Session 1 "Astronomy"
Virtual Research Environments and data publication in Astronomy
Presenter: Dr. Jochen Klar
Department of Supercomputing and E-Science
In astronomy not only the data sets become larger and larger, but the scientific method shifts from single target observations and theoretical model calculations to large surveys and extensive computer simulations. This results in higher technical requirements for the IT-Infrastructure and calls for a more structured and organized data management. In addition, the trend towards international collaborations requires efficient ways to share and collaborate on the aquired data sets. These issues are reinforced by the demands to publish the data and provide it to the wider community.
In my talk I will present how we meet these challenges at the Leibniz-Institute for Astrophysics Potsdam (AIP). In particular I will talk about the virtual research environments for the CLUES and MUSE collaborations, our Daiquiri framework for data publication via SQL interfaces and their integration in the Virtual Observatory.
A review is given on all-sky and large-area astronomical surveys and their catalogued data over the whole range of electromagnetic spectrum, from gamma-ray to radio, such as Fermi-GLAST and INTEGRAL in gamma-ray, ROSAT, XMM and Chandra in X-ray, GALEX in UV, SDSS and several POSS I and II based catalogues (APM, MAPS, USNO, GSC) in optical range, 2MASS in NIR, WISE and AKARI IRC in MIR, IRAS and AKARI FIS in FIR, NVSS and FIRST in radio and many others, as well as most important surveys giving optical images (DSS I and II, SDSS, etc.), proper motions (Tycho, USNO, Gaia), variability (GCVS, NSVS, ASAS, Catalina, Pan-STARRS) and spectroscopic data (FBS, SBS, Case, HQS, HES, SDSS, CALIFA, GAMA).
Most important astronomical databases and archives are reviewed as well, including Wide-Field Plate DataBase (WFPDB), ESO, HEASARC, IRSA and MAST archives, CDS SIMBAD, VizieR and Aladin, NED and HyperLEDA extragalactic databases, ADS and astro-ph services. They are powerful sources for many-sided efficient research using Virtual Observatory tools. It is shown that using and analysis of Big Data accumulated in astronomy lead to many new discoveries.
Hrachya Astsatryan (ASNET-AM)