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

André Freitas; Seán O’Riáin; Edward Curry

doi:10.1007/978-3-030-29665-0_7

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

André Freitas, Seán O’Riáin, Edward Curry

Research output: Chapter in Book or Conference Publication/Proceeding › Chapter › peer-review

3 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	Real-time Linked Dataspaces
Subtitle of host publication	Enabling Data Ecosystems for Intelligent Systems
Publisher	Springer International Publishing
Pages	105-124
Number of pages	20
ISBN (Electronic)	9783030296650
ISBN (Print)	9783030296643
DOIs	https://doi.org/10.1007/978-3-030-29665-0_7
Publication status	Published - 1 Jan 2019

Keywords

Best-effort
Data search
Dataspace
Knowledge graphs
Query processing

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10.1007/978-3-030-29665-0_7

Cite this

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AU - Curry, Edward

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

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Keywords

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