Current public and commercial services present, as a rule, “raw” data on environmental conditions such as air, water and snow quality, the water-level, and pollen count. But raw environmental data are not self-explanatory. To be informative, they require an interpretation and a tailoring to the health, interest and knowledge profiles of the citizens.
MARQUIS is a project in the current eContent programme of the EC. It is designed to address the above problem by english essay:
- a cross-border information service that provides user-tailored analysis, interpretation, and multilingual communication of me-teorological and air quality information for selected regions in the EU;
- a detailed comercialisation model of this service for both private and public institutions using the internet, mobile phone services, and the printed media as distribution media.
The central information processing features of MARQUIS’ service include:
- fine-grained local assessment of air pollutant emission and meteorological conditions using state of the art models;
- analysis of the air quality data with respect to their distribution over time or space and their correlation with meteorological conditions;
- interpretation of the environmental data with respect to their relevance to legal regulations, specific health and interest profiles and/or specific cultural backgrounds, a specific region, health-care, etc.
The central information providing features of MARQUIS’ service include:
- “on the fly” gene-ration of textual information using state of the art Computational Linguistics techniques in Catalan, English, Finnish, French, German, Polish, Portuguese, and Spanish – with region and culture-specific priorities being taken into account;
- generation of graphics and tables,
- maintenance of regional profiles with geographical and cultural characteristics as well as of individual customer login profiles concerning the interests, personal characteristics, expertise in the domain, and the information already provided by the service;
- information delivery on demand and event-driven.