Paper Submission

Submitted papers may be up to twelve (12) pages long and must be formatted according to the layout supplied by Springer- Verlag for the Lecture Notes in Computer Science series. The proceedings of selected papers will be published within this series.

Submitted papers may not have appeared in or be under consideration for another conference or a journal, nor may they be under review or submitted to another forum during the DS 2014 review process.

Key dates

  • Abstracts: May 19, 2014, 12:00 CET CLOSED
  • Full paper submission: May 9, 2014 May 26, 2014, 12:00 CET CLOSED
  • Author notification: June 20, 2014 COMPLETED
  • Camera-ready papers due: July 9, 2014 COMPLETED
  • Early registration deadline: September 8, 2014

To submit a paper, use the following link:

Call for papers

DS 2014 provides an open forum for intensive discussions and exchange of new ideas among researchers working in the area of Discovery Science. The scope of the conference includes the development and analysis of methods for discovering scientific knowledge, coming from machine learning, data mining, and intelligent data analysis, as well as their application in various scientific domains.
We welcome papers that focus on the analysis of different types of complex data, such as structured, spatio-temporal and network data. We particularly welcome papers addressing applications. Finally, we would like to encourage contributions from the areas of computational scientific discovery, mining scientific data, computational creativity and discovery informatics.
An indicative non-exhaustive list of topics includes
  • computational scientific discovery
  • data mining and knowledge discovery
  • machine learning and statistical methods
  • computational creativity
  • mining scientific data
  • data and knowledge visualization
  • knowledge discovery from scientific literature
  • mining text, unstructured and multimedia data
  • mining structured and relational data
  • mining temporal and spatial data
  • mining data streams
  • network analysis
  • discovery informatics
  • discovery and experimental workflows
  • knowledge capture and scientific ontologies
  • data and knowledge integration
  • logic and philosophy of scientific discovery
  • applications of computational methods in various scientific domains (e.g., bioinformatics, system biology, and climate informatics)

Call for papers is disseminated through and ML news group.