Information Visualization has been one of the cornerstones of Data Science, turning the abundance of Big Data being produced through modern systems into actionable knowledge. Indeed, the Big Data era has realized the availability of voluminous datasets that are dynamic, multidimensional, noisy and heterogeneous in nature. Transforming a data-curious user into someone who can access and analyze that data is even more burdensome now for a great number of users with little or no support and expertise on the data processing part.

In this context, several traditional problems from Data Management & Mining, Information Visualization, and Human-computer Interaction communities, such as efficient data storage, querying, and indexing to enable visual analytics, as well as new ways and AI techniques for visual presentation of massive data, need to be revisited. For instance, techniques that provide mechanisms for information abstraction, prefetching, sampling, progressive data visualization, and summarization to address problems related to visual information overplotting. Furthermore, it is essential to develop new methods that enhance user comprehension by providing customization options tailored to various user-defined exploration scenarios and preferences.

The Big Data Visual Exploration and Analytics workshop (BigVis) aims at addressing the above challenges and issues by providing a forum for researchers and practitioners to discuss, exchange, and disseminate their work. BigVis attempts to attract attention from the research areas of: Data Management & Mining, Information Visualization, Human-Computer Interaction, Machine Learning, and Computer Graphics, and highlight novel works that bridge together these communities.

The BigVis 2024 held in conjunction with the 50th International Conference on Very Large Databases (VLDB 2024), Guangzhou, China.