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Tagging Tool based on a Semantic Discovery Framewo.. (TATOO)
Tagging Tool based on a Semantic Discovery Framework
(TATOO)
Date du début: 1 janv. 2010,
Date de fin: 31 déc. 2012
PROJET
TERMINÉ
This proposal aims to set up a semantic web solution to close the discovery gap that prevents a full and easy access to environmental resources on the web. The proposal assumes the following: 1. It is meaningless to create yet another standard to facilitate access; we must exploit existing standards; 2. The burden of facilitating access to existing resources cannot be solely delegated to the owner. The user community must play a proactive role. 3. Existing environmental resources shall not require upgrades, re-deployment, re-implementation. The proposed solution must have a low cost and deliver a high impact.The core of the project will thus focus on the development of tools allowing third parties to easily discover environmental resources (data and/or services residing on different information nodes) on the web and to add valuable information in the form of semantic annotations to these resources, thus facilitating future usage and discovery, and kicking off a beneficial cycle of information enrichment.The proposed TaToo framework will be of a generic nature and will allow the integration of semantics, taking into account the challenges of different domain-ontologies in a multi-domain and multilingual context. TaToo provides three complex and extensive validation scenarios and therefore foresees skilled or expert users as the primary target user group.TaToo will encourage external validation of the usability of its framework and tools by scientific communities such as the International Environmental and Modelling Society (iEMSs), the International Federation of Information Processing (IFIP), and members of the Central and Eastern European Centre for Persistent Organic Pollutants (CEEPOPsCTR).TaToo will positively stimulate the European Economy because environmental resources will become more attractive by accumulating exploitable descriptions which are enhanced by expert users' information and linked with other knowledge domains.
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