Holistic Analytics of Sensor Data from Renewable Energy Sources: A Vision Paper

Søren Kejser Jensen; Christian Thomsen

doi:10.1007/978-3-031-42941-5_31

Holistic Analytics of Sensor Data from Renewable Energy Sources: A Vision Paper

Søren Kejser Jensen, Christian Thomsen^*

^*Kontaktforfatter

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

2 Citationer (Scopus)

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Abstract

Modern Renewable Energy System (RES) installations, e.g., wind turbines, produce petabytes of high-frequency time series. State of-the-art systems cannot cope with such amounts of data. Thus, practitioners generally store simple aggregates, e.g., 10-min averages. Based on discussions with practitioners, we present requirements and our vision for a next-generation time series management system that can efficiently manage vast amounts of time series across edge, cloud, and client.

Originalsprog	Engelsk
Titel	New Trends in Database and Information Systems, ADBIS 2023 Proceedings
Redaktører	Alberto Abelló, Oscar Romero, Panos Vassiliadis, Robert Wrembel, Francesca Bugiotti, Johann Gamper, Genoveva Vargas Solar, Ester Zumpano
Antal sider	7
Forlag	Springer
Publikationsdato	31 aug. 2023
Sider	360-366
ISBN (Trykt)	978-3-031-42940-8
ISBN (Elektronisk)	978-3-031-42941-5
DOI	https://doi.org/10.1007/978-3-031-42941-5_31
Status	Udgivet - 31 aug. 2023
Begivenhed	Proceedings of the 27th European Conference on Advances in Databases and Information Systems, ADBIS 2023 - Barcelona, Spanien Varighed: 4 sep. 2023 → 7 sep. 2023

Konference

Konference	Proceedings of the 27th European Conference on Advances in Databases and Information Systems, ADBIS 2023
Land/Område	Spanien
By	Barcelona
Periode	04/09/2023 → 07/09/2023

Navn	Communications in Computer and Information Science
Vol/bind	1850 CCIS
ISSN	1865-0929

Bibliografisk note

Publisher Copyright:
© 2023, The Author(s).

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10.1007/978-3-031-42941-5_31Licens: CC BY 4.0

Open Access articleForlagets udgivne version, 232 KBLicens: CC BY 4.0

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2 Citationer
1 Bidrag til bog/antologi

Time Series Management Systems: A 2022 Survey
Jensen, S. K., Pedersen, T. B. & Thomsen, C., 4 dec. 2022, (Accepteret/In press) Data Series Management and Analytics. Palpanas, T. & Zoumpatianos, K. (red.). Association for Computing Machinery, 81 s.
Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Bidrag til bog/antologi › Forskning › peer review

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Citationsformater

Jensen, S. K., & Thomsen, C. (2023). Holistic Analytics of Sensor Data from Renewable Energy Sources: A Vision Paper. I A. Abelló, O. Romero, P. Vassiliadis, R. Wrembel, F. Bugiotti, J. Gamper, G. Vargas Solar, & E. Zumpano (red.), New Trends in Database and Information Systems, ADBIS 2023 Proceedings (s. 360-366). Springer. https://doi.org/10.1007/978-3-031-42941-5_31

Jensen, Søren Kejser ; Thomsen, Christian. / Holistic Analytics of Sensor Data from Renewable Energy Sources : A Vision Paper. New Trends in Database and Information Systems, ADBIS 2023 Proceedings. red. / Alberto Abelló ; Oscar Romero ; Panos Vassiliadis ; Robert Wrembel ; Francesca Bugiotti ; Johann Gamper ; Genoveva Vargas Solar ; Ester Zumpano. Springer, 2023. s. 360-366 (Communications in Computer and Information Science, Bind 1850 CCIS).

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abstract = "Modern Renewable Energy System (RES) installations, e.g., wind turbines, produce petabytes of high-frequency time series. State of-the-art systems cannot cope with such amounts of data. Thus, practitioners generally store simple aggregates, e.g., 10-min averages. Based on discussions with practitioners, we present requirements and our vision for a next-generation time series management system that can efficiently manage vast amounts of time series across edge, cloud, and client.",

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note = "Publisher Copyright: {\textcopyright} 2023, The Author(s).; Proceedings of the 27th European Conference on Advances in Databases and Information Systems, ADBIS 2023 ; Conference date: 04-09-2023 Through 07-09-2023",

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Jensen, SK & Thomsen, C 2023, Holistic Analytics of Sensor Data from Renewable Energy Sources: A Vision Paper. i A Abelló, O Romero, P Vassiliadis, R Wrembel, F Bugiotti, J Gamper, G Vargas Solar & E Zumpano (red), New Trends in Database and Information Systems, ADBIS 2023 Proceedings. Springer, Communications in Computer and Information Science, bind 1850 CCIS, s. 360-366, Proceedings of the 27th European Conference on Advances in Databases and Information Systems, ADBIS 2023, Barcelona, Spanien, 04/09/2023. https://doi.org/10.1007/978-3-031-42941-5_31

Holistic Analytics of Sensor Data from Renewable Energy Sources: A Vision Paper. / Jensen, Søren Kejser ; Thomsen, Christian.
New Trends in Database and Information Systems, ADBIS 2023 Proceedings. red. / Alberto Abelló; Oscar Romero; Panos Vassiliadis; Robert Wrembel; Francesca Bugiotti; Johann Gamper; Genoveva Vargas Solar; Ester Zumpano. Springer, 2023. s. 360-366 (Communications in Computer and Information Science, Bind 1850 CCIS).

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

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AB - Modern Renewable Energy System (RES) installations, e.g., wind turbines, produce petabytes of high-frequency time series. State of-the-art systems cannot cope with such amounts of data. Thus, practitioners generally store simple aggregates, e.g., 10-min averages. Based on discussions with practitioners, we present requirements and our vision for a next-generation time series management system that can efficiently manage vast amounts of time series across edge, cloud, and client.

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A2 - Romero, Oscar

A2 - Vassiliadis, Panos

A2 - Wrembel, Robert

A2 - Bugiotti, Francesca

A2 - Gamper, Johann

A2 - Vargas Solar, Genoveva

A2 - Zumpano, Ester

PB - Springer

Y2 - 4 September 2023 through 7 September 2023

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Jensen SK , Thomsen C. Holistic Analytics of Sensor Data from Renewable Energy Sources: A Vision Paper. I Abelló A, Romero O, Vassiliadis P, Wrembel R, Bugiotti F, Gamper J, Vargas Solar G, Zumpano E, red., New Trends in Database and Information Systems, ADBIS 2023 Proceedings. Springer. 2023. s. 360-366. (Communications in Computer and Information Science, Bind 1850 CCIS). doi: 10.1007/978-3-031-42941-5_31

Holistic Analytics of Sensor Data from Renewable Energy Sources: A Vision Paper

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Time Series Management Systems: A 2022 Survey

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