Difference between revisions of "Template:Article of the week"

From LIMSWiki
Jump to navigationJump to search
(Updated article of the week text)
(Updated article of the week text)
 
(47 intermediate revisions by the same user not shown)
Line 1: Line 1:
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Gonzales PLOSComBio22 18-8.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Soto-Perdomo SoftwareX2023 24.jpg|240px]]</div>
'''"[[Journal:Ten simple rules for maximizing the recommendations of the NIH data management and sharing plan|Ten simple rules for maximizing the recommendations of the NIH data management and sharing plan]]"'''
'''"[[Journal:OptiGUI DataCollector: A graphical user interface for automating the data collecting process in optical and photonics labs|OptiGUI DataCollector: A graphical user interface for automating the data collecting process in optical and photonics labs]]"'''
 
OptiGUI DataCollector is a Python 3.8-based graphical user interface (GUI) that facilitates automated data collection in optics and photonics research and development equipment. It provides an intuitive and easy-to-use platform for controlling a wide range of optical instruments, including [[spectrometer]]s and lasers. OptiGUI DataCollector is a flexible and modular framework that enables simple integration with different types of devices. It simplifies experimental workflow and reduces human error by automating parameter control, data acquisition, and [[Data analysis|analysis]]. OptiGUI DataCollector is currently focused on optical mode conversion utilizing fiber optic technologies ... ('''[[Journal:OptiGUI DataCollector: A graphical user interface for automating the data collecting process in optical and photonics labs|Full article...]]''')<br />


The [[National Institutes of Health]] (NIH) Policy for Data Management and Sharing (DMS Policy) recognizes the NIH’s role as a key steward of the United States' biomedical research and information and seeks to enhance that stewardship through systematic recommendations for the preservation and [[Data sharing|sharing]] of research data generated by funded projects. The policy is effective as of January 2023. The recommendations include a requirement for the submission of a data management and sharing plan (DMSP) with funding applications, and while no strict template was provided, the NIH has released supplemental draft guidance on elements to consider when developing such a plan. This article provides 10 key recommendations for creating a DMSP that is both maximally compliant and effective. ('''[[Journal:Ten simple rules for maximizing the recommendations of the NIH data management and sharing planFull article...]]''')<br />
''Recently featured'':
''Recently featured'':
{{flowlist |
{{flowlist |
* [[Journal:Understanding cybersecurity frameworks and information security standards: A review and comprehensive overview|Understanding cybersecurity frameworks and information security standards: A review and comprehensive overview]]
* [[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]
* [[Journal:Bridging data management platforms and visualization tools to enable ad-hoc and smart analytics in life sciences|Bridging data management platforms and visualization tools to enable ad-hoc and smart analytics in life sciences]]
* [[Journal:Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology|Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology]]
* [[Journal:Digitalization of calibration data management in the pharmaceutical industry using a multitenant platform|Digitalization of calibration data management in the pharmaceutical industry using a multitenant platform]]
* [[Journal:Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study|Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study]]
}}
}}

Latest revision as of 15:05, 17 June 2024

Fig1 Soto-Perdomo SoftwareX2023 24.jpg

"OptiGUI DataCollector: A graphical user interface for automating the data collecting process in optical and photonics labs"

OptiGUI DataCollector is a Python 3.8-based graphical user interface (GUI) that facilitates automated data collection in optics and photonics research and development equipment. It provides an intuitive and easy-to-use platform for controlling a wide range of optical instruments, including spectrometers and lasers. OptiGUI DataCollector is a flexible and modular framework that enables simple integration with different types of devices. It simplifies experimental workflow and reduces human error by automating parameter control, data acquisition, and analysis. OptiGUI DataCollector is currently focused on optical mode conversion utilizing fiber optic technologies ... (Full article...)

Recently featured: