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Interoperable & efficient: linked data for the internet of things

Interoperable & efficient: linked data for the internet of things
Interoperable & efficient: linked data for the internet of things
Two requirements to utilise the large source of time-series sensor data from the Internet of Things are interoperability and efficient access. We present a Linked Data solution that increases interoperability through the use and referencing of common identifiers and ontologies for integration. From our study of the shape of Internet of Things data, we show how we can improve access within the resource constraints of Lightweight Computers, compact machines deployed in close proximity to sensors, by storing time-series data succinctly as rows and producing Linked Data ‘just-in-time’. We examine our approach within two scenarios: a distributed meteorological analytics system and a smart home hub. We show with established benchmarks that in comparison to storing the data in a traditional Linked Data store, our approach provides gains in both storage efficiency and query performance from over 3 times to over three orders of magnitude on Lightweight Computers. Finally, we reflect how pushing computing to edge networks with our infrastructure can affect privacy, data ownership and data locality.
161-175
Siow, Eugene
01f33f70-e412-467c-aab2-5509d58d1b94
Tiropanis, Thanassis
d06654bd-5513-407b-9acd-6f9b9c5009d8
Hall, Wendy
11f7f8db-854c-4481-b1ae-721a51d8790c
Siow, Eugene
01f33f70-e412-467c-aab2-5509d58d1b94
Tiropanis, Thanassis
d06654bd-5513-407b-9acd-6f9b9c5009d8
Hall, Wendy
11f7f8db-854c-4481-b1ae-721a51d8790c

Siow, Eugene, Tiropanis, Thanassis and Hall, Wendy (2016) Interoperable & efficient: linked data for the internet of things. INSCI 2016, 3rd International conference on Internet Science, Italy. 12 - 14 Sep 2016. pp. 161-175. (doi:10.1007/978-3-319-45982-0_15).

Record type: Conference or Workshop Item (Paper)

Abstract

Two requirements to utilise the large source of time-series sensor data from the Internet of Things are interoperability and efficient access. We present a Linked Data solution that increases interoperability through the use and referencing of common identifiers and ontologies for integration. From our study of the shape of Internet of Things data, we show how we can improve access within the resource constraints of Lightweight Computers, compact machines deployed in close proximity to sensors, by storing time-series data succinctly as rows and producing Linked Data ‘just-in-time’. We examine our approach within two scenarios: a distributed meteorological analytics system and a smart home hub. We show with established benchmarks that in comparison to storing the data in a traditional Linked Data store, our approach provides gains in both storage efficiency and query performance from over 3 times to over three orders of magnitude on Lightweight Computers. Finally, we reflect how pushing computing to edge networks with our infrastructure can affect privacy, data ownership and data locality.

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Accepted/In Press date: May 2016
e-pub ahead of print date: 13 September 2016
Venue - Dates: INSCI 2016, 3rd International conference on Internet Science, Italy, 2016-09-12 - 2016-09-14
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 397474
URI: https://eprints.soton.ac.uk/id/eprint/397474
PURE UUID: 27579bce-5e51-4101-a68c-897409c466e8
ORCID for Eugene Siow: ORCID iD orcid.org/0000-0002-3593-2436
ORCID for Thanassis Tiropanis: ORCID iD orcid.org/0000-0002-6195-2852
ORCID for Wendy Hall: ORCID iD orcid.org/0000-0003-4327-7811

Catalogue record

Date deposited: 01 Jul 2016 13:29
Last modified: 09 Jan 2018 18:01

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Contributors

Author: Eugene Siow ORCID iD
Author: Wendy Hall ORCID iD

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