NVO and the LSB Universe

There is tremendous scientific potential in a National Virtual Observatory, particularly for projects that need to mine large databases for rare or unusual objects. However, the NVO will also make an impact on any project, large or small, the requires a mixture of datasets to explore a wide range of astrophysical phenomenon. In this article I discuss the influence of the NVO on research into the formation and evolution of low surface brightness (LSB) galaxies. In particular, I present the preliminary results from an NVO-style project that combines the DPOSS and 2MASS datasets to search for giant disk galaxies. 1. The Dataset Revolution Astrophysical problems seem to increase in complexity with each successive generation. Observationally, new wavelengths and new flux limits bring about new phenomenon that demands more telescope time and begs theoretical interpretation. In the last 15 years we have seen an explosion in the amount, wavelength coverage and diversity of our datasets that have lead to numerous discoveries, but have also buried us in the sheer quantity of information. Our community has also grown parallel to our data growth, but most of the high powered observational tools still lie in the possession of a few institutions. This disparity in big telescope resources has been offset, in a large part, by the formation of national data centers and the distribution of analysis software. Now an astronomer, regardless of the size of their home institution, can have access to high quality data and produce cutting edge science. With the addition of small grant programs (i.e. NASA’s ADP program), an astronomical industry developed during the last two decades and discovery has moved from the hands of the few to the hands of the many. One only need to compare the impact of HST science on the astronomical community to that of Keck to see how the existence of non-proprietary datasets can push forward science. As datasets have grow larger, there has been a strong emphasis on data mining and computational power. However, intelligent and cleverly designed projects depend more on access to direct tools rather then sophisticated algorithms. Thus, many astronomical projects today involve teams of scientists who bring together the diverse talents needed to attack the details of massive amounts of data. This is the goal of NVO, to provide the infrastructure and intellectual support for astronomical programs that compliment our already existing observational and theoretical foundations.