Publication details

 

Conceptual Model Enhancing Accessibility of Data from Cancer–Related Environmental Risk Assessment Studies

Basic information
Original title:Conceptual Model Enhancing Accessibility of Data from Cancer–Related Environmental Risk Assessment Studies
Authors:Ladislav Dušek, Jiří Hřebíček, Miroslav Kubásek, Jiří Jarkovský, Jiří Kalina, Roman Baroš, Zdenka Bednářová, Jana Klánová, Ivan Holoubek
Further information
Citation:DUŠEK, Ladislav, Jiří HŘEBÍČEK, Miroslav KUBÁSEK, Jiří JARKOVSKÝ, Jiří KALINA, Roman BAROŠ, Zdenka BEDNÁŘOVÁ, Jana KLÁNOVÁ a Ivan HOLOUBEK. Conceptual Model Enhancing Accessibility of Data from Cancer–Related Environmental Risk Assessment Studies. In Jiří Hřebíček, Gerald Schimak, Ralf Denzer. 9th IFIP WG 5.11 International Symposium on Environmental Software Systems: Frameworks of eEnvironment, ISESS 2011. Heidelberg: Springer, 2011. s. 461-479, 19 s. ISBN 978-80-85763-60-7.Export BibTeX
@inproceedings{949246,
author = {Dušek, Ladislav and Hřebíček, Jiří and Kubásek, Miroslav and Jarkovský, Jiří and Kalina, Jiří and Baroš, Roman and Bednářová, Zdenka and Klánová, Jana and Holoubek, Ivan},
address = {Heidelberg},
booktitle = {9th IFIP WG 5.11 International Symposium on Environmental Software Systems: Frameworks of eEnvironment, ISESS 2011},
editor = {Jiří Hřebíček, Gerald Schimak, Ralf Denzer},
keywords = {cancer risk; data discovery; data model; Persistent organic pollutants},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Heidelberg},
isbn = {978-80-85763-60-7},
pages = {461-479},
publisher = {Springer},
title = {Conceptual Model Enhancing Accessibility of Data from Cancer–Related Environmental Risk Assessment Studies},
year = {2011}
}
Original language:English
Field:Informatics
Type:Article in Proceedings
Keywords:cancer risk; data discovery; data model; Persistent organic pollutants

This paper proposes conceptual model which can be used to facilitate the discovery, integration and analysis of environmental data in cancer-related risk studies. Persistent organic pollutants were chosen as a model because of their persistence, bioaccumulation potential and genotoxicity. Part dealing with cancer risk is primarily focused on population-based observations encompassing a wide range of epidemiologic studies, from local investigations to national cancer registries. The proposed model adopted multilayer hierarchy working with characteristics of given entities (POPs, cancer diseases as nomenclature classes) and couples "observation - measurement" as content defining classes. The proposal extends formally used taxonomy applying multidimensional set of descriptors including scores of measurement validity and precision. This solution has the potential to aid multidisciplinary data discovery and knowledge mining.