Key Dates and Deadlines

Given the special nature of the journal track, submitted papers have to adhere to the following eligibility criteria:

• Papers have to satisfy the high-quality criteria of journal papers and, at the same time, lend themselves to conference talks.
• Journal versions of previously published conference papers and survey papers will not be considered for the special issue.
• A paper rejected by the Machine Learning Journal should not be submitted to the Data Mining and Knowledge Discovery Journal and vice versa.
• Papers that do not fall into the eligible category may be rejected without formal reviews but can, of course, be resubmitted as regular papers to the Springer journals. Authors are encouraged to adhere to the best practices of Reproducible Research (RR), by making available data and software tools for reproducing the results reported in their papers. For the sake of persistence and proper authorship attribution, we require the use of standard repository hosting services, e.g. dataverse, mldata, openml, mloss, bitbucket, github for source code.

Authors who submit their work to the ECML PKDD 2025 journal track with these journals commit themselves to presenting their paper at the ECML PKDD conference if it is accepted.

The journal track allows continuous submissions from October 2024 to February 2025. Papers will be processed and sent out for review after each of the following three cutoff dates:

• October 11, 2024
• December 13, 2024
• February 14, 2025

The deadline on each of these dates is 23:59, Anywhere on Earth (AoE). We strive for a high-quality and efficient review process. For each submission, we aim to obtain three reviews from experienced reviewers, including members of the Guest Editorial Board. Our goal is to arrive at an initial decision about 10 weeks after each cutoff date, though meeting this target may not always be possible. After the initial review phase, many papers will require substantial revisions, and the revised paper will be re-reviewed, which extends the review process. Consequently, a paper’s chance of finishing the review cycle and being included in the ECML PKDD 2025 special issue decreases with each subsequent cutoff date. This means that accepted papers, especially those that were submitted to the later deadlines, may be included in the ECML PKDD 2026 (or even later) special issue (and subject to the approval of the ECML PKDD steering committee and future organizers). The reviewing process is single-blind.

To submit to this track, authors have to make a journal submission to the CMT site, as follows:

• Authors must submit their papers to the CMT submission site. They must submit the title and abstract, add the author names, choose the areas related to the paper, and indicate which of the two journals the paper is intended for.
• The full paper in pdf format, following the Springer templates, must also be submitted to the CMT system. All reviewing processes will take place using the CMT submission system. Please note that no paper can be submitted to both journals.

Templates can be found at https://www.springernature.com/gp/authors/campaigns/latex-author-support. It is highly recommended that submitted papers do not exceed 20 pages, including references. Every paper may be accompanied by unlimited appendices.

Both journals require authors to include an information sheet (for Machine learning submissions) or a cover letter (up to 2 pages) as supplementary material (for Data Mining and Knowledge Discovery submissions) that contains a short summary of their contribution and specifically addresses the following questions:

• What is the main claim of the paper? Why is this an important contribution to the machine learning/data mining research area?
• What is the evidence provided to support claims? Be precise.
• Report 3-5 most closely related contributions in the past 7 years (authored by researchers outside the authors’ research group) and briefly state the relation of the submission to them.
• Specify 5 general keywords and 5 specific keywords describing the main research activity presented in the manuscript.
• Declare any conflict of interest by reporting the email domains of all institutions with which the authors have an institutional conflict of interest. Authors have an institutional conflict of interest if they are currently employed or have been employed at this institution in the past three years, or if the authors have extensively collaborated with this institution within the past three years. Authors are also required to identify all Guest Editorial Board Members with whom the authors have a conflict of interest. Examples of conflicts of interest include co-authorship in the last five years, a colleague in the same institution within the last three years, and advisor/student relationships.
• Who are the most appropriate reviewers for the paper? Authors are required to suggest up to four candidate reviewers (especially if external to the Guest Editorial Board), including a brief motivation for each suggestion. Optionally, list up to four researchers/potential reviewers with competing interests that should not be considered for reviewers. For each cut-off date, there is paper bidding.

First Name Last Name Organization

• Alberto Fernandez Hilario University of Granada
• Albrecht Zimmermann Universit de Caen Normandie
• Amedeo Napoli LORIA, Nancy
• Amparo Alonso-Betanzos Universidade da Coruna
• Andre de Carvalho USP, Brazil
• Angelo Impedovo Niuma s.r.l.
• Annalisa Appice University of Bari Aldo Moro
• Antonio Salmeron Universidad de Almeria
• Barbara Catania University of Genoa
• Blaz Zupan University of Ljubljana
• César Ferri Universitat Politécnica Valéncia
• Corrado Loglisci Universita degli Studi di Bari 'Aldo Moro'
• De-Nian Yang Academia Sinica
• Destercke Sebastien UTC
• Dino Ienco INRAE
• Dragi Kocev Jo≈æef Stefan Institute
• Eirini Ntoutsi Bundeswehr University Munich
• Esther Galbrun University of Eastern Finland
• Esther-Lydia Silva-Ramirez Universidad de Cadiz
• Fabian Spaeh Boston University
• Felix Iglesias TU Wien
• Francesco Gullo University of L'Aquila
• Genoveva VARGAS-SOLAR CNRS LIRIS
• George Cavalcanti UFPE
• Georgiana Ifrim University College Dublin
• Germain Forestier University of Haute Alsace
• Giuseppe Manco ICAR-CNR, IT
• Giuseppina Andresini University of Bari Aldo Moro
• Hsuan-Tien Lin National Taiwan University
• Hui Chen Macquarie University
• Ioanna Miliou Stockholm University
• Isak Samsten Stockholm University
• Jan Ramon INRIA, FR
• Jaume Bacardit Newcastle University
• Jose Gamez Universidad de Castilla-La Mancha
• Kai Puolam√§ki University of Helsinki
• Lars Schmidt-Thieme University of Hildesheim
• Lia Morra Politecnico di Torino
• Linas Petkevicius VIlnius University
• Loic Cerf UFMG
• Mahito Sugiyama National Institute of Informatics
• Marc Plantevit EPITA, France
• Maria Bampa Stockholm University
• Marie Anastacio Leiden Institute of Advanced Computer Science, Leiden University
• Mario Antunes Universidade de Aveiro
• Martin Holena Institute of Computer Science
• Matteo Riondato Amherst College
• Matthias Jakobs TU Dortmund University
• Michelangelo Ceci University of Bari
• Mitra Baratchi LIACS - University of Leiden
• Myra Spiliopoulou Otto-von-Guericke-University Magdeburg
• Nikolaj Tatti Helsinki University
• Nuno Moniz University of Notre Dame
• Panagiotis Karras University of Copenhagen
• Panagiotis Papapetrou Stockholm University
• Paolo Garza Politecnico di Torino
• Pascal Welke TU Wien
• Pedro Larranaga Technical University of Madrid
• Pedro Pereira Rodrigues University of Porto
• Qi Zhang University of Technology Sydney
• Ricardo Prudencio Universidade Federal de Pernambuco
• Riccardo Guidotti University of Pisa
• Richard Allmendinger University of Manchester
• Rita Ribeiro INESC TEC
• Ruggero Pensa University of Turin
• Salvador Garcia Universidad de Granada
• Sepideh Pashami Halmstad University
• Shinichi Shirakawa Yokohama National University
• Shridhar Devamane KLEIT,HUBBALLI
• Slawomir Nowaczyk Halmstad University
• Szymon Jaroszewicz Polish Academy of Sciences
• Szymon Bobek Jagiellonian University
• Thien Le MIT
• Thomas Dyhre Nielsen Aalborg University
• Vicente Garcia Jimenez Universidad Autónoma de Ciudad Ju√°rez
• Vincenzo Pasquadibisceglie University of Bari Aldo Moro
• Wagner Meira Jr. UFMG
• Ye Zhu Deakin University
• zhangkai wu University of Technology Sydney