15 years of Big Data: a systematic literature review

IF 8.6 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Davide Tosi, Redon Kokaj, Marco Roccetti
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Abstract

Big Data is still gaining attention as a fundamental building block of the Artificial Intelligence and Machine Learning world. Therefore, a lot of effort has been pushed into Big Data research in the last 15 years. The objective of this Systematic Literature Review is to summarize the current state of the art of the previous 15 years of research about Big Data by providing answers to a set of research questions related to the main application domains for Big Data analytics; the significant challenges and limitations researchers have encountered in Big Data analysis, and emerging research trends and future directions in Big Data. The review follows a predefined procedure that automatically searches five well-known digital libraries. After applying the selection criteria to the results, 189 primary studies were identified as relevant, of which 32 were Systematic Literature Reviews. Required information was extracted from the 32 studies and summarized. Our Systematic Literature Review sketched the picture of 15 years of research in Big Data, identifying application domains, challenges, and future directions in this research field. We believe that a substantial amount of work remains to be done to align and seamlessly integrate Big Data into data-driven advanced software solutions of the future.

Abstract Image

大数据 15 年:系统文献综述
大数据作为人工智能和机器学习领域的基本构件,仍然受到越来越多的关注。因此,在过去的 15 年中,人们在大数据研究方面投入了大量精力。本系统性文献综述的目的是总结过去 15 年有关大数据的研究现状,回答一系列研究问题,这些问题涉及大数据分析的主要应用领域、研究人员在大数据分析中遇到的重大挑战和限制,以及大数据的新兴研究趋势和未来方向。综述按照预定程序自动搜索了五个著名的数字图书馆。在对结果应用选择标准后,确定了 189 项相关的主要研究,其中 32 项为系统文献综述。我们从这 32 项研究中提取了所需的信息并进行了总结。我们的系统文献综述勾勒出大数据 15 年来的研究图景,确定了这一研究领域的应用领域、挑战和未来方向。我们认为,要将大数据与数据驱动的未来先进软件解决方案进行协调和无缝集成,仍有大量工作要做。
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来源期刊
Journal of Big Data
Journal of Big Data Computer Science-Information Systems
CiteScore
17.80
自引率
3.70%
发文量
105
审稿时长
13 weeks
期刊介绍: The Journal of Big Data publishes high-quality, scholarly research papers, methodologies, and case studies covering a broad spectrum of topics, from big data analytics to data-intensive computing and all applications of big data research. It addresses challenges facing big data today and in the future, including data capture and storage, search, sharing, analytics, technologies, visualization, architectures, data mining, machine learning, cloud computing, distributed systems, and scalable storage. The journal serves as a seminal source of innovative material for academic researchers and practitioners alike.
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