Theory and practice of linked open statistical data

Efthimios Tambouris; Evangelos Kalampokis; Marijn Janssen; Ricardo Matheus; Paul Hermans; Tarmo Kalvet

doi:10.1145/3209281.3209341

Theory and practice of linked open statistical data

Efthimios Tambouris, Evangelos Kalampokis, Marijn Janssen, Ricardo Matheus, Paul Hermans, Tarmo Kalvet

Information and Communication Technology

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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Abstract

The number of Open Statistical Data available for reuse is rapidly increasing. Linked open data technology enables easy reuse and linking of data residing in different locations in a simple and straightforward manner. Yet, many people are not familiar with the technology standards and tools for making use of open statistical data. In this tutorial, we will introduce Linked Open Statistical Data (LOSD) and demonstrate the use of LOSD technologies and tools to visualize open data obtained from various European Countries. We will also give the participants the opportunity to use these tools thus obtaining a personal experience on their capabilities.

Original language	English
Title of host publication	Proceedings of the 19th Annual International Conference on Digital Government Research
Subtitle of host publication	Governance in the Data Age, DG.O 2018
Publisher	Association for Computing Machinery (ACM)
ISBN (Electronic)	9781450365260
DOIs	https://doi.org/10.1145/3209281.3209341
Publication status	Published - 2018
Event	19th Annual International Conference on Digital Government Research: Governance in the Data Age, DG.O 2018 - Delf, Netherlands Duration: 30 May 2018 → 1 Jun 2018

Conference

Conference	19th Annual International Conference on Digital Government Research: Governance in the Data Age, DG.O 2018
Country/Territory	Netherlands
City	Delf
Period	30/05/18 → 1/06/18

Keywords

ICT Tools
Linked Open Data
Linked Open Statistics

Access to Document

10.1145/3209281.3209341

a130-tambourisFinal published version, 223 KB

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title = "Theory and practice of linked open statistical data",

abstract = "The number of Open Statistical Data available for reuse is rapidly increasing. Linked open data technology enables easy reuse and linking of data residing in different locations in a simple and straightforward manner. Yet, many people are not familiar with the technology standards and tools for making use of open statistical data. In this tutorial, we will introduce Linked Open Statistical Data (LOSD) and demonstrate the use of LOSD technologies and tools to visualize open data obtained from various European Countries. We will also give the participants the opportunity to use these tools thus obtaining a personal experience on their capabilities.",

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author = "Efthimios Tambouris and Evangelos Kalampokis and Marijn Janssen and Ricardo Matheus and Paul Hermans and Tarmo Kalvet",

year = "2018",

doi = "10.1145/3209281.3209341",

language = "English",

booktitle = "Proceedings of the 19th Annual International Conference on Digital Government Research",

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note = "19th Annual International Conference on Digital Government Research: Governance in the Data Age, DG.O 2018 ; Conference date: 30-05-2018 Through 01-06-2018",

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Tambouris, E, Kalampokis, E, Janssen, M, Matheus, R, Hermans, P & Kalvet, T 2018, Theory and practice of linked open statistical data. in Proceedings of the 19th Annual International Conference on Digital Government Research: Governance in the Data Age, DG.O 2018., a130, Association for Computing Machinery (ACM), 19th Annual International Conference on Digital Government Research: Governance in the Data Age, DG.O 2018, Delf, Netherlands, 30/05/18. https://doi.org/10.1145/3209281.3209341

Theory and practice of linked open statistical data. / Tambouris, Efthimios; Kalampokis, Evangelos; Janssen, Marijn et al.
Proceedings of the 19th Annual International Conference on Digital Government Research: Governance in the Data Age, DG.O 2018. Association for Computing Machinery (ACM), 2018. a130.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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T1 - Theory and practice of linked open statistical data

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AU - Kalampokis, Evangelos

AU - Janssen, Marijn

AU - Matheus, Ricardo

AU - Hermans, Paul

AU - Kalvet, Tarmo

PY - 2018

Y1 - 2018

N2 - The number of Open Statistical Data available for reuse is rapidly increasing. Linked open data technology enables easy reuse and linking of data residing in different locations in a simple and straightforward manner. Yet, many people are not familiar with the technology standards and tools for making use of open statistical data. In this tutorial, we will introduce Linked Open Statistical Data (LOSD) and demonstrate the use of LOSD technologies and tools to visualize open data obtained from various European Countries. We will also give the participants the opportunity to use these tools thus obtaining a personal experience on their capabilities.

AB - The number of Open Statistical Data available for reuse is rapidly increasing. Linked open data technology enables easy reuse and linking of data residing in different locations in a simple and straightforward manner. Yet, many people are not familiar with the technology standards and tools for making use of open statistical data. In this tutorial, we will introduce Linked Open Statistical Data (LOSD) and demonstrate the use of LOSD technologies and tools to visualize open data obtained from various European Countries. We will also give the participants the opportunity to use these tools thus obtaining a personal experience on their capabilities.

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KW - Linked Open Data

KW - Linked Open Statistics

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M3 - Conference contribution

AN - SCOPUS:85049002151

BT - Proceedings of the 19th Annual International Conference on Digital Government Research

PB - Association for Computing Machinery (ACM)

T2 - 19th Annual International Conference on Digital Government Research: Governance in the Data Age, DG.O 2018

Y2 - 30 May 2018 through 1 June 2018

ER -

Theory and practice of linked open statistical data

Abstract

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Keywords

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