Welcome to the 2nd Multi-Source Data Mining Workshop Website

About the workshop

The generalization of digital technology has generated a huge amount of data, collected from various sources, and that can be spread out in different places.

Mining multiple sources of data to discover useful information is of critical importance for decision making. Indeed, these data sources can represent several dimensions or points of view about a phenomenon. However, how to efficiently mine quality information from multiple data sources is still a challenging task for current research, as in real world applications, data stored in multiple places by different, owned by different stakeholder, often conflict: data name, format, value or point of view may be different. Furthermore, data can be heterogeneous in their structure, sequential or not, …

The main objective of the 2nd International Workshop on Multi-Source Data Mining (MSDM)  is to discuss promising and recent research, applicative problems and results behind current multi data source mining.

The success of the 1st edition of the Workshop has confirmed our wish to propose a 2nd edition. We thus invite you to participate in the 2nd  edition of the International Workshop on Multi-Source Data Mining (MSDM), to be held during the IEEE International Conference on Data Mining – ICDM (https://icdm2021.auckland.ac.nz), 2021 in Auckland, New Zealand.

The workshop’s aim is to contribute to bringing together approaches defined or used, when data sources are multiple, possibly heterogeneous, represent multiple points of view, are possibly linked, even through time, including from the applicative point of view.

Topics of interest

We welcome contributions of researchers and practitioners that address (but are not limited to) the following topics of interest: 
  • Algorithms and models for multi-source data mining
  • Multi-relational data mining
  • Heterogeneous data mining (including graph, structured/semi-structured data, text, spatio-temporal, time-series, streaming data)
  • Multi-dimensional data mining
  • Redescription mining
  • Temporal multi-source mining
  • Big data mining
  • Practical applications of multi source data mining, including recommender systems.

Preliminary works and results are welcome, as well as position papers.


Authors are encouraged to send their contribution, in line with the  ICDM submissions, max 8 pages plus 2 extra pages in the IEEE 2-column format, including the bibliography and any possible appendices..

As in last years, papers that are not accepted by the main conference will be automatically sent to a workshop selected by the authors when the papers were submitted to the main conference.

Submissions longer than 10 pages will be rejected without review. All submissions will be peer reviewed by the Workshop Program Committee on the basis of technical quality, relevance to scope of the workshop, originality, significance, and clarity.

For paper submission, please proceed to the submission website.

Important dates

  • September 3, 2021: Workshop papers submission
  • September 24, 2021: Notification of workshop papers acceptance to authors
  • October 1, 2021: Camera-ready deadline and copyright form
  • December 7, 2021: Workshops date


Armelle Brun, LORIA – Université de Lorraine, France

Program committee

Armelle Brun, LORIA – Université de Lorraine, France

Agathe Merceron, Beuth University of Applied Sciences, Berlin, Germany

Anne Boyer, LORIA – Université de Lorraine, France

Aysegul Yildiz Ulus, University of Galatasaray, Turkey

Cyril De Runz, LIFAT, Université de Tours, France

Esther Galbrun, School of Computing, University of Eastern Finland, Finland

Julie Budaher, Université Toulouse, France

Nicolas Lachiche, Université de Strasbourg, France

Sandra Bringay, LIRMM, Université de Montpellier, France

Shengrui Wang, Université de Sherbrooke, Canada

Yannick Toussaint, LORIA, Université de Lorraine, France

Contact information

Please send enquiries to brun at loria dot fr

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