GI Systems for public health with an ontology based approach


Autoria(s): Gür, Nurefşan
Contribuinte(s)

Sánchez, Laura Díaz

Kauppinen, Tomi

Painho, Marco

Data(s)

06/12/2012

06/12/2012

05/03/2012

Resumo

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Health is an indispensable attribute of human life. In modern age, utilizing technologies for health is one of the emergent concepts in several applied fields. Computer science, (geographic) information systems are some of the interdisciplinary fields which motivates this thesis. Inspiring idea of the study is originated from a rhetorical disease DbHd: Database Hugging Disorder, defined by Hans Rosling at World Bank Open Data speech in May 2010. The cure of this disease can be offered as linked open data, which contains ontologies for health science, diseases, genes, drugs, GEO species etc. LOD-Linked Open Data provides the systematic application of information by publishing and connecting structured data on the Web. In the context of this study we aimed to reduce boundaries between semantic web and geo web. For this reason a use case data is studied from Valencia CSISP- Research Center of Public Health in which the mortality rates for particular diseases are represented spatio-temporally. Use case data is divided into three conceptual domains (health, spatial, statistical), enhanced with semantic relations and descriptions by following Linked Data Principles. Finally in order to convey complex health-related information, we offer an infrastructure integrating geo web and semantic web. Based on the established outcome, user access methods are introduced and future researches/studies are outlined.

Identificador

http://hdl.handle.net/10362/8328

Idioma(s)

eng

Relação

Master of Science in Geospatial Technologies;TGEO0080

Direitos

openAccess

Palavras-Chave #Linked Open Data #Semantic Web #Health Statistics #Geographical Information Systems #Spatial #Health #Statistical Ontologies
Tipo

masterThesis