K. Andrews, Thomas Traunmüller, Thomas Wolkinger, Robert Gutounig, Julian Ausserhofer
{"title":"Building an open data visualisation web app using a data server: the Styrian diversity visualisation project","authors":"K. Andrews, Thomas Traunmüller, Thomas Wolkinger, Robert Gutounig, Julian Ausserhofer","doi":"10.1145/2809563.2809596","DOIUrl":null,"url":null,"abstract":"Statistical open data is usually provided only in the form of spreadsheets or CSV files, which can sometimes be very large. The writer of an open data app is confronted with two choices: restrict themselves to managable bite-sized chunks of data, which can be consumed (read, parsed, and held in memory) in one go, or install and maintain their own data server which the app can query on demand. The Styrian Diversity Visualisation project was conceived to visualise the diversity of inhabitants of the Austrian Province of Styria (Land Steiermark) using open data served from a data server (triple store). The corresponding web app queries the data server at run rime with a SPARQL query 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. The data server is an instance of a Virtuoso Open Source server. The web app (client) is written in HTML5 and uses the leafletjs JavaScript library to provide mobile-friendly interactive maps. The user interface was designed as a set of three stories, each guiding users through a scenario with accompanying interactive visualisations based on corresponding open data sets.","PeriodicalId":20526,"journal":{"name":"Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business","volume":"36 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2015-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2809563.2809596","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Statistical open data is usually provided only in the form of spreadsheets or CSV files, which can sometimes be very large. The writer of an open data app is confronted with two choices: restrict themselves to managable bite-sized chunks of data, which can be consumed (read, parsed, and held in memory) in one go, or install and maintain their own data server which the app can query on demand. The Styrian Diversity Visualisation project was conceived to visualise the diversity of inhabitants of the Austrian Province of Styria (Land Steiermark) using open data served from a data server (triple store). The corresponding web app queries the data server at run rime with a SPARQL query 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. The data server is an instance of a Virtuoso Open Source server. The web app (client) is written in HTML5 and uses the leafletjs JavaScript library to provide mobile-friendly interactive maps. The user interface was designed as a set of three stories, each guiding users through a scenario with accompanying interactive visualisations based on corresponding open data sets.