One Tutorial about MTS heterogeneity has been Accepted by SSTD 2025！
Our Tutorial MTS heterogeneity and Adaptive Modeling, entitled “Heterogeneity in Multivariate Time Series: Comprehensive Analysis and Adaptive Modeling”, has been accepted by The 19th International Symposium on Spatial and Temporal Data (SSTD).
Introduction
Multivariate time series (MTS) data are ubiquitous in complex dynamic systems such as meteorology, transportation, and energy.However, data heterogeneity caused by cross-domain variations has become a central bottleneck restricting model generalization and consistency in comparative studies. This paper systematically reviews recent MTS forecasting research, revealing that inconsistencies in experimental conclusions primarily arise from neglecting substantial differences in data distributions and characteristics. To address this issue, we introduce BasicTS, an fair and scalable benchmark designed to fairly quantify the impact of heterogeneity on model performance. Subsequently, to tackle generalization challenges posed by heterogeneity, this tutorial proposes two adaptive solutions: (i) developing BLAST, a balanced and diversity-enhanced pre-training corpus that explicitly models heterogeneity, significantly improving zero-shot general forecasting; and (ii) introducing ARIES, a relational assessment and model recommendation framework that leverages a statistical pattern-to-model matching mechanism to automatically select optimal forecasting models for specific real-world sequences. Through comprehensive experiments and case studies, we demonstrate that precisely characterizing and leveraging data heterogeneity, beyond mere model design, is crucial for improving the robustness of MTS forecasting. This research provides methodological guidance and practical insights for academia and industry to fully exploit the value of time series data and make data-driven decisions.
About SSTD
The International Symposium on Spatial and Temporal Data (SSTD) has a long and distinguished history as a premier forum for researchers, practitioners, and industry leaders to present and discuss spatial and temporal data management innovations. Since its inception in 1989, SSTD has been at the forefront of advancing foundational theories, systems, and applications that address the challenges of handling spatial and temporal information. Over the years, the symposium has played a pivotal role in fostering research that has shaped the evolution of spatial databases, geospatial computing, and spatio-temporal analytics. The 19th edition of SSTD continues this tradition while broadening its focus to explore the full lifecycle of spatial and temporal data, reflecting the growing importance of these data types in an era of big data, AI, and ubiquitous computing.
All accepted papers will be published in the SSTD 2025 proceedings by ACM.