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We describe our initial investigations into generating textual summaries of spatiotemporal data with the help of a prototype Natural Language Generation (NLG) system that produces pollen forecasts for Scotland. forecasts were written. An example of a pollen forecast text is shown in Figure 1, its corresponding data is shown in table 1. A pollen forecast in the map form is shown in Figure 2. ‘Monday looks set to bring another day of relatively high pollen counts, with values up to a very high eight in the Central Belt. . | Generating Spatio-Temporal Descriptions in Pollen Forecasts Ross Turner Somayajulu Sripada and Ehud Reiter Ian P Davy Dept of Computing Science Aerospace and Marine International University of Aberdeen UK Banchory Aberdeenshire UK rturner ssripada ereiter @csd.abdn.ac.uk idavy@weather3000.com Abstract We describe our initial investigations into generating textual summaries of spatiotemporal data with the help of a prototype Natural Language Generation NLG system that produces pollen forecasts for Scotland. 1 Introduction New monitoring devices such as remote sensing systems are generating vast amounts of spatio-temporal data. These devices coupled with the wider accessibility of the data have spurred large amounts of research into how it can best be analysed. There has been less research however into how the results of the data analysis can be effectively communicated. As part of a wider research project aiming to produce textual reports of complex spatio-temporal data we have developed a prototype NLG system which produces textual pollen forecasts for the general public. Pollen forecast texts describe predicted pollen concentration values for different regions of a country. Their production involves two subtasks predicting pollen concentration values for different regions of a country and describing these numerical values textu-ally.In our work we focus on the later subtask textual description of spatio-temporally distributed pollen concentration values. The subtask of predicting pollen concentrations is carried out by our industrial collaborator Aerospace and Marine International UK Ltd AMI . A fairly substantial amount of work already exists on weather forecast generation. A number of systems have been developed and are currently in commercial use with two of the most notable being FOG Goldberg etal. 1994 and MultiMeteo Coch 1998 . 2 Knowledge Acquisition Our knowledge acquisition activities consisted of corpus studies and discussions with experts. We have .
