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Patterns in the Public Square: Reference Models for Regulatory Science
Science and engineering involve discovery, representation, explanation, and exploitation of recurrent patterns, observed as phenomena. Model-based representations describe not only natural phenomena and engineered products, but also the socio-technical systems of systems that carry out scientific st...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer International Publishing
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9542451/ https://www.ncbi.nlm.nih.gov/pubmed/36207616 http://dx.doi.org/10.1007/s10439-022-03083-z |
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author | Schindel, William D. |
author_facet | Schindel, William D. |
author_sort | Schindel, William D. |
collection | PubMed |
description | Science and engineering involve discovery, representation, explanation, and exploitation of recurrent patterns, observed as phenomena. Model-based representations describe not only natural phenomena and engineered products, but also the socio-technical systems of systems that carry out scientific study, product engineering, medical practice, public health, commerce, and regulation. The term “Regulatory Science” invites us to represent and understand innovation, regulation and their intended and actual consequences as observable system phenomena in their own right, using scientific and engineering principles, tools, and insights. This article summarizes three classes of model-based reference patterns central to representing, understanding, communicating, and enhancing systems of innovation, regulation, and improvement over life cycles. In order of increasing scale, these pattern classes are (1) the domain-independent pattern of model-based representation of system phenomena (the S*Metamodel) in the sciences and engineering disciplines, underlying all modeling and simulation; (2) domain-specific patterns representing families of natural systems and engineered products in their life cycle contexts; and (3) the large-scale Innovation Ecosystem Pattern, in which science, engineering, commerce, medicine, and regulation are performed, planned, and advanced—including sharing of managed models and data across ecosystems. All three are applied by the Model-Based Patterns Working Group of the International Council on Systems Engineering (INCOSE). |
format | Online Article Text |
id | pubmed-9542451 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-95424512022-10-11 Patterns in the Public Square: Reference Models for Regulatory Science Schindel, William D. Ann Biomed Eng S.I. : Modeling for Advancing Regulatory Science Science and engineering involve discovery, representation, explanation, and exploitation of recurrent patterns, observed as phenomena. Model-based representations describe not only natural phenomena and engineered products, but also the socio-technical systems of systems that carry out scientific study, product engineering, medical practice, public health, commerce, and regulation. The term “Regulatory Science” invites us to represent and understand innovation, regulation and their intended and actual consequences as observable system phenomena in their own right, using scientific and engineering principles, tools, and insights. This article summarizes three classes of model-based reference patterns central to representing, understanding, communicating, and enhancing systems of innovation, regulation, and improvement over life cycles. In order of increasing scale, these pattern classes are (1) the domain-independent pattern of model-based representation of system phenomena (the S*Metamodel) in the sciences and engineering disciplines, underlying all modeling and simulation; (2) domain-specific patterns representing families of natural systems and engineered products in their life cycle contexts; and (3) the large-scale Innovation Ecosystem Pattern, in which science, engineering, commerce, medicine, and regulation are performed, planned, and advanced—including sharing of managed models and data across ecosystems. All three are applied by the Model-Based Patterns Working Group of the International Council on Systems Engineering (INCOSE). Springer International Publishing 2022-10-07 2023 /pmc/articles/PMC9542451/ /pubmed/36207616 http://dx.doi.org/10.1007/s10439-022-03083-z Text en © The Author(s) under exclusive licence to Biomedical Engineering Society 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | S.I. : Modeling for Advancing Regulatory Science Schindel, William D. Patterns in the Public Square: Reference Models for Regulatory Science |
title | Patterns in the Public Square: Reference Models for Regulatory Science |
title_full | Patterns in the Public Square: Reference Models for Regulatory Science |
title_fullStr | Patterns in the Public Square: Reference Models for Regulatory Science |
title_full_unstemmed | Patterns in the Public Square: Reference Models for Regulatory Science |
title_short | Patterns in the Public Square: Reference Models for Regulatory Science |
title_sort | patterns in the public square: reference models for regulatory science |
topic | S.I. : Modeling for Advancing Regulatory Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9542451/ https://www.ncbi.nlm.nih.gov/pubmed/36207616 http://dx.doi.org/10.1007/s10439-022-03083-z |
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