Update: Hooray, we won the I-KNOW 2015 best demo award for our work. Congrats to Keith Andrews and Thomas Traunmüller who were the main drivers behind that paper.
Back in the summer of 2013 I drafted a concept for a visualization platform that would show the diversity of the Province Styria using open census data: Similar as in many news apps, users would interactively engage with the data visualization, find out more about their socio-economic situation in comparison to others, and thereby learn about the diversity of federal state.
The idea was then further developed by my colleagues Thomas Wolkinger and Keith Andrews. After a number of concept iterations, the Integration Department of the Government of Styria asked our Institute to develop such a platform in collaboration with Graz University of Technology. Thomas Traunmüller, Eva Goldgruber and Robert Gutounig came on board. While I was on educational leave, the four continued the work. Now it is almost finished and will go public soon. The launch will be accompanied with blog posts about diversity, published on our data blog.
In order to also scientifically disseminate our work, Keith wrote a demo paper for this year’s I-KNOW conference in Graz. I-KNOW is an important international conference in the field of knowledge management. The paper focuses on the challenges in the development process and the advantages of using linked open data over static data for such an application
Here is the 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 them- selves to managable bite-sized chunks of data, which can be con- sumed (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.
Andrews, K., Traunmüller, T., Wolkinger, T., Gutounig, R., & Ausserhofer, J. (2015). Building an Open Data Visualisation Web App using a Data Server: The Styrian Diversity Visualisation Project. Presented at the 15th International Conference on Knowledge Technologies and Data-Driven Business (i-KNOW 2015), Graz. http://doi.org/10.1145/1235
Last but not least I would like thank Heinz Wittenbrink, who brought us in contact with the Styrian government. Of great help was also the project NOLDE where we learned so much about linked open data.