GeoSneakPique: Visual Autocompletion for Geospatial Queries
This addresses the challenge for users of geospatial data who struggle with ambiguous location definitions in queries, though it is incremental as it builds on existing interface methods.
The paper tackles the problem of specifying geographic locations in natural language queries, especially for fuzzy cognitive regions, by introducing GeoSneakPique, a mapping widget that allows users to define areas interactively with data-driven guidance, and a qualitative evaluation indicates its usefulness.
How many crimes occurred in the city center? And exactly which part of town is the 'city center'? While location is at the heart of many data questions, geographic location can be difficult to specify in natural language (NL) queries. This is especially true when working with fuzzy cognitive regions or regions that may be defined based on data distributions instead of absolute administrative location (e.g., state, country). GeoSneakPique presents a novel method for using a mapping widget to support the NL query process, allowing users to specify location via direct manipulation with data-driven guidance on spatial distributions to help select the area of interest. Users receive feedback to help them evaluate and refine their spatial selection interactively and can save spatial definitions for re-use in subsequent queries. We conduct a qualitative evaluation of the GeoSneakPique that indicates the usefulness of the interface as well as opportunities for better supporting geospatial workflows in visual analysis tasks employing cognitive regions.