CBS Public-Private Platform funding for Dolores Morales


Economics Department Professor Dolores Romero Morales and colleague Daniel Hardt who were recently granted 36,000 DKK from the CBS Public-Private Platform for a research project on 'Visualizing Public Complex Data'.

The project concerns the visualization of complex public data. One important example is bublic linguistic data, which abound, for instance, in social media. Interpreting and visualizing linguistic data involves substantial challenges; words and phrases and phrases of varying lengths must be considered on various dimensions, including their relative frequencies and their inter-dependencies. These dependencies can in turn be viewed on various levels, including syntatic, semantic and pragmatic.
Complex data imply that the data has an additional attribute attached, as with spatial data. Electoral results are an example of spatial data, which involve the geographical coordinates of the electoral districts. Another example of complex data is time-stamped data such as university rankings, which take place on a yearly bases. Visualization tools for complex data should preserve the attribute associated with the data. In case of spatial data, a more effective display is obtained when the data is visualized onto a map. In case of time-stamped data, the visualization is more effective if there is a smooth visual transition from one period to the next. Although, there are many visualization tools for simple data, complex data has been overlooked.
The page was last edited by: Department of Economics // 11/10/2015