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SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data

BACKGROUND: To our knowledge, there is no software or database solution that supports large volumes of biological time series sensor data efficiently and enables data visualization and analysis in real time. Existing solutions for managing data typically use unstructured file systems or relational d...

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Autores principales: Salehi, Ali, Jimenez-Berni, Jose, Deery, David M., Palmer, Doug, Holland, Edward, Rozas-Larraondo, Pablo, Chapman, Scott C., Georgakopoulos, Dimitrios, Furbank, Robert T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4672489/
https://www.ncbi.nlm.nih.gov/pubmed/26649067
http://dx.doi.org/10.1186/s13007-015-0097-z
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author Salehi, Ali
Jimenez-Berni, Jose
Deery, David M.
Palmer, Doug
Holland, Edward
Rozas-Larraondo, Pablo
Chapman, Scott C.
Georgakopoulos, Dimitrios
Furbank, Robert T.
author_facet Salehi, Ali
Jimenez-Berni, Jose
Deery, David M.
Palmer, Doug
Holland, Edward
Rozas-Larraondo, Pablo
Chapman, Scott C.
Georgakopoulos, Dimitrios
Furbank, Robert T.
author_sort Salehi, Ali
collection PubMed
description BACKGROUND: To our knowledge, there is no software or database solution that supports large volumes of biological time series sensor data efficiently and enables data visualization and analysis in real time. Existing solutions for managing data typically use unstructured file systems or relational databases. These systems are not designed to provide instantaneous response to user queries. Furthermore, they do not support rapid data analysis and visualization to enable interactive experiments. In large scale experiments, this behaviour slows research discovery, discourages the widespread sharing and reuse of data that could otherwise inform critical decisions in a timely manner and encourage effective collaboration between groups. RESULTS: In this paper we present SensorDB, a web based virtual laboratory that can manage large volumes of biological time series sensor data while supporting rapid data queries and real-time user interaction. SensorDB is sensor agnostic and uses web-based, state-of-the-art cloud and storage technologies to efficiently gather, analyse and visualize data. CONCLUSIONS: Collaboration and data sharing between different agencies and groups is thereby facilitated. SensorDB is available online at http://sensordb.csiro.au.
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spelling pubmed-46724892015-12-09 SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data Salehi, Ali Jimenez-Berni, Jose Deery, David M. Palmer, Doug Holland, Edward Rozas-Larraondo, Pablo Chapman, Scott C. Georgakopoulos, Dimitrios Furbank, Robert T. Plant Methods Software BACKGROUND: To our knowledge, there is no software or database solution that supports large volumes of biological time series sensor data efficiently and enables data visualization and analysis in real time. Existing solutions for managing data typically use unstructured file systems or relational databases. These systems are not designed to provide instantaneous response to user queries. Furthermore, they do not support rapid data analysis and visualization to enable interactive experiments. In large scale experiments, this behaviour slows research discovery, discourages the widespread sharing and reuse of data that could otherwise inform critical decisions in a timely manner and encourage effective collaboration between groups. RESULTS: In this paper we present SensorDB, a web based virtual laboratory that can manage large volumes of biological time series sensor data while supporting rapid data queries and real-time user interaction. SensorDB is sensor agnostic and uses web-based, state-of-the-art cloud and storage technologies to efficiently gather, analyse and visualize data. CONCLUSIONS: Collaboration and data sharing between different agencies and groups is thereby facilitated. SensorDB is available online at http://sensordb.csiro.au. BioMed Central 2015-12-08 /pmc/articles/PMC4672489/ /pubmed/26649067 http://dx.doi.org/10.1186/s13007-015-0097-z Text en © Salehi et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Salehi, Ali
Jimenez-Berni, Jose
Deery, David M.
Palmer, Doug
Holland, Edward
Rozas-Larraondo, Pablo
Chapman, Scott C.
Georgakopoulos, Dimitrios
Furbank, Robert T.
SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data
title SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data
title_full SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data
title_fullStr SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data
title_full_unstemmed SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data
title_short SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data
title_sort sensordb: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4672489/
https://www.ncbi.nlm.nih.gov/pubmed/26649067
http://dx.doi.org/10.1186/s13007-015-0097-z
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