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

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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig6 BuřitaJOfSysInteg2018 9-1.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Tab1 Williamson F1000Res2023 10.png|240px]]</div>
'''"[[Journal:Information management in context of scientific disciplines|Information management in context of scientific disciplines]]"'''
'''"[[Journal:Data management challenges for artificial intelligence in plant and agricultural research|Data management challenges for artificial intelligence in plant and agricultural research]]"'''


This paper aims to analyze publications with the theme of [[information management]] (IM), cited on Web of Science (WoS) or Scopus. The frequency of publishing about IM has approached linear growth, from a few articles in the period 1966–1970 to 100 at the WoS and 600 at Scopus in the period 2011–2015. From this selection of publications, this analysis looked at 21 of the most cited articles on WoS and 21 of the most cited articles on Scopus, published in 31 different journals, oriented to [[informatics]] and computer science; economics, business, and management; medicine and psychology; art and the humanities; and ergonomics. The diversity of interest in IM in various areas of science, technology, and practice was confirmed. The content of the selected articles was analyzed in its area of interest, in relation to IM, and whether the definition of IM was mentioned. One of the goals was to confirm the hypothesis that IM is included in many scientific disciplines, that the concept of IM is used loosely, and it is mostly mentioned as part of data or information processing. ('''[[Journal:Information management in context of scientific disciplines|Full article...]]''')<br />
[[Artificial intelligence]] (AI) is increasingly used within plant science, yet it is far from being routinely and effectively implemented in this domain. Particularly relevant to the development of novel food and agricultural technologies is the development of validated, meaningful, and usable ways to integrate, compare, and [[Data visualization|visualize]] large, multi-dimensional datasets from different sources and scientific approaches. After a brief summary of the reasons for the interest in data science and AI within plant science, the paper identifies and discusses eight key challenges in [[Information management|data management]] that must be addressed to further unlock the potential of AI in crop and agronomic research, and particularly the application of [[machine learning]] (ML), which holds much promise for this domain ... ('''[[Journal:Data management challenges for artificial intelligence in plant and agricultural research|Full article...]]''')<br />
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''Recently featured'':
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}}

Revision as of 17:50, 15 April 2024

Tab1 Williamson F1000Res2023 10.png

"Data management challenges for artificial intelligence in plant and agricultural research"

Artificial intelligence (AI) is increasingly used within plant science, yet it is far from being routinely and effectively implemented in this domain. Particularly relevant to the development of novel food and agricultural technologies is the development of validated, meaningful, and usable ways to integrate, compare, and visualize large, multi-dimensional datasets from different sources and scientific approaches. After a brief summary of the reasons for the interest in data science and AI within plant science, the paper identifies and discusses eight key challenges in data management that must be addressed to further unlock the potential of AI in crop and agronomic research, and particularly the application of machine learning (ML), which holds much promise for this domain ... (Full article...)
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