dc.contributor.author | Andrews, Keith | en_US |
dc.contributor.author | Traunmüller, Thomas | en_US |
dc.contributor.author | Wolkinger, Thomas | en_US |
dc.contributor.author | Goldgruber, Eva | en_US |
dc.contributor.author | Gutounig, Robert | en_US |
dc.contributor.author | Ausserhofer, Julian | en_US |
dc.contributor.editor | Tobias Isenberg and Filip Sadlo | en_US |
dc.date.accessioned | 2016-06-09T09:33:38Z | |
dc.date.available | 2016-06-09T09:33:38Z | |
dc.date.issued | 2016 | en_US |
dc.identifier.isbn | 978-3-03868-015-4 | en_US |
dc.identifier.issn | - | en_US |
dc.identifier.uri | http://dx.doi.org/10.2312/eurp.20161150 | en_US |
dc.identifier.uri | https://diglib.eg.org:443/handle/10 | |
dc.description.abstract | Statistical open data is usually provided only in the form of spreadsheets or CSV files. The developers of open data apps must either restrict themselves to managable bite-sized chunks of data, which can be consumed (read, parsed, and held in memory) in one go, or must install and maintain their own data server which the app can query on demand. The Styrian Diversity Visualisation (in German ''Steirische Vielfalt Visualisiert'' or SVV) project demonstrates the use of a dedicated data server (triple store) to host large amounts of statistical open data. The SVV web app queries the data server dynamically using SPARQL queries to obtain exactly the data required at that particular time, greatly simplifying its internal logic. There is no need to parse and store entire data sets in memory. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.subject | H.5.2 [Information Interfaces and Presentation] | en_US |
dc.subject | User Interfaces | en_US |
dc.subject | D.2.12 [Software Engineering] | en_US |
dc.subject | Interoperability | en_US |
dc.subject | Data Mapping | en_US |
dc.title | Styrian Diversity Visualisation: Visualising Statistical Open Data with a LeanWeb App and Data Server | en_US |
dc.description.seriesinformation | EuroVis 2016 - Posters | en_US |
dc.description.sectionheaders | Poster | en_US |
dc.identifier.doi | 10.2312/eurp.20161150 | en_US |
dc.identifier.pages | 93-95 | en_US |