Next I created the web page with data bound table – based on the circulation records from the placeholder data control. The easiest way of doing this was through the use of a Placeholder Data Control – that allows we to work with data that to the application appear like data from an enterprise resource such as a web service or a database but that in fact is typed in or read from a CSV file. In addition to the initial presentation, this ADF based version of the Delta Graph allows manipulation of the view, for example sorting the records by change or by current circulation:īefore creating the – data bound – Delta Graph display, I needed to create a data set that I could work with and bind the table to. So I started playing with ‘ordinary’ ADF Faces and – using some CSS definitions – I came up with the following ADF Faces rendition of the Delta Graph: And the inline-display inside table rows is related to spark charts, but again, it is not quite the same. Gauges appeared to come closest, but not quite there. However, it did not seem to offer a graph type that is very close to this presentation. My first port of call obviously was the ADF DVT (Data Visualization Tags) library. I started wondering it this way of presenting changes would be easy to implement in ADF Faces applications. It reveals a lot of information in an appealing way. The other day, my newspaper printed the next figure that illustrates the changes in circulation for all Dutch newspapers – comparing the 1st quarter of 2011 with one year ago. It inspires me to mimic in my own toolset: ADF. My morning paper has a broad palette of ways to represent numbers, trends, aggregates and incidents. Newspapers frequently use graphics to illustrate the news reported in their articles. Proper visualization provides quicker insight and reveals the true meaning of the numbers in an instant. And visualization of data can help to increase the value of the data tremendously. I may have bored you before with stories about Data Visualization.

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