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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Rao JofBigData2018 5.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Huang iScience2022 25-8.jpg|240px]]</div>
'''"[[Journal:Privacy preservation techniques in big data analytics: A survey|Privacy preservation techniques in big data analytics: A survey]]"'''
'''"[[Journal:Elegancy: Digitizing the wisdom from laboratories to the cloud with free no-code platform|Elegancy: Digitizing the wisdom from laboratories to the cloud with free no-code platform]]"'''


Incredible amounts of data are being generated by various organizations like [[hospital]]s, banks, e-commerce, retail and supply chain, etc. by virtue of digital technology. Not only humans but also machines contribute to data streams in the form of closed circuit television (CCTV) streaming, web site logs, etc. Tons of data is generated every minute by social media and smart phones. The voluminous data generated from the various sources can be processed and analyzed to support decision making. However [[Data analysis|data analytics]] is prone to privacy violations. One of the applications of data analytics is recommendation systems, which are widely used by e-commerce sites like Amazon and Flipkart for suggesting products to customers based on their buying habits, leading to inference attacks. Although data analytics is useful in decision making, it will lead to serious privacy concerns. Hence privacy preserving data analytics became very important. This paper examines various privacy threats, privacy preservation techniques, and models with their limitations. The authors then propose a data lake-based modernistic privacy preservation technique to handle privacy preservation in unstructured data. ('''[[Journal:Privacy preservation techniques in big data analytics: A survey|Full article...]]''')<br />
One of the top priorities in any [[laboratory]] is [[Archival informatics|archiving]] experimental data in the most secure, efficient, and errorless way. It is especially important to those in chemical and biological research, for it is more likely to damage experiment records. In addition, the transmission of experiment results from paper to electronic devices is time-consuming and redundant. Therefore, we introduce an [[Open-source software|open-source]] no-code [[electronic laboratory notebook]] (ELN), Elegancy, a [[Cloud computing|cloud-based]]/standalone web service distributed as a Docker image. Elegancy fits all laboratories but is specially equipped with several features benefitting biochemical laboratories. It can be accessed via various web browsers, allowing researchers to upload photos or audio recordings directly from their mobile devices. Elegancy also contains a meeting arrangement module, audit/revision control, and laboratory supply management system. We believe Elegancy could help the scientific research community gather evidence, share information, reorganize knowledge, and digitize laboratory works with greater ease and security ... ('''[[Journal:Elegancy: Digitizing the wisdom from laboratories to the cloud with free no-code platform|Full article...]]''')<br />
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Latest revision as of 17:08, 10 April 2023

Fig1 Huang iScience2022 25-8.jpg

"Elegancy: Digitizing the wisdom from laboratories to the cloud with free no-code platform"

One of the top priorities in any laboratory is archiving experimental data in the most secure, efficient, and errorless way. It is especially important to those in chemical and biological research, for it is more likely to damage experiment records. In addition, the transmission of experiment results from paper to electronic devices is time-consuming and redundant. Therefore, we introduce an open-source no-code electronic laboratory notebook (ELN), Elegancy, a cloud-based/standalone web service distributed as a Docker image. Elegancy fits all laboratories but is specially equipped with several features benefitting biochemical laboratories. It can be accessed via various web browsers, allowing researchers to upload photos or audio recordings directly from their mobile devices. Elegancy also contains a meeting arrangement module, audit/revision control, and laboratory supply management system. We believe Elegancy could help the scientific research community gather evidence, share information, reorganize knowledge, and digitize laboratory works with greater ease and security ... (Full article...)

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