Abstract
Recent advances have been made in evolving the NASA/IPAC Extragalactic Database (NED) into a data mining discovery engine. Infrastructure changes and data integration techniques are enabling more than a 10-fold expansion. NED will soon contain over a billion objects with their fundamental attributes (such as names, positions, redshifts, fluxes, and diameters) determined via cross-identifications among the largest sky surveys and over 100,000 smaller but scientifically important catalogs and journal articles. In addition, enhancements to the user interface, including new APIs, VO protocols, and queries involving derived physical quantities, will provide new pathways for multi-wavelength studies of large extragalactic samples.
Highlights
The NASA/IPAC Extragalactic Database (NED1) is an information system provided for the astronomical community that facilitates and accelerates multi-wavelength research on objects beyond our Milky Way that would otherwise be impossible or impractical to accomplish
3.1 The four "V"’s (The following is extracted from Paper I.) Many challenges confronted by the NED team pertain to the four “V’s of Big Data” - Volume, Variety, Velocity, and Veracity
Implementation of a VO Table Access Protocol (TAP) service is in progress, which will enable ‘power users’ to run ADQL queries against the NED object directory
Summary
The NASA/IPAC Extragalactic Database (NED1) is an information system provided for the astronomical community that facilitates and accelerates multi-wavelength research on objects beyond our Milky Way that would otherwise be impossible or impractical to accomplish. The NED team is continuously integrating data from the literature, NASA mission archives, and large sky surveys to produce and serve a comprehensive census of the observed universe. The database consists of information synthesized from over 22 NASA missions, large surveys such as GALEX and SDSS, and information gleaned from over 103,000 journal articles, catalogs, and astronomical telegrams. A repository for images and spectra contributed by authors of journal articles ("data behind the plots") is supported to simplify reproducibility of published results and making new discoveries in combination with other data in NED
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