Title
Pine: A System for Crowdsourced Spatial Data Source Discovery While Map Browsing
Publication Date
2018
Document Type
Conference Proceeding
Abstract
Locating spatial data sources for a specific area of interest (AOI) is a difficult task, because of constantly updating server locations (URLs), specific layer location changes within that server location, and the relative unpopularity of a specific spatial data source. The proposed system, named Pine attempts to remedy the issue using automatic, yet user-led discovery of data sources by utilizing a web plug-in that discovers spatial data sources as users browse the web. The web plug-in has a two-fold function, (1) immediately presenting the spatial data source and all of the layers contained within that server discovered by the plug-in, (2) sending those layers and servers into a centralized, search-able repository that is accessible via the web. By utilizing the users browsing habits, and their machines as the discoverers of spatial data, Pine avoids the very high computational overhead of discovery of spatial data sources from a central server using a web crawling approach. As with any user-contributed data set, Pine must get users to actually contribute to the central repository, and it achieves this by including functionality that is useful to the user on its own by displaying a search-able list in the web plug-in of spatial data sources that the user has discovered themselves, a previously difficult task. The system implements a push based approach for discovering data sources, as the plug-in sends the data directly to the central repository, it is always up to date with the newest data sources discovered by any of the many instances of the web plug-in running on users computers.
First Page
592
Last Page
595
DOI
10.1145/3274895.3274971
Recommended Citation
Haynes, M.; Hendawi, A.; and Ali, M., "Pine: A System for Crowdsourced Spatial Data Source Discovery While Map Browsing" (2018). School of Engineering and Technology Publications. 327.
https://digitalcommons.tacoma.uw.edu/tech_pub/327