Big Data and Cloud Computing

Abstract

Big data emerged as a new paradigm to provide unprecedented content and value for Digital Earth. Big Earth data are increasing tremendously with growing heterogeneity, posing grand challenges for the data management lifecycle of storage, processing, analytics, visualization, sharing, and applications. During the same time frame, cloud computing emerged to provide crucial computing support to address these challenges. This chapter introduces Digital Earth data sources, analytical methods, and architecture for data analysis and describes how cloud computing supports big data processing in the context of Digital Earth. Keywords Geoscience • Spatial data infrastructure • Digital transformation • Big data architecture 9.1 Introduction Digital Earth refers to the virtual representation of the Earth we live in. It represents the Earth in the digital world from data to model. Data are collected and models are abstracted to build the digital reality. Massive amounts of data are generated from various sensors deployed to observe our home planet while building Digital Earth. The term "big data" was first presented by NASA researchers to describe the massive amount of information that exceeds the capacities of main memory, local disk, and even remote disk (Friedman 2012). According to the National Institute of Standards and Technology (NIST), "Big Data is a term used to describe the large amount of data in the networked, digitized, sensor-laden, information-driven world" (Chang and Grady 2015). This definition refers to the bounty of digital data from various data sources in the context of Digital Earth, which focus on big data's geographical aspects of social information, Earth observation (EO), sensor observation service (SOS), cyber infrastructure (CI), social media and business information (Guo 2017; Guo et al. 2017; Yang et al. 2017a, b). Digital Earth data are collected from satellites,

Application of Big Data Analytics for Improving Learning Process in Technical Vocational Education and Training

“…Furthermore, the result also revealed that big data help in teaching strategy analysis. This agrees with [9] that the ultimate goal of using big data in education is to help educators formulate teaching strategies and analyze the collected information of learners to explore the functions of various components of the learning system and to analyze learner learning outcomes and teaching strategies. Addendum, [18] also corroborated that the prospects of big data are to analyze and summarize the teaching strategies to provide more effective teaching strategies in the field of education.…”

“…Lots of educational institutions have shown that analytics can facilitate student achievement, finance, interest as well as appropriate resource distribution and utilization [11]. [9] state that analytics is used in the planning, staffing, administration, supervision and financial plan. The prospective advantage of analytics in education is to estimate the expenditure to complete a programme (such as diploma and degree); school undertakings that have not been recognized as well as resource optimization.…”

“…Big Data Analytics is the way of developing actionable insights through problem characterization and the use of statistical models and investigation alongside virtual upcoming and/or existing data. When taking into account analytics in the field of education, it is helpful to reflect on how these techniques are applied in the framework of the institution [9]. Furthermore, other common techniques of analytics in the field of education are learning and academic analytics [10].…”

“…These learning materials generate a gigantic number of unused data that are shattered as conventional learning methods are not capable of processing them [8]. This has resulted in the penetration of Big Data analytics into education to process a large amount of data involved to measure the understanding, personalize the learning experience and facilitate to design new interesting courses [9]. It is against this background that this study looks into the recent applications of Big Data analytics for improving the learning process: Problems and Prospects for its application in TVET.…”

Spatiotemporal data mining: a survey on challenges and open problems

“…However, distributed frameworks suffer from many limitations in terms of data sharing, processing scalability, and interactive performance Li et al. ( 2020 ). Besides, existing cloud solutions have limited support to the visualisation of the GIS big data Wang et al.…”