跨学科数据集成方法

Q4 Engineering
Spool Pub Date : 2022-05-27 DOI:10.47982/spool.2022.1.00
M. Hensel, H. Bier
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引用次数: 0

摘要

快速城市化伴随着相关的土地覆盖和土地利用变化以及资源枯竭,助长了生态系统和生物多样性的退化,并对人类健康和福祉产生负面影响。社会对反应和结果的要求对与环境有关的各个领域的研究和教育构成了重大挑战。除了当前的环境危机,迫切需要在数据驱动的方法、工作流程和工具的帮助下,为建筑环境开发“绿色解决方案”。鉴于这些发展,需要从狭窄的学科和特定领域的方法转向更广泛的跨学科、多领域和多标量战略。这包括数据获取、数据共享和数据整合,以及数据驱动的建模,以便能够解决快速城市化所产生的可持续性问题的复杂性。虽然已经努力解决多领域方法的挑战,例如在可持续性、城市和建筑科学领域,以及方法和工具的互操作性,但实际问题更加深刻,需要跨学科的知识交流,以发展充分的共享范例、概念、方法和工具。网络物理架构(CpA)第5期通过与涉及环境问题的一系列学科的专家合作,同时利用数据采集、数据共享和集成以及数据驱动建模,在一篇论述中确定更广泛的跨学科、多领域和多标量方法的模式,解决了这些挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interdisciplinary Data-integrated Approaches
Rapid urbanization with the associated land cover and land use change, as well as resource depletion, contribute to the degradation of ecosystems and biodiversity and have a negative impact on human health and well-being. Societal calls for responses and results pose a significant challenge for research and education in the various fields concerned with the environment. Alongside the current environmental crisis there is a pressing need for developing ‘green solutions’ for the built environment with the help of data-driven methods, workflows and tools. In view these developments, a shift from narrow disciplinary and domain-specific approaches towards broader interdisciplinary, multi-domain and multi-scalar strategies is required. This includes data-acquisition, data-sharing and data-integration, as well as data-driven modelling to enable the complexity of sustainability problems arising from rapid urbanization to be tackled. While there have been efforts to address the challenges of multi-domain approaches, for instance in the fields of sustainability, the urban and architectural sciences, as well as the interoperability of methods and tools, the actual problem goes deeper, requiring interdisciplinary knowledge exchange to develop adequate shared paradigms, concepts, methods and tools.  Cyber-physical Architecture (CpA) issue 5 addresses these challenges by engaging with experts from a range of disciplines involved in environmental concerns while utilizing data-acquisition, data-sharing and integration, and data-driven modelling in a discourse that identifies modalities for a broader interdisciplinary, multi-domain and multi-scalar approach.
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来源期刊
Spool
Spool Engineering-Architecture
CiteScore
0.40
自引率
0.00%
发文量
0
审稿时长
21 weeks
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