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10.1186/s13007-015-0097-z http://scihub22266oqcxt.onion/10.1186/s13007-015-0097-z C4672489!4672489 !26649067     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=26649067 &cmd=llinks): Failed to open stream: HTTP request failed! 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SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data |pdf=|usr=}}{{26649067 }} gab.com Text SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data JO: Plant Methods http://www.kidney.de/pget.php?&tw=1&pmid=26649067 #FOAvip 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. Twit Text FOAVip SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data ????Plant Methods http://www.kidney.de/pget.php?&tw=1&pmid=26649067 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26649067 #FOAvip English Wikipedia <ref>{{Cite pmid|26649067 }}</ref> SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data #MMPMID26649067 Salehi A ; Jimenez-Berni J ; Deery DM ; Palmer D ; Holland E ; Rozas-Larraondo P ; Chapman SC ; Georgakopoulos D ; Furbank RT Plant Methods 2015[]; 11 (ä): 53 PMID26649067 show ga 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. äSensorDB: a virtual laboratory for the integration, visualization and (epmc).pdf DeepDyve Pubget Overpricing