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The Kilo-Degree Survey (KiDS) is an optical wide-field imaging survey carried out with the VLT Survey Telescope and the OmegaCAM camera. KiDS will image 1500 square degrees in four filters (ugri), and together with its near-infrared counterpart VIKING will produce deep photometry in nine bands. Designed for weak lensing shape and photometric redshift measurements, the core science driver of the survey is mapping the large-scale matter distribution in the Universe back to a redshift of ~0.5. Secondary science cases are manifold, covering topics such as galaxy evolution, Milky Way structure, and the detection of high-redshift clusters and quasars. KiDS is an ESO Public Survey and dedicated to serving the astronomical community with high-quality data products derived from the survey data, as well as with calibration data. Public data releases will be made on a yearly basis, the first two of which are presented here. For a total of 148 survey tiles (~160 sq.deg.) astrometrically and photometrically calibrated, coadded ugri images have been released, accompanied by weight maps, masks, source lists, and a multi-band source catalog. A dedicated pipeline and data management system based on the Astro-WISE software system, combined with newly developed masking and source classification software, is used for the data production of the data products described here. The achieved data quality and early science projects based on the data products in the first two data releases are reviewed in order to validate the survey data. Early scientific results include the detection of nine high-z QSOs, fifteen candidate strong gravitational lenses, high-quality photometric redshifts and galaxy structural parameters for hundreds of thousands of galaxies. (Abridged), Comment: 26 pages, 26 figures, 2 appendices; two new figures, several textual clarifications, updated references; accepted for publication in A&A

The OmegaCAM wide-field optical imager is the sole instrument on the VLT Survey Telescope at ESO's Paranal Observatory. The instrument, as well as the telescope, have been designed for surveys with very good, natural seeing-limited image quality over a 1 square degree field. OmegaCAM was commissioned in 2011 and has been observing three ESO Public Surveys in parallel since October 15, 2011. We use the Astro-WISE information system to monitor the calibration of the observatory and to produce the Kilo Degree Survey (KiDS). Here we describe the photometric monitoring procedures in Astro-WISE and give a first impression of OmegaCAM's photometric behavior as a function of time. The long-term monitoring of the observatory goes hand in hand with the KiDS survey production in Astro-WISE. KiDS is observed under partially non-photometric conditions. Based on the first year of OmegaCAM operations it is expected that a $\sim 1%-2%$ photometric homogeneity will be achieved for KiDS., Comment: Accepted for publication in topical issue of Experimental Astronomy on Astro-WISE information system

The recent explosion of recorded digital data and its processed derivatives threatens to overwhelm researchers when analysing their experimental data or when looking up data items in archives and file systems. While current hardware developments allow to acquire, process and store 100s of terabytes of data at the cost of a modern sports car, the software systems to handle these data are lagging behind. This general problem is recognized and addressed by various scientific communities, e.g., DATAGRID/EGEE federates compute and storage power over the high-energy physical community, while the astronomical community is building an Internet geared Virtual Observatory, connecting archival data. These large projects either focus on a specific distribution aspect or aim to connect many sub-communities and have a relatively long trajectory for setting standards and a common layer. Here, we report "first light" of a very different solution to the problem initiated by a smaller astronomical IT community. It provides the abstract "scientific information layer" which integrates distributed scientific analysis with distributed processing and federated archiving and publishing. By designing new abstractions and mixing in old ones, a Science Information System with fully scalable cornerstones has been achieved, transforming data systems into knowledge systems. This break-through is facilitated by the full end-to-end linking of all dependent data items, which allows full backward chaining from the observer/researcher to the experiment. Key is the notion that information is intrinsic in nature and thus is the data acquired by a scientific experiment. The new abstraction is that software systems guide the user to that intrinsic information by forcing full backward and forward chaining in the data modelling., Comment: To be published in ADASS XVI ASP Conference Series, 2006, R. Shaw, F. Hill and D. Bell, eds