The SPADES Framework for Scalable Management of Spatio-textual Data

Abstract

This paper presents the research activities in the context of the SPADES project for scalable indexing and processing of big spatial and spatio-textual data. Management of spatio-textual data raises challenges due to the high dimensional nature of text, in combination with the problem of preserving data locality for spatial data. In this paper, we provide an overview of our contributions in this field, both for centralized and parallel processing. We present an indexing layer that supports spatio-textual data, as well as other data types: spatio-temporal, multidimensional as well as semantic data represented in RDF. This is coupled with a processing layer that encompasses algorithms both for centralized and parallel processing.