English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper describes the increasing role of ontologies in the context of Grid computing for obtaining, comparing and analyzing distributed heterogeneous scientific data. In the communities of people committed to a common goal, the management of resources and services becomes very important. We chose the application domain of human disease research and control. A characteristic of the domain is that trusted databases exist but their schemas are often poorly or not documented. The network of biomedical databases forms a loose federation of autonomous, distributed, heterogeneous data repositories ripe for information integration. Grid services will provide a dynamic way to use resources in such a large distributed scientific environment while the use of ontology enables the system to carryout reasoning at 3 levels: a) available information in all Bio-Databases (Grid nodes) worldwide, b) reasoning about the retrievable information from each node, c) reasoning about the retrieved information and presenting it in a meaningful format for users. We adopted the ontology design methodology of DOGMA and developed Generic Human Disease Ontology (GenDO) that contains common general information regarding human diseases. The information is represented in 4 “dimensions”: (a) disease types, (b) causes (c) symptoms and (d) treatments. We illustrate how this GenDO helps to produce Specific Human Disease Ontologies (SpeDO) on request. We show how the combination of two different but complementary techniques, namely Grid computing and ontology, results in a dynamic and intelligent information system. The two approaches together, being complementary, enable the system as a whole.

Grid Services Complemented by Domain Ontology Supporting Biomedical Community