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

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'''"[[Journal:Advanced engineering informatics: Philosophical and methodological foundations with examples from civil and construction engineering|Advanced engineering informatics: Philosophical and methodological foundations with examples from civil and construction engineering]]"'''
'''"[[Journal:Ten simple rules for managing laboratory information|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 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 />


We argue that the representation and formalization of complex engineering knowledge is the main aim of inquiries in the scientific field of [[Wikipedia:Engineering informatics|advanced engineering informatics]]. We introduce [[Ontology (information science)|ontology]] and logic as underlying methods to formalize [[Information#As an influence which leads to a transformation|knowledge]]. We also suggest that it is important to account for the purpose of engineers and the context they work in while representing and formalizing knowledge. Based on the concepts of ontology, logic, purpose, and context, we discuss different possible research methods and approaches that scholars can use to formalize complex engineering knowledge and to validate whether a specific formalization can support engineers with their complex tasks. On the grounds of this discussion, we suggest that research efforts in advanced engineering should be conducted in a bottom-up manner, closely involving engineering practitioners. We also suggest that researchers make use of social science methods while both eliciting knowledge to formalize and validating that formalized knowledge. ('''[[Journal:Advanced engineering informatics: Philosophical and methodological foundations with examples from civil and construction engineering|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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