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Using geovisual analytics in Google Earth to understand disease distribution: a case study of campylobacteriosis in the Czech Republic (2008-2012)
L. Marek, P. Tuček, V. Pászto,
Jazyk angličtina Země Anglie, Velká Británie
Typ dokumentu časopisecké články, práce podpořená grantem
NLK
BioMedCentral
od 2002-01-12
BioMedCentral Open Access
od 2002
Directory of Open Access Journals
od 2002
Free Medical Journals
od 2002
PubMed Central
od 2002
Europe PubMed Central
od 2002
ProQuest Central
od 2009-01-01
Open Access Digital Library
od 2002-01-01
Open Access Digital Library
od 2002-08-01
Open Access Digital Library
od 2002-01-01
Medline Complete (EBSCOhost)
od 2003-01-01
Health & Medicine (ProQuest)
od 2009-01-01
ROAD: Directory of Open Access Scholarly Resources
od 2002
Springer Nature OA/Free Journals
od 2002-12-01
PubMed
25628063
DOI
10.1186/1476-072x-14-7
Knihovny.cz E-zdroje
- MeSH
- časoprostorová analýza * MeSH
- dítě MeSH
- dospělí MeSH
- geografická kartografie * MeSH
- geografické informační systémy statistika a číselné údaje MeSH
- kampylobakterové infekce diagnóza epidemiologie MeSH
- kojenec MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladiství MeSH
- mladý dospělý MeSH
- novorozenec MeSH
- pochopení * MeSH
- předškolní dítě MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- Check Tag
- dítě MeSH
- dospělí MeSH
- kojenec MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladiství MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- novorozenec MeSH
- předškolní dítě MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Česká republika MeSH
BACKGROUND: Visual analytics aims to connect the processing power of information technologies and the user's ability of logical thinking and reasoning through the complex visual interaction. Moreover, the most of the data contain the spatial component. Therefore, the need for geovisual tools and methods arises. Either one can develop own system but the dissemination of findings and its usability might be problematic or the widespread and well-known platform can be utilized. The aim of this paper is to prove the applicability of Google Earth™ software as a tool for geovisual analytics that helps to understand the spatio-temporal patterns of the disease distribution. METHODS: We combined the complex joint spatio-temporal analysis with comprehensive visualisation. We analysed the spatio-temporal distribution of the campylobacteriosis in the Czech Republic between 2008 and 2012. We applied three main approaches in the study: (1) the geovisual analytics of the surveillance data that were visualised in the form of bubble chart; (2) the geovisual analytics of the disease's weekly incidence surfaces computed by spatio-temporal kriging and (3) the spatio-temporal scan statistics that was employed in order to identify high or low rates clusters of affected municipalities. The final data are stored in Keyhole Markup Language files and visualised in Google Earth™ in order to apply geovisual analytics. RESULTS: Using geovisual analytics we were able to display and retrieve information from complex dataset efficiently. Instead of searching for patterns in a series of static maps or using numerical statistics, we created the set of interactive visualisations in order to explore and communicate results of analyses to the wider audience. The results of the geovisual analytics identified periodical patterns in the behaviour of the disease as well as fourteen spatio-temporal clusters of increased relative risk. CONCLUSIONS: We prove that Google Earth™ software is a usable tool for the geovisual analysis of the disease distribution. Google Earth™ has many indisputable advantages (widespread, freely available, intuitive interface, space-time visualisation capabilities and animations, communication of results), nevertheless it is still needed to combine it with pre-processing tools that prepare the data into a form suitable for the geovisual analytics itself.
Citace poskytuje Crossref.org
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