Background: 

The growth in astronomical data and information resources requires a comparable increase in data-oriented  research approaches to scientific discovery in astronomy.  This data science orientation includes visualization, discovery informatics (data mining), machine learning, large-database astronomy, and semantic science. An informatics subdiscipline of astronomy (Astroinformatics) will include specific computational skills, ways of thinking, and research methodologies, parallel to the requirements of theoretical astrophysics and observational astronomy. 

With the advent of very large sky surveys, real-time astronomy from a host of telescopes, and Virtual Observatory access to enormous databases, it is time to move forward in recognizing and supporting the emerging discipline of Astroinformatics.  A special session at the AAS January 2010 meeting is timely, since it  follows upon several smaller international workshops in the past couple of years (including Practical Semantic Astronomy 2008 and 2009, Machine Learning and AI Applications in Astrophysics and Cosmology, Classification and Discovery in Large Astronomical Surveys, and others).