Difference between revisions of "Main Page/Featured article of the week/2023"

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<!-- <h2 style="font-size:105%; font-weight:bold; text-align:left; color:#000; padding:0.2em 0.4em; width:50%;">Featured article of the week: January 09–15:</h2>
<h2 style="font-size:105%; font-weight:bold; text-align:left; color:#000; padding:0.2em 0.4em; width:50%;">Featured article of the week: January 09–15:</h2>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Cecchetti JMIRMedInfo8 8-10.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Wong DataSciJourn22 21-1.png|240px]]</div>
'''"[[Journal:Fueling clinical and translational research in Appalachia: Informatics platform approach|Fueling clinical and translational research in Appalachia: Informatics platform approach]]"'''
'''"[[Journal:Development and governance of FAIR thresholds for a data federation|Development and governance of FAIR thresholds for a data federation]]"'''


The Appalachian population is distinct, not just culturally and geographically but also in its healthcare needs, facing the most health care disparities in the United States. To meet these unique demands, Appalachian medical centers need an arsenal of analytics and data science tools with the foundation of a centralized [[data warehouse]] to transform healthcare data into actionable clinical interventions. However, this is an especially challenging task given the fragmented state of medical data within Appalachia and the need for integration of other types of data such as environmental, social, and economic with medical data. This paper aims to present the structure and process of the development of an integrated platform at a midlevel Appalachian academic medical center, along with its initial uses ... ('''[[Journal:Fueling clinical and translational research in Appalachia: Informatics platform approach|Full article...]]''')<br />
The [[Journal:The FAIR Guiding Principles for scientific data management and stewardship|FAIR]] (findable, accessible, interoperable, and re-usable) principles and practice recommendations provide high-level guidance and recommendations that are not research-domain specific in nature. There remains a gap in practice at the data provider and domain scientist level, demonstrating how the FAIR principles can be applied beyond a set of generalist guidelines to meet the needs of a specific domain community. We present our insights developing FAIR thresholds in a domain-specific context for self-governance by a community (in this case, agricultural research). "Minimum thresholds" for FAIR data are required to align expectations for data delivered from providers’ distributed data stores through a community-governed federation (the Agricultural Research Federation, AgReFed) ... ('''[[Journal:Development and governance of FAIR thresholds for a data federation|Full article...]]''')<br />
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|<br /> //--><h2 style="font-size:105%; font-weight:bold; text-align:left; color:#000; padding:0.2em 0.4em; width:50%;">Featured article of the week: January 02–08:</h2>
|<br /><h2 style="font-size:105%; font-weight:bold; text-align:left; color:#000; padding:0.2em 0.4em; width:50%;">Featured article of the week: January 02–08:</h2>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig3 Giray Sustain21 13-13.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig3 Giray Sustain21 13-13.png|240px]]</div>
'''"[[Journal:Design of a data management reference architecture for sustainable agriculture|Design of a data management reference architecture for sustainable agriculture]]"'''
'''"[[Journal:Design of a data management reference architecture for sustainable agriculture|Design of a data management reference architecture for sustainable agriculture]]"'''

Revision as of 15:04, 16 January 2023

If you're looking for other "Article of the Week" archives: 2014 - 2015 - 2016 - 2017 - 2018 - 2019 - 2020 - 2021 - 2022 - 2023

Featured article of the week archive - 2023

Welcome to the LIMSwiki 2023 archive for the Featured Article of the Week.

Featured article of the week: January 09–15:

Fig1 Wong DataSciJourn22 21-1.png

"Development and governance of FAIR thresholds for a data federation"

The FAIR (findable, accessible, interoperable, and re-usable) principles and practice recommendations provide high-level guidance and recommendations that are not research-domain specific in nature. There remains a gap in practice at the data provider and domain scientist level, demonstrating how the FAIR principles can be applied beyond a set of generalist guidelines to meet the needs of a specific domain community. We present our insights developing FAIR thresholds in a domain-specific context for self-governance by a community (in this case, agricultural research). "Minimum thresholds" for FAIR data are required to align expectations for data delivered from providers’ distributed data stores through a community-governed federation (the Agricultural Research Federation, AgReFed) ... (Full article...)


Featured article of the week: January 02–08:

Fig3 Giray Sustain21 13-13.png

"Design of a data management reference architecture for sustainable agriculture"

Effective and efficient data management is crucial for smart farming and precision agriculture. To realize operational efficiency, full automation, and high productivity in agricultural systems, different kinds of data are collected from operational systems using different sensors, stored in different systems, and processed using advanced techniques, such as machine learning and deep learning. Due to the complexity of data management operations, a data management reference architecture is required. While there are different initiatives to design data management reference architectures, a data management reference architecture for sustainable agriculture is missing. In this study, we follow domain scoping, domain modeling, and reference architecture design stages to design the reference architecture for sustainable agriculture. Four case studies were performed to demonstrate the applicability of the reference architecture. This study shows that the proposed data management reference architecture is practical and effective for sustainable agriculture ... (Full article...)


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