This HTML5 document contains 46 embedded RDF statements represented using HTML+Microdata notation.

The embedded RDF content will be recognized by any processor of HTML5 Microdata.

Namespace Prefixes

PrefixIRI
n4http://linked.opendata.cz/ontology/domain/vavai/riv/typAkce/
dctermshttp://purl.org/dc/terms/
n23http://localhost/temp/predkladatel/
n17http://purl.org/net/nknouf/ns/bibtex#
n14http://linked.opendata.cz/resource/domain/vavai/projekt/
n11http://linked.opendata.cz/resource/domain/vavai/riv/tvurce/
n18http://linked.opendata.cz/resource/domain/vavai/subjekt/
n13http://linked.opendata.cz/ontology/domain/vavai/
n21https://schema.org/
shttp://schema.org/
skoshttp://www.w3.org/2004/02/skos/core#
n3http://linked.opendata.cz/ontology/domain/vavai/riv/
n9http://bibframe.org/vocab/
n2http://linked.opendata.cz/resource/domain/vavai/vysledek/
rdfhttp://www.w3.org/1999/02/22-rdf-syntax-ns#
n6http://linked.opendata.cz/ontology/domain/vavai/riv/klicoveSlovo/
n7http://linked.opendata.cz/resource/domain/vavai/vysledek/RIV%2F61989592%3A15310%2F13%3A33145347%21RIV14-MSM-15310___/
n8http://linked.opendata.cz/ontology/domain/vavai/riv/duvernostUdaju/
xsdhhttp://www.w3.org/2001/XMLSchema#
n22http://linked.opendata.cz/ontology/domain/vavai/riv/aktivita/
n19http://linked.opendata.cz/ontology/domain/vavai/riv/jazykVysledku/
n20http://linked.opendata.cz/ontology/domain/vavai/riv/druhVysledku/
n16http://linked.opendata.cz/ontology/domain/vavai/riv/obor/
n15http://reference.data.gov.uk/id/gregorian-year/

Statements

Subject Item
n2:RIV%2F61989592%3A15310%2F13%3A33145347%21RIV14-MSM-15310___
rdf:type
n13:Vysledek skos:Concept
dcterms:description
The term of data quality should be used with caution because the concept of uncertainty and quality of spatial data are not synonymous, even though in many cases they are remarkably close to each other. They have highly similar characteristics and solve similar domains. In many cases, the quality and uncertainty are confused. Uncertainty in this sense is considered to be a characteristic that allows us to assess the quality of the data and how uncertainty affects the quality of spatial data. The basic difference is that the uncertainty can be introduced at any stage of the production of maps and GIS analyses (observation, conceptual modelling, measurement, analysis, etc.) and as such is not only related to the quality of spatial data themselves, but to the entire process. Sometimes we can see examples in the geoinformatics and geomatics when the pursuit of perfectly accurate and precision data are achieved, but perfect or near-perfect representation are the exception rather than the rule. Much common is the situation when is practically impossible to capture every single aspect due to intricate details of the world. In addition, different individuals perceive the world in different ways, and it is difficult to identify one valid and universally accepted theory. Visualisation is a strong tool to showing results by representation in a better way than text description of the quality of data. In the other hand, unsophisticated visualisation is insufficient due to the complexity of the spatial quality data problem. Based on this statement it is necessary to visualise also information about data quality and uncertainty. This paper describes different perspectives of uncertainty and spatial data quality visualisation in context of modelling the spatial distributions of ecotones. The term of data quality should be used with caution because the concept of uncertainty and quality of spatial data are not synonymous, even though in many cases they are remarkably close to each other. They have highly similar characteristics and solve similar domains. In many cases, the quality and uncertainty are confused. Uncertainty in this sense is considered to be a characteristic that allows us to assess the quality of the data and how uncertainty affects the quality of spatial data. The basic difference is that the uncertainty can be introduced at any stage of the production of maps and GIS analyses (observation, conceptual modelling, measurement, analysis, etc.) and as such is not only related to the quality of spatial data themselves, but to the entire process. Sometimes we can see examples in the geoinformatics and geomatics when the pursuit of perfectly accurate and precision data are achieved, but perfect or near-perfect representation are the exception rather than the rule. Much common is the situation when is practically impossible to capture every single aspect due to intricate details of the world. In addition, different individuals perceive the world in different ways, and it is difficult to identify one valid and universally accepted theory. Visualisation is a strong tool to showing results by representation in a better way than text description of the quality of data. In the other hand, unsophisticated visualisation is insufficient due to the complexity of the spatial quality data problem. Based on this statement it is necessary to visualise also information about data quality and uncertainty. This paper describes different perspectives of uncertainty and spatial data quality visualisation in context of modelling the spatial distributions of ecotones.
dcterms:title
Uncertainty vs. spatial data quality visualisations: a case study on ecotones Uncertainty vs. spatial data quality visualisations: a case study on ecotones
skos:prefLabel
Uncertainty vs. spatial data quality visualisations: a case study on ecotones Uncertainty vs. spatial data quality visualisations: a case study on ecotones
skos:notation
RIV/61989592:15310/13:33145347!RIV14-MSM-15310___
n13:predkladatel
n18:orjk%3A15310
n3:aktivita
n22:P
n3:aktivity
P(EE2.3.20.0166)
n3:dodaniDat
n15:2014
n3:domaciTvurceVysledku
n11:6130348 n11:6581897 n11:4581393
n3:druhVysledku
n20:D
n3:duvernostUdaju
n8:S
n3:entitaPredkladatele
n7:predkladatel
n3:idSjednocenehoVysledku
112558
n3:idVysledku
RIV/61989592:15310/13:33145347
n3:jazykVysledku
n19:eng
n3:klicovaSlova
uncertainty, ecotones, spatial data quality
n3:klicoveSlovo
n6:uncertainty n6:spatial%20data%20quality n6:ecotones
n3:kontrolniKodProRIV
[0274101DB60E]
n3:mistoKonaniAkce
Albena, Bulgaria
n3:mistoVydani
Sofia
n3:nazevZdroje
SGEM2013 Conference Proceedings
n3:obor
n16:DE
n3:pocetDomacichTvurcuVysledku
3
n3:pocetTvurcuVysledku
3
n3:projekt
n14:EE2.3.20.0166
n3:rokUplatneniVysledku
n15:2013
n3:tvurceVysledku
Pechanec, Vilém Kilianová, Helena Brus, Jan
n3:typAkce
n4:WRD
n3:zahajeniAkce
2013-06-16+02:00
s:issn
1314-2704
s:numberOfPages
8
n9:doi
10.5593/SGEM2013/BB2.V1/S11.052
n17:hasPublisher
STEF92 Technology Ltd.
n21:isbn
978-954-91818-9-0
n23:organizacniJednotka
15310