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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Water Stress Around 2000 A.D. By WaterGAP.jpg|280px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Berezin PLoSCompBio23 19-12.png|240px]]</div>
'''[[Hydroinformatics]]''' is the multidisciplinary application of information and decision support systems to address the equitable and efficient management and use of water for many different purposes. Hydroinformatics draws on and integrates hydraulics, hydrology, environmental engineering, and many other disciplines. It sees application at all points in the water cycle, from atmosphere to ocean, and in artificial interventions in that cycle such as urban drainage and water supply systems. It provides support for decision making at all levels, from governance and policy through to management and operations.
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


Hydroinformatics also recogniszs the inherently social nature of the problems of water management and of decision making processes, and it includes mechanisms towards understanding the social processes by which technologies are brought into use and how they change the water system. Since the resources to obtain and develop technological solutions affecting water collection, purification, and distribution continue to be concentrated in the hands of the minority, the need to examine these social processes are particularly acute. Hydroinformatics can help tackle problems and tasks such as improving shallow-water flow models, optimizing damn breaks, and constructing bridges across bodies of water. ('''[[Hydroinformatics|Full article...]]''')<br />
[[Information]] is the cornerstone of [[research]], from experimental data/[[metadata]] and computational processes to complex inventories of reagents and equipment. These 10 simple rules discuss best practices for leveraging [[laboratory information management system]]s (LIMS) to transform this large information load into useful scientific findings. The development of [[mathematical model]]s that can predict the properties of biological systems is the holy grail of [[computational biology]]. Such models can be used to test biological hypotheses, guide the development of biomanufactured products, engineer new systems meeting user-defined specifications, and much more ... ('''[[Journal:Ten simple rules for managing laboratory information|Full article...]]''')<br />
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Latest revision as of 18:03, 10 June 2024

Fig2 Berezin PLoSCompBio23 19-12.png

"Ten simple rules for managing laboratory information"

Information is the cornerstone of research, from experimental data/metadata and computational processes to complex inventories of reagents and equipment. These 10 simple rules discuss best practices for leveraging laboratory information management systems (LIMS) to transform this large information load into useful scientific findings. The development of mathematical models that can predict the properties of biological systems is the holy grail of computational biology. Such models can be used to test biological hypotheses, guide the development of biomanufactured products, engineer new systems meeting user-defined specifications, and much more ... (Full article...)

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