Abstract
This paper reports on the development and application of strategies and tools for geographic information seeking and knowledge building that leverages unstructured text resources found on the web. Geographic knowledge building from unstructured web sources starts with web document foraging during which the quantity, scope and diversity of web-based information create incredible cognitive burdens on an analyst’s or researcher’s ability to judge information relevancy. Determining information relevancy is ultimately a process of sensemaking. In this paper, we present our research on visually supporting web document foraging and sensemaking. In particular, we present the Sense-of-Place ( SensePlace) analytic environment. The scientific goal of SensePlace is to visually and computationally support analyst sensemaking with text artifacts that have potential place, time, and thematic relevance to an analytical problem through identification and visual highlighting of named entities (people, places, times, and organizations) in documents, automated inference to determine document relevance using stored knowledge, and a visual interface with coupled geographic map, timeline, and concept graph displays that are used to contextualize the contexts of potentially relevant documents. We present the results of a case study analysis using SensePlace to uncover potential population migration, geopolitical, and other infectious disease dynamics drivers for measles and other epidemics in Niger. Our analysis allowed us to demonstrate how our approach can support analysis of complex situations along (a) multi-scale geographic dimensions (i.e., vaccine coverage areas), (b) temporal dimensions (i.e., seasonal population movement and migrations), and (c) diverse thematic dimensions (effects of political upheaval, food security, transient movement, etc.).
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