Big data applications in engineering and science

Ong, K; De Silva, D; Boo, YL; Lim, EH; Bodi, F; Alahakoon, D; Leao, S

Abstract

Research to solve engineering and science problems commonly require the collection and complex analysis of a vast amount of data. This makes them a natural exemplar of big data applications. For example, data from weather stations, high resolution images from CT scans, or data captured by astronomical instruments all easily showcase one or more big data characteristics, i.e., volume, velocity, variety and veracity. These big data characteristics present computational and analytical challenges that need to be overcame in order to deliver engineering solutions or make scientific discoveries. In this chapter, we catalogued engineering and science problems that carry a big data angle. We will also discuss the research advances for these problems and present a list of tools available to the practitioner. A number of big data application exemplars from the past works of the authors are discussed with further depth, highlighting the association of the specific problem and its big data characteristics. The overview from these various perspectives will provide the reader an up-to-date audit of big data developments in engineering and science.

Citation

Ong, K., De Silva, D., Boo, Y., Lim, E., Bodi, F., Alahakoon, D., & Leao, S. (2016). Big data applications in engineering and science. In Big Data Concepts, Theories, and Applications (315-351). Springer. https://doi.org/10.1007/978-3-319-27763-9_9

• Publication Date: Mar 4, 2016
• Deposit Date: Dec 16, 2016
• Publisher: Springer
• Pages: 315-351
• Book Title: Big Data Concepts, Theories, and Applications
• ISBN: 9783319277615
• DOI: https://doi.org/10.1007/978-3-319-27763-9_9
• Publisher URL: http://dx.doi.org/10.1007/978-3-319-27763-9_9