Simulating data journalism to communicate hydrological information from sensor networks

Abstract

Presenting relevant information via web-based user friendly interfaces makes the information more accessible to the general public. This is especially useful for sensor networks that monitor natural environments. Adequately communicating this type of information helps increase awareness about the limited availability of natural resources and promotes their better use with sustainable practices. In this paper, I suggest an approach to communicating this information to wide audiences based on simulating data journalism using artificial intelligence techniques. I analyze this approach by describing a pioneer knowledge-based system called VSAIH, which looks for news in hydrological data from a national sensor network in Spain and creates news stories that general users can understand. VSAIH integrates artificial intelligence techniques, including a model-based data analyzer and a presentation planner. In the paper, I also describe characteristics of the hydrological national sensor network and the technical solutions applied by VSAIH to simulate data journalism. © Springer-Verlag Berlin Heidelberg 2012.