A realtime sensing-data-triggered news article provision system with 5D world map

The most important aim of our study is to realize a multi-database for social sciences and environmental sciences. Our system connects heterogeneous databases about historical phenomena by using common spatiotemporal information and visualize the connected results onto 5D World Map (a set of chronologically ordered global maps). To actualize that, we created a news articles provision system using real-time sensor data as a trigger and determined the effectiveness in the experiment. Here we found that we can get the information about the happening in the same atmospheric condition in the past by exhibiting news articles. These results provide new insight into our understanding of the relationship between real-time situation and past occurrence with news articles.