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.

Call for Papers

We invite papers discussing novel research and ideas without substantial overlap with papers that have been published or submitted to a journal or a conference with proceedings. Submitted papers must be maximum 6 pages long (including all figures, tables, and references) and should report original research results or significant case studies. Submissions should be formatted using the MDM 2024 camera-ready template. If accepted, at least one of the authors must attend the workshop to present the work. All accepted papers will be published in the proceedings of the 2024 International Conference on Mobile Data Management and included in the IEEE Xplore® digital library.

Submissions discussing the following topics will be considered:

  • Fusion and analysis methods for multimodal data
  • Fusion and analysis methods for multiformat data
  • Distributed and parallel cross domain fusion
  • Fusion of raw data with data models
  • Online (Edge/Fog/Cloud) processing of multisource data
  • Resource-limited processing of multisource data
  • Domain fusion in distributed and parallel data collections
  • Applications of cross domain fusion
  • Methods for combining data with background knowledge
All abstracts and papers must be submitted using the following link:

Important Dates (23:59 AoE)

  • Paper Submission

    Authors submit papers until
    April 12, 2024
    April 19, 2024

  • Acceptance Notice

    Authors will be notified until
    May 3, 2024
    May 7, 2024

  • Camera-Ready

    Deadline for camera-ready submissions
    May 15, 2024

Organizers

  • Matthias Renz

    Dept. of Computer Science
    Kiel University

  • Peer Kröger

    Dept. of Computer Science
    Kiel University

  • Nikos Mamoulis

    Dept. of Computer Science & Engineering
    University of Ioannina

  • Nelson Tavares de Sousa

    Dept. of Computer Science
    Kiel University

  • Yannick Wölker

    Dept. of Computer Science
    Kiel University

Program Committee

  • Amr Magdy (University of California Riverside)
  • Daniyal Kazempour (CAU Kiel)
  • Demetrios Zeinalipour-Yazti (University of Cyprus)
  • Dimitrios Skoutas (Athena Research Center)
  • Dimitris Papadias (HKUST)
  • Dimitris Sacharidis (ULB)
  • Goce Trajcevski (Iowa State University)
  • Martin Werner (TU München)
  • Matthias Schubert (Ludwig-Maximilians-Universität München)
  • Panagiotis Bouros (Johannes Gutenberg University Mainz)
  • Raymond Chi-Wing Wong (The Hong Kong University of Science and Technology)
  • Reynold Cheng (The University of Hong Kong, China)
  • Sanjay Kumar Madria (Missouri University of Science & Technology, USA)
  • Theodoros Chondrogiannis (University of Konstanz)
  • Yannis Theodoridis (University of Piraeus)
  • Yaron Kanza (AT&T Labs-Research)