Posted on November 22nd, 2012 by Jamie Mahoney
Back in August, I wrote a blog post that mentioned a paper that I had submitted to The International Conference on Information Visualization Theory and Applications, titled ‘Data Visualisation and Visual Analytics Within the Decision Making Process’. I found out this week that my submission has been accepted as a short paper. It can be downloaded from the Lincoln Repository.
The (short) abstract is included below :
Large amounts of data are collected and stored within universities. This paper discusses the use of data visualisation and visual analytics as methods of making sense of the collected data, analysing it to assess the affects of historical institutional decisions and discusses the use of such techniques to aid decision making processes.
Posted on May 31st, 2012 by Jamie Mahoney
On the 29th and 30th of May I attended the dev8eD conference in Birmingham, which was organized for ” …developers, educational technologists and users working throughout education on the development of tools, widgets, apps and resources aimed at staff in education and enhancing the student learning experience.”
There was several organised sessions that were of direct relevance to the ON Course project, including sessions on XCRI-CAP and the XCRI-CAP Aggregator currently being developed.
One of the challenges at dev8eD was to make use of the data available through the XCRI-CAP Aggregator and present it in useful / meaningful / interesting ways; with some help from Dale Mckeown who also works the University of Lincoln, I created a mashup of data from multiple sources to make a rudimentary course search engine.
The mashup uses data from the course aggregator (currently searching only by keywords) with geo-location data, university league table data and pub location data. The course finder also links to local crime data for institutions and ‘cost of living’ data. These latter two data sources were used to show how external data sets can be used to enrich the searching experience, providing further context for the wider surroundings and environment of universities.
When more XCRI feeds are added to the aggregator, the quality and quantity of data available through the aggregator’s API will obviously increase, meaning that such a search engine would become more useful. In its current state, the website acts as a good prototype for search functionality, and also demonstrates the potential for ‘mashing up’ XCRI data with numerous other datasets.
The code (such as it is) for the website is available on Github.