Statistics and Data Science
Statistics and Data Science. 2025; 1: (1) ; 10.12208/j.sds.20250002 .
总浏览量: 849
Faculty of Creative Industries, City University, Kuala Lumpur, Malaysia
*通讯作者: Yingquan Wang,单位:Faculty of Creative Industries, City University, Kuala Lumpur, Malaysia;
本文深入探讨了大数据信息界面的发展历程及特点。首先介绍了大数据信息界面的起源,强调其与大数据技术兴起的密切关联。其次,探讨了大数据信息界面的呈现形式,强调了数据可视化是实现大数据直观呈现的关键手段,该技术通过编码和解码两个阶段实现。最后,本文深入分析了大数据信息界面的数据规模庞大、数据类型多样、数据关系复杂、数据反馈实时性强等特点。通过对比传统信息界面与大数据信息界面,强调了大数据信息界面在应对海量、多样、复杂、实时数据挑战方面的优势和必要性。大数据信息界面的发展不仅是技术创新的产物,更是对用户体验和信息传达有效性的深思熟虑。
This paper delves into the development and features of big data information interfaces. It introduces the origin of big data information interfaces, emphasizing their close correlation with the rise of big data technology. The paper explores the presentation forms of big data information interfaces, emphasizing data visualization as a key method achieved through encoding and decoding stages to offer an intuitive representation of big data. Furthermore, it conducts an in-depth analysis of the characteristics of big data information interfaces, including the enormity of data scale, diversity of data types, complexity of data relationships, and real-time data feedback. By comparing traditional information interfaces with big data information interfaces, the paper highlights the advantages and necessity of the latter when facing challenges related to vast, diverse, complex, and real-time data. The development of big data information interfaces is not only a result of technological innovation but also a profound consideration of user experience and information communication effectiveness.
[1] Jia, Q., Chai, C., & Cai, R. (2022). A Comprehensive Review of Aesthetic Design in Data Visualization. Packaging Engineering, 43(20), 24-28.
[2] Liu, B., Liu, Z., Liu, Y., & Li, Z. (2021). A Comprehensive Review of Data Visualization Research. Journal of Hebei University of Science and Technology, 42(06), 09-14.
[3] Wang, N., & Qiu, X. (2021). Simulation of UI Interface Data Visualization Transmission Based on Perceptual Feedback. Computer Simulation, 38(10), 34-36.
[4] Huo, C., & Lu, X. (2021). Advancements and Prospects in Research on Data Visualization Literacy. Journal of Library Science in China, 47(02), 16-20.
[5] Gan, L. (2020). Symbolic Communication of “Graphs” and “Numbers”—A Rhetorical Analysis Based on Data Visualization Charts. Dongyue Tribune, 41(02), 35-37.
[6] Du, H., & Jiang, J. (2022). Information Visualization Design under Cognitive and Visual Thinking. Packaging Engineering, 43(08), 15-18.
[7] Liu, F. (2018). Data Visualization and Information Charts: Communication Design in the Information Age. Art Panorama, 05, 33-36.