Multimission Archive at STScI

Alberto Conti, aconti@stsci.edu, for the MAST Team

The Multimission Archive at STScI (MAST) is the NASA repository for ultraviolet and optical observations from both active and legacy missions. MAST supports the astronomical community by maintaining public-access interfaces to its collections, and providing expert user support and access calibration and analysis software.

As of November 2010, the volume of MAST’s data holdings was 155 terabytes (TB). Approximately 72% of this volume is data from Hubble Space Telescope, including reprocessed data in the Hubble Legacy Archive (HLA); 16% is from Galaxy Evolution Explorer (GALEX); 10% is high-level science products (HLSPs) or data from Far Ultraviolet Spectroscopic Explorer, X-ray Multi-Mirror Mission–Newton, or the Digitized Sky Survey; and 2% is from Kepler.

MAST User Group

On July 16, 2010, the MAST User Group (MUG) held its annual meeting at the Institute. The MUG provides an essential user perspective on archive operations and development, including assessments of the priorities for short- and long-term operational and scientific enhancements to MAST. The 2010 MUG report and the presentations made at the meeting by MAST staff members are available here.

The New Kepler-to-GALEX Cross-Match Tool

Coinciding with Kepler’s Cycle 3 guest-observer (GO) season, MAST is happy to announce the availability of a cross-match tool between GALEX sources and the Kepler initial catalog. Its purpose is to extend the wavelength baseline from the optical magnitudes of Kepler ground support (Sloan-like g, r, i, and z filters) to near- and far-ultraviolet bandpasses. This extension is especially important for selecting hot star targets when only photometric data are available.

The cross-match tool is available two ways: by an interface form and by Structured Query Language (SQL) queries in the CasJobs tool environment.

The form has the look and feel of other MAST mission-data retrieval forms (Figure 1). It works for simple queries that yield a relatively small list of results (<15,000 rows). Users of the form need not know the SQL query language, which is an advantage.