Welcome to CDF4MD at MDM 2024
Mobile data management deals with diverse data coming from dynamic and potentially
heterogeneous data sources. Mobile systems produce myriads of data,
including such of different modalities, types, or at different processing stages,
summarised by the term domain. With emerging modern technologies, such as
Internet-of-Things, these systems and their data get more complex with each
day to come. State-of-the-Art (SOTA) methods typically only allow to analyze
data sets within a single domain. We are missing data analysis techniques that
are designed for fusing multiple pieces from different (scientific) domains in order
to gain a more holistic knowledge of complex systems. It is imperative that
such explorative data analysis methods are developed to enable domain experts
to effectively leverage this holistic knowledge.
This workshop introduces cross-domain fusion (CDF) as an emerging
topic to mobile data management. CDF involves identifying patterns,
trends, and anomalies in spatio-temporal data, including sensor measurements,
satellite imagery, or data generated by scientific models with spatio-temporal
context. This offers insights into the underlying processes and mechanisms governing
the system under investigation. CDF addresses the key aspects of fusing
multiple views from different domains using exploratory data analysis to identify
patterns, trends, and anomalies among arbitrary views enabling, for instance, the construction
of spatio-temporal digital twin worlds.