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


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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Correspondence to Edward Curry .

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Freitas, A., O’Riáin, S., Curry, E. (2020). Querying and Searching Heterogeneous Knowledge Graphs in Real-time Linked Dataspaces. In: Real-time Linked Dataspaces. Springer, Cham.

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  • Print ISBN: 978-3-030-29664-3

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