SIWAM: Using Social Data to Semantically Assess the Difficulties in Mountain Activities

In the last few years, the amount of people moving to the mountains to do several activities such as hiking, climbing or mountaineering, is steadily increasing. Not surprisingly, this has come along with a raise in the amount of accidents, which are mainly due to the inexperience of the people, and the lack of information and proper planning. Although one could expect to find appropriate updated information about this issue on the Internet, most of the information related to mountain activities is stored in personal blogs, or in Web sites that are not exploiting the possibilities that the Semantic Web and the Social Web offer regarding content generation and information processing. In this paper, we present SIWAM, a semantic framework oriented to share and evaluate the difficulties of mountain activities. It provides a thematic social network front-end to enable users to share their descriptions about their own experiences. Using text mining techniques on these descriptions, it extracts relevant facts about these experiences, which are used to evaluate the difficulty of the particular activity. The evaluation is done according to a well-established standard for evaluating the difficulty of mountain activities (MIDE), which is modeled in the system using ontologies.