Monitoring and Assessment of Environmental Impact by Persistent Organic Pollutants View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2010

AUTHORS

David Hutchison , Takeo Kanade , Josef Kittler , Jon M. Kleinberg , Friedemann Mattern , John C. Mitchell , Moni Naor , Oscar Nierstrasz , C. Pandu Rangan , Bernhard Steffen , Madhu Sudan , Demetri Terzopoulos , Doug Tygar , Moshe Y. Vardi , Gerhard Weikum , Jaroslav Urbánek , Karel Brabec , Ladislav Dušek , Ivan Holoubek , Jiří Hřebíček , Miroslav Kubásek

ABSTRACT

Institute RECETOX coordinates the “Central and Eastern European Centre for Persistent Organic Pollutants (POPs)” of Stockholm Convention (SC) environmental services: data monitoring, processing, storage and their management. This is supported by the Global Environmental Assessment and Information System (GENASIS) that utilizes data from national and international monitoring networks to obtain as-complete-as-possible set of information and a representative picture of environmental contamination by POPs. Institute of Biostatistics and Analyses (IBA) operates the System for Visualizing of Oncology Data (SVOD) for cancer epidemiology in the Czech Republic for data from Czech National Oncology Register. The synthesis of existing POPs pollution monitoring databases with epidemiological data is required for identifying some effects of POPs on human health. This task requires new, rich, data and services discovery capabilities within the bodies of knowledge available, which are discussed in the paper. IBA and RECETOX anthropogenic impact studies requiring data discovery from a multitude of monitoring networks and resources. The FP7 project “TaToo - Tagging Tool based on a Semantic Discovery Framework” are setting up a semantic web solution to close the discovery gap that prevents a full and easy access to information resources on the web. The use of TaToo tools together with GENASIS and SVOD is presented for the discovery of anthropogenic impact in several examples. More... »

PAGES

483-488

Book

TITLE

Artificial Neural Networks – ICANN 2010

ISBN

978-3-642-15824-7
978-3-642-15825-4

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-15825-4_65

DOI

http://dx.doi.org/10.1007/978-3-642-15825-4_65

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1008227167


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