BigVis 2021 will devote a session to machine learning approaches in the context of Big data visualization and analytics.

Additionally, in the context of visual exploration and analytics, topics of interest include, but are not limited to:

  • Visualization, exploration & analytics techniques for various data types; e.g., stream, spatial, high-dimensional, graph
  • Human-in-the-loop processing
  • Human-centered databases
  • Data modeling, storage, indexing, caching, prefetching & query processing for interactive applications
  • Interactive & human-centered machine learning
  • Interactive data mining
  • User-oriented visualization; e.g., recommendation, assistance, personalization
  • Visualization & knowledge; e.g., storytelling
  • Progressive analytics
  • In-situ visual exploration & analytics
  • Novel interface & interaction paradigms
  • Visual representation techniques; e.g., aggregation, sampling, multi-level, filtering
  • Scalable visual operations; e.g., zooming, panning, linking, brushing
  • Scientific visualization; e.g., volume visualization
  • Analytics in the fields of scholarly data, digital libraries, multimedia, scientific data, social data, etc.
  • Immersive visualization
  • Interactive computer graphics
  • Setting-oriented visualization; e.g., display resolution/size, smart phones, visualization over networks
  • High performance, distributed & parallel techniques
  • Visualization hardware & acceleration techniques
  • Linked Data & ontologies visualization
  • Benchmarks for data visualization & analytics
  • Case & user studies
  • Systems & tools

  • BigVis 2021 invites submissions of novel research, completed or in-progress work, vision, and system papers. The page limit for regular and short research papers is 8 and 4 pages, respectively. Additionally, we welcome submission of work-in-progress as short paper of up to 4 pages long. Papers of this type describe an ongoing work that has not yet reached the maturity required for a research paper. Further, we solicit vision papers (up to 4 pages) that describe a vision for the future of the field of visual exploration and analytics. Finally, we accept system papers and demos up to 4 pages long.

    Papers must be original and not submitted or accepted for publication in any other workshop, conference or journal.

    Papers should be submitted electronically as PDF documents and be formatted according to the ACM Proceedings Format (Latex, MS Word). Submissions will be accepted only through the submission site EasyChair at All workshop papers will be indexed by DBLP and will be published online at CEUR (

    Submission: January 24 (AoE)
    Notification: February 16, 2021
    Camera-ready: February 25, 2021
    Workshop: March 23, 2021

    Authors of selected papers will be invited to submit extended versions of their work to Special Issue Machine Learning Approaches in Big Data Visualization of the IEEE Computer Graphics and Applications (CG&A) .

    BigVis 2020: "Interactive Big Data Visualization and Analytics", Big Data Research Journal, Elsevier, 2021.

    BigVis 2018: "Big Data Exploration, Visualization & Analytics", Big Data Research Journal, Elsevier, 2019.