The rapid proliferation of tracking sensors—ranging from vessel and vehicle tracking systems to smartwatches, cameras, and Earth observation sensors—has led to an unprecedented influx of high-frequency, high-volume data. Yet, despite this abundance, many trajectories remain incomplete, contain errors, or are entirely missing. A vast reservoir of tracking data remains unexplored or underutilized, holding valuable insights that could enhance monitoring and decision-making. The MMDEC dataset aims to serve as a resource for both teaching and the research community, and is specifically designed to support advanced maritime trajectory analysis and inference. Its core contribution lies in the explicit integration of SAR-based, AI-driven ship detections and attribute estimates with AIS vessel reports and multiple contextual data layers, enabling direct comparison between transmitted vessel positions and independently observed radar targets. MMDEC aggregates and harmonizes multi-source data including AIS streams, satellite imagery, meteorological and oceanographic fields, port locations, and sea state and marine protected area boundaries over western Celtic Sea, the English Channel, and part of the North Sea. The dataset covers a continuous three-month period from 1 July to 30 September 2023. Its multimodal content and explicit spatial–temporal alignment provide a multi-sensor benchmark for evaluating algorithms designed to enhance, validate, or infer maritime trajectories from heterogeneous observational sources.
Averty et al. (Sun,) studied this question.