Towards an Industry Data Gateway: An Integrated Platform for the Analysis of Wind Turbine Data

Aguilera, Alvaro; Grunzke, Richard; Markwardt, Ulf; Habich, Dirk; Schollbach, Dirk; Garcke, Jochen

doi:10.1109/iwsg.2015.8

Cited by 7 publications

(10 citation statements)

References 14 publications

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“…The first automatically built cluster comprises the seven use cases no. 2 [41], 3 [42], 5 [38], 6 [71], 8 [48], 37 [61] and 39 [63]. One particularity of the cases located in this cluster that was noticed at the very beginning of the examination and comparison, was the aim to improve already existing analysis processes.…”

Section: ) Description Of Clustermentioning

confidence: 95%

“…On the other side, the improvement of existing processes can be defined as achieving better quality of the performed analysis. This can be realized by using all of the available information, like unstructured medical and genome data on the way to personalized medicine [63], investigating the meaning of social media data to improve crisis mapping systems [41] or the broadening of the scope [61].…”

Section: ) Description Of Clustermentioning

confidence: 99%

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Identifying Similarities of Big Data Projects–A Use Case Driven Approach

et al. 2020

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Big data is considered as one of the most promising technological advancements in the last decades. Today it is used for a multitude of data intensive projects in various domains and also serves as the technical foundation for other recent trends in the computer science domain. However, the complexity of its implementation and utilization renders its adoption a sophisticated endeavor. For this reason, it is not surprising that potential users are often overwhelmed and tend to rely on existing guidelines and best practices to successfully realize and monitor their projects. A valuable source of knowledge are use case descriptions, of which a multitude exists, each of them with a varying information density. In this design science research endeavor, 43 use cases are identified by conducting a thorough literature review in combination with the application and adaption of a corresponding template for big data projects. By a subsequent categorization, which is performed by identifying and employing a hierarchical clustering algorithm, nine different standard use cases emerge, as the contribution's artifact. This provides decision-makers with an initial entry point, which can be utilized to shape their project ideas, not only by identifying the general meaningfulness of their potential big data project but also in terms of concrete implementation details.

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Section: ) Description Of Clustermentioning

confidence: 95%

Section: ) Description Of Clustermentioning

confidence: 99%

Identifying Similarities of Big Data Projects–A Use Case Driven Approach

et al. 2020

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“…Software, tools, and frameworks for faster simulation and optimization are also highly desired. Benefited from the advancement of data analytics techniques, several data-driven optimization algorithms are proposed for the design tasks for wind and hydro turbines [121][122][123][124]. Moreover, the development of computational infrastructures, such as HPC, enhances the evaluation efficiency for complex models from hardware-level [125,126].…”

Section: Energy Production Devicesmentioning

confidence: 99%

Enhancing Sustainability and Energy Efficiency in Smart Factories: A Review

et al. 2018

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With the rapid development of sensing, communication, computing technologies, and analytics techniques, today’s manufacturing is marching towards a new generation of sustainability, digitalization, and intelligence. Even though the significance of both sustainability and intelligence is well recognized by academia, industry, as well as governments, and substantial efforts are devoted to both areas, the intersection of the two has not been fully exploited. Conventionally, studies in sustainable manufacturing and smart manufacturing have different objectives and employ different tools. Nevertheless, in the design and implementation of smart factories, sustainability, and energy efficiency are supposed to be important goals. Moreover, big data based decision-making techniques that are developed and applied for smart manufacturing have great potential in promoting the sustainability of manufacturing. In this paper, the state-of-the-art of sustainable and smart manufacturing is first reviewed based on the PRISMA framework, with a focus on how they interact and benefit each other. Key problems in both fields are then identified and discussed. Specially, different technologies emerging in the 4th industrial revolution and their dedications on sustainability are discussed. In addition, the impacts of smart manufacturing technologies on sustainable energy industry are analyzed. Finally, opportunities and challenges in the intersection of the two are identified for future investigation. The scope examined in this paper will be interesting to researchers, engineers, business owners, and policymakers in the manufacturing community, and could serve as a fundamental guideline for future studies in these areas.

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“…VAVID [25] is a science gateway that is based on MoSGrid and tailored to use cases related to wind energy power stations and car crash simulations. In VAVID an integration with Unity is currently being developed to be used with a LDAP authentication source.…”

Section: Authentication and Securitymentioning

confidence: 99%