Progressive, Holistic Geospatial Interlinking

Abstract

Geospatial data constitute a considerable part of Semantic Web data, but at the moment, its sources are inadequately interlinked with topological relations in the Linked Open Data cloud. Geospatial Interlinking covers this gap with batch techniques that are restricted to individual topological relations, even though most operations are common for all main relations. In this work, we introduce a batch algorithm that simultaneously computes all topological relations and define the task of Progressive Geospatial Interlinking, which produces results in a pay-as-you-go manner when the available computational or temporal resources are limited. We propose two progressive algorithms and conduct a thorough experimental study over large, real datasets, demonstrating the superiority of our techniques over the current state-of-the-art.