In this era of big data, with the enrichment of data collection and description measures, a wide array of data in various formats or modalities, called multimodal data, can be collected far more easily than ever before. It is important to discover the features and knowledge hidden in the data through comprehensive understanding and scientific programming, which can provide benefits across many different applications, from scientific and engineering computing to intelligent decisions and predictive services.

Regarding multimodal data, different modalities represent data samples from different perspectives, which usually provide complementary information to each other, and exploiting complementary characteristics can lead to a more comprehensive description of data samples. However, integrating knowledge across modalities and thereby unlocking the huge value of the data is still a significant problem in big data research, and this is the major difference between learning tasks in big data and traditional data. Scientific programming will play a significant role in providing solutions and mechanisms to issues surrounding multimodal big data, such as optimising the processing of large volumes or high dimensions of low-quality multimodal data and accelerating the analysis of real-time multimodal data, as well as integrating and fusing the features of heterogeneous multimodal data.

Therefore, the aim of this Special Issue is to attract high-quality papers from academics and industry researchers in big data and data fusion, and to present the most recent advanced methods and applications for realising the effective fusion of multimodal big data through scientific programming. We welcome both original research and review articles.

Potential topics include but are not limited to the following:

• Scientific programming methods and tools for multimodal data
• Multimodal data fusion and analysis
• Multimodal feature learning
• Low-quality multimodal data fusion
• Incremental/online multimodal data fusion
• Domain adaption for multimodal data
• Multimodal data programming and industry applications
• Multimodal data programming in other fields