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Workshop on Astroinformatics

This is a workshop within the IEEE International Conference on Data Mining. The goal is to attain a stronger interaction between computer scientists, statisticians, and astronomers. Topics of interest include: computational models that represent astronomical phenomena, knowledge discovery/extraction methods, discovery methods guided by domain information (taxonomies, ontologies), efficient methods that search for patterns in large astronomical datasets, machine learning and statistical methods applied to astronomical sets, information retrieval and fusion, information visualization, and data mining across heterogeneous datasets in astronomy.
When 07 December 2013
from 09:00 AM to 06:00 PM
Where Dallas, Texas
Contact Name
Contact Phone 7137433614
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Astroinformatics is a recent interdisciplinary field of science that applies modern computational tools to the solution of astronomical problems. The field was born in response to the rapid growth of data volumes corresponding to a variety of sky surveys. Data repositories have gone from gigabytes into terabytes, and we expect those repositories to reach the terabytes in the coming years. An important area in astroinformatics is the application of data mining tools for analysis of large astronomical repositories and surveys. Key issues involve not only an efficient management of data resources, but also the design of new conceptual tools that efficiently address the nature of astronomical data. Important topics include  data organization, data description, astronomical classification taxonomies, data mining, machine learning, visualization, and astrostatistics. 

Submissions are invited on all aspects of astroinformatics. Submissions should present innovative ideas that add to the existing set of tools available to the astronomical and computational community. Possible topics include the following (list not exclusive):

  • Computational models that represent astronomical phenomena
  • Knowledge discovery/extraction methods
  • Discovery methods guided by domain information (taxonomies, ontologies)
  • Efficient methods that search for patterns in large astronomical datasets
  • Machine learning and statistical methods applied to astronomical sets
  • Information retrieval and fusion
  • Information Visualization
  • Data mining across heterogeneous datasets in astronomy


Session program: Astroinformatics (AstroInfo)

Region-Based Querying of Solar Data Using Descriptor Signatures -- Juan M. Banda, Chang Liu, and Rafal A. Angryk

Calculation and Applications of Bayesian Evidence in Astrophysics and Particle Physics Phenomenology -- Farhan Feroz

Neural Networks for Astronomical Data Analysis and Bayesian Inference -- Philip Graff, Farhan Feroz, Michael P. Hobson, and Anthony Lasenby

Online Classification for Time-Domain Astronomy -- Kitty K. Lo, Tara Murphy, Umaa Rebbapragada, and Kiri Wagstaff

On Using SIFT Descriptors for Image Parameter Evaluation -- Patrick M. McInerney, Juan M. Banda, and Rafal A. Angryk

Automatic Identification of Hexagonal Pattern Artifacts in Radio Astronomical Surveys -- Dina Said, Jeroen Stil, Russ Taylor, and Ken Barker


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