Open Science In Engineering


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Opening Science


Opening Science

Author: Sönke Bartling

language: en

Publisher: Springer

Release Date: 2013-12-16


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Modern information and communication technologies, together with a cultural upheaval within the research community, have profoundly changed research in nearly every aspect. Ranging from sharing and discussing ideas in social networks for scientists to new collaborative environments and novel publication formats, knowledge creation and dissemination as we know it is experiencing a vigorous shift towards increased transparency, collaboration and accessibility. Many assume that research workflows will change more in the next 20 years than they have in the last 200. This book provides researchers, decision makers, and other scientific stakeholders with a snapshot of the basics, the tools, and the underlying visions that drive the current scientific (r)evolution, often called ‘Open Science.’

Open Science in Engineering


Open Science in Engineering

Author: Michael E. Auer

language: en

Publisher: Springer Nature

Release Date: 2023-12-31


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The REV Conference is the annual conference of the International Association of Online Engineering (IAOE) together with the Global Online Laboratory Consortium (GOLC). REV 2023 is the 20th in a series of annual events concerning the area of online engineering, cyber-physical systems and Internet of things, including remote engineering and virtual instrumentation. In a globally connected world, the interest in online collaboration, teleworking, remote services, and other digital working environments is rapidly increasing. In response to that, the general objective of this conference is to contribute and discuss fundamentals, applications, and experiences in the field of online and remote engineering, virtual instrumentation, and other related new technologies, including: Cross-reality Open Science Internet of Things and Industrial Internet of Things Industry 4.0 Cyber-security M2M and smart objects.

Data-Driven Science and Engineering


Data-Driven Science and Engineering

Author: Steven L. Brunton

language: en

Publisher: Cambridge University Press

Release Date: 2022-05-05


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A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.