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Visual analytics of cellular signaling data

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Abstract

Cellular signaling data is a type of traffic data, which contains rich spatio-temporal information. Rather than studying the trajectories of individuals, we propose a visual analytics methodology to analyze the crowd flows among a geographical network extracted from real-time cellular signaling data. We design a suite of visualization techniques to explore and reveal mobility patterns over the networks of spatiotemporal clustering. The feasibility of our approach was verified on a real real-time cellular signaling dataset in one week.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China(No.61320106006, No.61532006, No.61877002) and the Beijing Municipal Natural Science Foundation (No.4162019).

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Authors and Affiliations

  1. School of Computer and Information Engineering, Beijing Technology and Business University, Beijing, 100048, China

    Haisheng Li, Yang Wei, Yuanjie Huang & Qiang Cai

  2. National Engineering Laboratory for Agri-product Quality Traceability, Beijing, 100048, China

    Haisheng Li, Yang Wei, Yuanjie Huang & Qiang Cai

  3. Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing, 100048, China

    Haisheng Li, Yang Wei, Yuanjie Huang & Qiang Cai

  4. School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Junping Du

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  1. Haisheng Li
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  2. Yang Wei
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  3. Yuanjie Huang
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  4. Qiang Cai
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  5. Junping Du
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Correspondence to Haisheng Li.

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Li, H., Wei, Y., Huang, Y. et al. Visual analytics of cellular signaling data. Multimed Tools Appl 78, 29447–29461 (2019). https://doi.org/10.1007/s11042-018-6966-5

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