Querying and Searching Heterogeneous Knowledge Graphs in Real-time Linked Dataspaces

Open Access


As the volume and variety of data sources within a dataspace grow, it becomes a semantically heterogeneous and distributed environment; this presents a significant challenge to querying the dataspace. Approaches used for querying siloed databases fail within large dataspaces because users do not have an a priori understanding of all the available datasets. This chapter investigates the main challenges in constructing query and search services for knowledge graphs within a linked dataspace. Search and query services within a linked dataspace do not follow a one-size-fits-all approach and utilise a range of different techniques to support different characteristics of data sources and user needs.


Knowledge graphs Query processing Data search Best-effort Dataspace 

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© The Author(s) 2020

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Authors and Affiliations

  1. 1.Insight Centre for Data AnalyticsNational University of Ireland GalwayGalwayIreland
  2. 2.National University of Ireland GalwayGalwayIreland

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