Deriving Locational Reference through Implicit Information Retrieval

Abstract

The often fragmented process of online spatial data retrieval remains a barrier to domain scientists interested in spatial analysis. Although there is a wealth of hidden spatial information online, scientists without prior experience querying web APIs (Application Programming Interface) or scraping web documents cannot extract this potentially valuable implicit information across a growing number of sources. In an attempt to broaden the spectrum of exploitable spatial data sources, this paper proposes an extensible, locational reference deriving model that shifts extraction and encoding logic from the user to a preprocessing mediation layer. To implement this, we develop a user interface that: collects data through web APIs and scrapers, determines locational reference as geometries, and re-encodes the data as explicit spatial information, usable with spatial analysis tools, such as those in R or ArcGIS.