24th International Conference on Discovery Science

Halifax, Canada
11-13 October, 2021

DS’2021 provides an open forum for intensive discussions and exchange of new ideas among researchers working in the area of 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, and big data analytics, as well as 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, including structured, spatio-temporal and network data, as well as heterogeneous, continuous or imprecise data. We also encourage papers in the fields of computational scientific discovery, mining scientific data, computational creativity and discovery informatics. We welcome papers addressing applications of artificial intelligence in different domains of science, including biomedicine and life sciences, materials science, astronomy, physics, chemistry, as well as social sciences.

Conference Format

We hope that by October the world will have returned to normality and we can welcome you in Halifax. However, in case the COVID-19 risks will persist and travelling will be difficult, DS 2021 will take place either as a mixed event by 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 and positive.

News

2021/03/03 - First version of the conference Web site is live! Still work in progress, obviously!

Key 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

Call for Papers

Scope

The international conference on Discovery Science provides an open forum for intensive discussions and exchange of new ideas among researchers working in the area of 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, and big data analytics, as well as their application in various domains.

Topics

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, including structured, spatio-temporal and network data, as well as heterogeneous, continuous or imprecise data. We also encourage papers in the fields of computational scientific discovery, mining scientific data, computational creativity and discovery informatics. We welcome papers addressing applications of artificial intelligence in different domains of science, including biomedicine and life sciences, materials science, astronomy, physics, chemistry, as well as 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
  • Process discovery and analysis
  • 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 discovery setting
  • Machine learning and cybersecurity
  • 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

Submission Guidelines

Papers must be written in English and formatted according to the Springer LNCS guidelines. Papers should be submitted in PDF form via the DS 2020 Online Submission System at EasyChair. 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 2020 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 will have allocated time for oral presentation in 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 2020 review process.

Guidelines for Accepted Papers

To be announced

Special Issue

The authors of a number of selected papers presented at DS 2021 will be invited to submit extended versions of their papers 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.

Award

There will be a Best Student Paper Award in the value of 555 Eur sponsored by Springer.

Conference Organization

Program Chairs

Steering Committe Chair

Local Organizing Committee

Program Committee

Program Chairs

  • Carlos Soares, University of Porto, Portugal
  • Luis Torgo, Dalhousie University, Canada

Program Committee Members

To Be Announced

Conference Program

To Be Announced

Venue

To Be Announced

Conference Registration

To Be Announced

Sponsors

To Be Announced

Contact