Advances in data gathering, storage, and distribution have created a need for computational tools and techniques to aid in data analysis. Data Mining and Knowledge Discovery in Databases (KDD) is a rapidly growing area of research and application that builds on techniques and theories from many fields, including statistics, databases, pattern recognition and learning, data visualization, uncertainty modelling, data warehousing and OLAP, optimization, and high performance computing.

KDD is concerned with issues of scalability, the multi-step knowledge discovery process for extracting useful patterns and models from raw data stores (including data cleaning and noise modelling), and issues of making discovered patterns understandable. 

Data Mining and Knowledge Discovery is the premier technical publication in the field, providing a resource collecting relevant common methods and techniques and a forum for unifying the diverse constituent research communities. The journal publishes original technical papers in both the research and practice of DMKD, surveys and tutorials of important areas and techniques, and detailed descriptions of significant applications. Short (2-4 pages) application summaries are published in a special section. 

The journal accepts paper submissions of any work relevant to DMKD. A summary of the scope of Data Mining and Knowledge Discovery includes:

Theory and Foundational Issues: Data and knowledge representation; modelling of structured, textual, and multimedia data; uncertainty management; metrics of interestingness and utility of discovered knowledge; algorithmic complexity, efficiency, and scalability issues in data mining; statistics over massive data sets. 

Data Mining Methods: including classification, clustering, probabilistic modelling, prediction and estimation, dependency analysis, search, and optimization. 

Algorithms for data mining including spatial, textual, and multimedia data (e.g., the Web), scalability to large databases, parallel and distributed data mining techniques, and automated discovery agents. 

Knowledge Discovery Process: Data pre-processing for data mining, including data cleaning, selection, efficient sampling, and data reduction methods; evaluating, consolidating, and explaining discovered knowledge; data and knowledge visualization; interactive data exploration and discovery. 

Application Issues: Application case studies; data mining systems and tools; details of successes and failures of KDD; resource/knowledge discovery on the Web; privacy and security issues.

Editor in Chief
Johannes Fürnkranz, TU Darmstadt, Germany 

Advisory Board 
Rakesh Agrawal, Microsoft Search Labs, USA 
Christos Faloutsos, Carnegie Mellon University, USA 
Usama Fayyad, Yahoo, Inc., USA
Heikki Mannila, Helsinki University of Technology, Finland 
Raghu Ramakrishnan, Yahoo! Research, USA 
Padhraic Smyth, University of California, Irvine, USA 
Geoff Webb, Monash University, Australia 

Action Editors 
Charu Aggarwal, IBM T.J. Watson Research Center, USA 
Pierre Baldi, University of California, Irvine, USA 
Albert Bifet, LTCI, Télécom ParisTech, Université Paris-Saclay, France 
Hendrik Blockeel, Katholieke Universiteit Leuven, Belgium 
Toon Calders, Université Libre de Bruxelles, Belgium 
Ian Davidson, University of California at Davis, USA 
Aristides Gionis, Aalto University, Finland 
Bart Goethals, University of Antwerp, Belgium 
Shuiwang Ji, Texas A&M University, USA
George Karypis, University of Minnesota, USA 
Eamonn Keogh, University of California, Riverside, USA 
Kristian Kersting, TU Darmstadt, Germany 
Donato Malerba, Università degli Studi di Bari Aldo Moro, Italy 
Pauli Miettinen, University of Eastern Finland, Finland
Evangelos E. Papalexakis, University of California Riverside, USA 
Panagiotis Papapetrou, Stockholm University, Sweden 
Srinivasan Parthasarathy, Ohio State University, USA 
Myra Spiliopoulou, Otto-von-Guericke University Magdeburg, Germany 
Hanghang Tong, Arizona State University, USA 
Grigorios Tsoumakas, University Thessaloniki, Greece
Fei Wang, Cornell University, USA 
Mohammed J. Zaki, Rensselaer Polytechnic Institute, USA 
Indrė Žliobaitė, University of Helsinki, Finland

Editorial Board 
Annalisa Appice, University of Bari, Italy
Anthony Bagnall,University of East Anglia, UK 
Bettina Berendt,KU Leuven, Belgium 
Michael R. Berthold, University of Konstanz and KNIME, Germany 
Francesco Bonchi,ISI Foundation, Torino, Italy
Henrik Boström, KTH Royal Institute of Technology, Sweden 
Ulf Brefeld, Leuphana University of Lüneberg, Germany
Wray Buntine, Monash University, Australia 
Andre Ponce de Leon F. de Carvalho, University Sao Paolo, Brazil
Michelangelo Ceci,Università degli Studi di Bari Aldo Moro, Italy 
Aniket Chakrabarti, Microsoft, USA
Jesse Davis,Katholieke Universiteit Leuven, Belgium 
Tijl De Bie, University of Bristol, UK 
Luc De Raedt, Katholieke Universiteit Leuven, Belgium 
Krzysztof Dembczyński, University of Poznan, Poland
Charlotte Domeniconi, George Mason University, USA
Saso Dzeroski, Jožef Stefan Institute, Slovenia 
Tom Fawcett,Silicon Valley Data Science LLC, USA 
Stefano Ferilli,Università degli Studi di Bari Aldo Moro, Italy 
Peter Flach, University of Bristol, UK 
Eibe Frank, University of Waikato, Hamilton, New Zealand 
João Gama, University of Porto, Portugal 
Jingrui He, Arizona State University, USA 
Jaako Hollmén, Aalto University, Finland 
Xia Ben Hu, Texas A&M University, USA
Eyke Hüllermeier, University of Paderborn, Germany 
Nathalie Japkowicz, American University, USA
Szymon Jaroszewicz, National Institute of Telecommunications, Poland 
Alípio Jorge, University of Porto / INESC TEC, Portugal
Arno Knobbe,LIACS, Universiteit Leiden, Netherlands
Dragi Kocev, Jožef Stefan Institute, Slovenia 
Vipin Kumar,University of Minnesota, USA 
Mark Last, Ben-Gurion University of the Negev, Israel 
Nada Lavrac, Jožef Stefan Institute, Slovenia 
Zhenhui (Jessie) Li, The Pennsylvania State University, USA
Jefrey Lijffijt, Ghent University, Belgium
Bing Liu, University of Illinois, Chicago, USA 
Daniel Lowd, University of Oregon, USA 
Wagner Meira, Universidade Federal de Minas Gerais, Brazil 
Prem Melville, Social Alpha, USA 
Ernestina Menasalva, Universidad Politécnia De Madrid, Spain
Dunja Mladenic, Jožef Stefan Institute, Slovenia 
Katharina Morik, Technische Universität Dortmund, Germany 
Abdullah Mueen, University of New Mexico, USA 
Sriraam Natarajan, University Indiana, Bloomington, USA 
Siegfried Nijssen, LIACS, Universiteit Leiden, Netherlands 
Mykola Pechenizkiy, Eindhoven University of Technology, Netherlands 
Ruggero G. Pensa, University of Torino, Italy 
Francois Petitjean, Monash University, Australia
Bernhard Pfahringer, University of Waikato, Hamilton, New Zealand 
Marc Plantevit, Université de Lyon, France
B. Aditya Prakash, Virginia Tech, USA 
Chedy Raïssi,INRIA Paris, France
Jan Ramon, INRIA Lille Nord Europe, France 
Chandan K. Reddy, Virginia Tech, USA 
Marko Robnik-Sikonja, University of Ljubljana, Slovenia 
Tobias Scheffer, University of Potsdam, Germany
Arno Siebes,Universiteit Utrecht, Netherlands 
Jie Tang,Tsinghua University, China
Nikolaj Tatti, Helsinki Institute of Information Technology, Aalto University, Finland 
Hannu Toivonen,University of Helsinki, Finland 
Vincent S. Tseng, National Chiao Tung University, Taiwan
Antti Ukkonen, University of Helsinki, Finland
Matthijs van Leeuwen, Leiden University, Netherlands 
Jilles Vreeken, Max Planck Institute for Informatics and Saarland University, Germany 
Tim Weninger, University of Notre Dame, USA 
Hui Xiong, Rutgers University, USA
Jieping Ye, University of Michigan, Ann Arbor, USA 
Albrecht Zimmermann, Université de Caen Normandie, France