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DS 2021 : 24th International Conference on Discovery Science

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Conference Series : Discovery Science
 
Link: https://ds2021.cs.dal.ca/
 
When Oct 11, 2021 - Oct 13, 2021
Where Halifax, Canada
Abstract Registration Due May 16, 2021
Submission Deadline May 23, 2021
Notification Due Jul 20, 2021
Final Version Due Aug 8, 2021
Categories    discovery science   machine learning   artificial intelligence   data science
 

Call For Papers

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The 24th International Conference on Discovery Science (DS 2021)
http://ds2021.cs.dal.ca/
Halifax, Canada, October, 11-13, 2021

CALL FOR PAPERS

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COVID-19

We hope that by October, the world will have returned to normality, and we can welcome you to Halifax. However, in case the COVID-19 risk persists and travelling is difficult, DS 2021 will take place either as a mixed event, offering both remote and on-site presentation options, or as a fully online event in the worst case. The accepted papers will still be published by Springer, and the special issue will proceed as announced. In these challenging times that the whole of humanity is going through, we hope that all of you are safe and remain healthy.

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Important Dates

Abstract submission: May 16, 2021

Full paper submission: May 23, 2021

Notification: July 20, 2021

Camera-ready version, author registration: August 8, 2021

Conference: October 11-13, 2021

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Scope and Topics

The International Conference on Discovery Science provides an open forum for intensive discussions and exchange of new ideas among researchers working in Discovery Science. The conference focus is on the use of artificial intelligence methods in science. Its scope includes the development and analysis of methods for discovering scientific knowledge, coming from machine learning, data mining, intelligent data analysis, big data analytics, and their application in various domains.

We invite submissions of research papers addressing all aspects of discovery science. We encourage papers that focus on the analysis of different types of massive and complex data. This includes structured, spatio-temporal and network data and heterogeneous, continuous or imprecise data. We also encourage papers in computational scientific discovery, mining scientific data, computational creativity and discovery informatics. We welcome papers addressing artificial intelligence applications in different domains of science, including biomedicine and life sciences, materials science, astronomy, physics, chemistry, and social sciences.

Possible topics include, but are not limited to:

* Artificial intelligence (machine learning, knowledge representation and reasoning, natural language processing, statistical methods, etc.) applied to science
* Machine learning: supervised learning (including ranking, multi-target prediction and structured prediction), unsupervised learning, semi-supervised learning, active learning, reinforcement learning, online learning, transfer learning, etc.
* Knowledge discovery and data mining
* Causal modelling
* AutoML, meta-learning, planning to learn
* Machine learning and high-performance computing, grid and cloud computing
* Literature-based discovery
* Ontologies for science, including the representation and annotation of datasets and domain knowledge
* Explainable AI, interpretability of machine learning and deep learning models
* Discovery and analysis of process models
* Computational creativity
* Anomaly detection and outlier detection
* Data streams, evolving data, change detection, concept drift, model maintenance
* Network analysis
* Time-series analysis
* Learning from complex data
+ Graphs, networks, linked and relational data
+ Spatial, temporal and spatiotemporal data
+ Unstructured data, including textual and web data
+ Multimedia data
* Data and knowledge visualization
* Human-machine interaction for knowledge discovery and management
* Evaluation of models and predictions in a discovery setting
* Applications of the above techniques in scientific domains, such as
+ Physical sciences (e.g., materials sciences, particle physics)
+ Life sciences (e.g., systems biology/systems medicine)
+ Environmental sciences
+ Natural and social sciences

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Submission Guidelines

Papers must be written in English and formatted according to the Springer LNCS guidelines. Authors should consult Springer’s authors’ instructions (ftp://ftp.springernature.com/cs-proceeding/svproc/guidelines/Springer_Instructions_for_Authors_of_Proceedings_CS.pdf ) and use their proceedings templates, either for LaTeX (ftp://ftp.springernature.com/cs-proceeding/llncs/llncs2e.zip) or for Word (ftp://ftp.springernature.com/cs-proceeding/llncs/word/splnproc1703.zip), for the preparation of their papers. Springer’s proceedings LaTeX templates are also available in Overleaf (https://www.overleaf.com/latex/templates/springer-lecture-notes-in-computer-science/kzwwpvhwnvfj#.WsdHOy5uZpg). Springer encourages authors to include their ORCIDs in their papers. Guidelines are available at https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines. Papers should be submitted in PDF form via the DS 2021 Online Submission System (EasyChair – URL will be announced soon). Once a paper has been submitted to the conference, changes to the author list are not permitted.

Submitted papers should not exceed 15 pages (long papers) and 10 pages (short ones) in total (including references). All submissions will be subject to review by the DS 2021 Program Committee. The Program Committee reserves the right to offer acceptance as Short Papers (10 pages in the Proceedings) to some Long Paper submissions. All accepted papers will appear in the conference proceedings published by Springer LNCS series and have allocated time for oral presentation at the conference.

The reviews are single-blind. Authors do not need to anonymize their submission. Submitted papers may not have appeared in or be under consideration for another workshop, conference or journal. They may not be under review or submitted to another forum during the DS 2021 review process.

Authors of accepted papers will transfer their copyrights to Springer. The corresponding author of each paper, acting on behalf of all authors, must complete and sign a Consent-to-Publish form. The corresponding author signing the copyright form should match the corresponding author marked on the paper.

Open access publication (against the payment of additional open access fees) is possible. It should be specified when submitting the camera-ready copies of the papers. Further information (including prices) is available at https://www.springer.com/gp/computer-science/lncs/open-access-publishing-in-computer-proceedings. Springer requires the invoicing address and the CC-BY Consent-to-Publish forms together with the camera-ready copy files for publication.

For a paper to appear in the proceedings, at least one of the authors must register for the conference by the camera-ready submission deadline and present the paper at the conference.

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Special issue and Best Student Paper Award

The authors of selected papers presented at DS 2021 will be invited to submit extended versions for possible inclusion in a special issue of Machine Learning journal (published by Springer) on Discovery Science. Fast-track processing will be used to have them reviewed and published.

There will be an award for the Best Student Paper in the value of 555 Eur sponsored by Springer.

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Organization

Program Chairs
* Carlos Soares, University of Porto, Portugal
* Luis Torgo, Dalhousie University, Canada

Steering Committee Chair
* Saso Dzeroski, Jozef Stefan Institute, Ljubljana, Slovenia

Local Organizing Committee
* David Langstroth, Dalhousie University, Canada
* Nuno Moniz, University of Porto, Portugal
* Paula Branco, Ottawa University, Canada
* Vitor Cerqueira, Dalhousie University, Canada
* Yassine Baghoussi, University of Porto, Portugal

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Contact

All questions about submissions should be emailed to the program chairs Carlos Soares (csoares@fe.up.pt) or Luis Torgo (ltorgo@dal.ca)

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