Big data analysis and optimization and platform components

Hsu, Kenglung

doi:10.1016/j.jksus.2022.101945

Cited by 7 publications

(3 citation statements)

References 19 publications

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“…Big data refers to large growing datasets that include heterogeneous formats: structured, unstructured, and semistructured data [91]. Despite the ubiquity of big data in research entities, there is currently no consensus on what amount of data can be called big data [92]- [94]. To date, due to the development and adaption of advanced technologies, industries are facing challenges when handling the increasing data, such as collecting, integrating, storing, and information sharing.…”

Section: Data Management and Data Analyticsmentioning

confidence: 99%

“…According to recent research, the application of big data is mainly summarised as three parts: data collection, data structuring, and knowledge extraction, as shown in Figure 2. To fine the procedure, data management emerges as a critical role, which aims to facilitate data analytics and complex multidimensional data visualisation [19], [94]- [96]. For example, lots of geological surveys have more than two dimensions which poses challenge on data analytics and visualisation [97]- [100].…”

Section: Data Management and Data Analyticsmentioning

confidence: 99%

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Exploring the Fusion Potentials of Data Visualization and Data Analytics in the Process of Mining Digitalization

et al. 2023

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Mining digitalisation have been receiving significant attention due to the utilisation of advanced technologies, such as IoT, automation, and sensing. However, maximising the potential value of collected data in the mining industry remains a challenge. Therefore, this paper aims to review timely concern topics to facilitate the fusion implementation in mining engineering. Specifically, this review covers recent popular topics, such as, data visualisation, data management, data analytics, data fusion, visual analytics, and mining digital twin construction. In this paper, we aim to draw a comprehensive picture about the fusion of data visualisation and analytics in the big data context, by examining the recent academic research related to these topics. Therefore, this paper reviews the visualisation domain by conventional classification, including scientific visualisation, information visualisation, and visual analytics, associated with the analysis of current digital twin development. Next, according to the challenges and issues related to visualisation development, this paper reviews the data management and data analytics domains as well. Incorporating with the fusion concept, machine learning-oriented fusion applications and potential scenarios in the mining industry have been discussed. In addition, based on the observation across various domains, this paper presents challenges and future potentials of data fusion in mining.INDEX TERMS mining digitalisation, data management, data analytics, data visualisation, and data fusion I. INTRODUCTION

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Section: Data Management and Data Analyticsmentioning

confidence: 99%

Section: Data Management and Data Analyticsmentioning

confidence: 99%

Exploring the Fusion Potentials of Data Visualization and Data Analytics in the Process of Mining Digitalization

et al. 2023

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“…Cai et al (2019) emphasize the problems related to data collection, storage and analysis queries. Kenglung H. (2022) prioritizes the access to reliable information in time of Big Data collection and analysis.…”

Section: Variety Indicates Different Forms Of Datamentioning

confidence: 99%

Using Big Data by Ukrainian official statistics when martial law applies: problems and solutions

Osaulenko¹,

Horobets²

2023

SiTns

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The article is focused on issues of the secure operation of official statistics in Ukraine during the application of martial law. It was found that the gaps in conventional sources of statistical data caused by the war needed to be filled with data from alternative sources, including Big Data. The level of digitalisation in Ukraine as the basis for using Big Data was analysed by the proposed indices of internetisation, social progress and digital transformation. Thanks to our research, several problems (methodological, legal, financial, and managerial) were identified as vital for statistical offices on their way to the implementation of Big Data in statistical processes. Our proposals concern tools for Big Data processing, such as Data Hypercube as a way for presenting Big Data for their visualisation, applications of Web scraping in estimating the consumer prices index, analyses of labour and real estate markets, and the applications of specialised software for the collection, processing and analysis of Big Data sets.

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Research on Intelligent Optimization Decision Support Platform of Solid Waste Environmental Risk Event Disposal Technology Under the Background of Big Data

Zhao

Guan

Tao

et al. 2022

2022 International Conference on Cloud Computing, Big Data and Internet of Things (3CBIT)

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Big data analysis and optimization and platform components

Cited by 7 publications

References 19 publications

Exploring the Fusion Potentials of Data Visualization and Data Analytics in the Process of Mining Digitalization

Exploring the Fusion Potentials of Data Visualization and Data Analytics in the Process of Mining Digitalization

Using Big Data by Ukrainian official statistics when martial law applies: problems and solutions

Research on Intelligent Optimization Decision Support Platform of Solid Waste Environmental Risk Event Disposal Technology Under the Background of Big Data

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