Applying Geospatial Data Mining and Knowledge Discovery in Extraction of Volunteered Geographic Information---A Case Study of Birdwatching Data

With the prevalence of Web 2.0 social network sites and blogs, innovating network communication technology, and location-based services, the spatio-temporal multimedia data disseminated on the Internet has also grown exponentially. Numerous non-professional users frequently voluntarily disseminate spatio-temporal multimedia data. However, although network users can voluntarily share spatio-temporal multimedia data, collecting the data requires a significant amount of time; occasionally they even experience setbacks by no knowing how to convert the data. Volunteered spatio-temporal multimedia data contains extensive information, has the characteristics of Web 2.0 data, and was expanded from the original server construction companies to common users. Thus, developing more efficient spatio-temporal knowledge discovery and data mining technologies to analyze volunteered spatio-temporal multimedia data is a priority. This research is a two-year project that aims to develop a set of spatio-temporal techniques for compiling volunteered spatio-temporal data from the Internet and create a database. For example, we will use online avian information combined with our spatio-temporal information techniques to compile and analyze the information obtained from the WWW and disseminated by birdwatchers. The goals for the first year include the following: (1) Establish a spatio-temporal algorithm and database; (2) develop methods for extracting, exploring, and analyzing social network sites; and (3) apply the developed techniques to manage the information collected from the WWW by birdwatchers and create a database of avian habitats and migration behavior. The goals for the second year include the following: (1) Validate our algorithm and databse; (2) develop accessing, indexing, inquiring, optimizing, retrieving, and visualizing techniques for the volunteered spatio-temporal multimedia database; and (3) determine the avian spatial distribution condition using avian habitat and migration information.

Project ID:PB10108-3611
External Project ID:NSC101-2119-M182-001