Semantic Web Technologies ◽  
Web Technologies

Management of SME's Semi Structured Data Using Semantic Technique

Web Services ◽  
2019 ◽  
pp. 1812-1835
Author(s):  
Saravjeet Singh ◽  
Jaiteg Singh
Keyword(s):  
Semantic Web ◽  
Data Management ◽  
Complex Form ◽  
Web Technology ◽  
Structured Data ◽  
Unstructured Data ◽  
Effective Solution ◽  
Semantic Web Technology ◽  
Semantic Data ◽  
To Come

Management of data for an organization is crucial task but when data goes to its complex form then it becomes multifaceted as well as vital. In today era most of the organizations generating semi structured or unstructured data that requires special techniques to handle and manage. With the needs to handle unstructured data, semantic web technology provides a way to come up with the effective solution. In this chapter Synthetic Semantic Data Management (SSDM) is explained that is based semantic web technique and will helps to manage data of small and Midsized Enterprise (SME). SSDM provide the procedure to handle, store, manages and retrieval of semi structured data.

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