Faceted Search of Heterogeneous Geographic Information for Dynamic Map Projection
This addresses the challenge of efficiently exploring sparse and noisy geographic datasets for users of collaborative Web GIS tools, though it appears incremental relative to existing faceted search approaches.
The paper tackles the problem of exploring heterogeneous geographic information by proposing a faceted information exploration model with interactive widgets for dynamic map projection. The model outperforms simple category-based projection and traditional faceted search tools in user performance and experience when tested on geographic maps with multiple data categories.
This paper proposes a faceted information exploration model that supports coarse-grained and fine-grained focusing of geographic maps by offering a graphical representation of data attributes within interactive widgets. The proposed approach enables (i) a multi-category projection of long-lasting geographic maps, based on the proposal of efficient facets for data exploration in sparse and noisy datasets, and (ii) an interactive representation of the search context based on widgets that support data visualization, faceted exploration, category-based information hiding and transparency of results at the same time. The integration of our model with a semantic representation of geographical knowledge supports the exploration of information retrieved from heterogeneous data sources, such as Public Open Data and OpenStreetMap. We evaluated our model with users in the OnToMap collaborative Web GIS. The experimental results show that, when working on geographic maps populated with multiple data categories, it outperforms simple category-based map projection and traditional faceted search tools, such as checkboxes, in both user performance and experience.