Yanxia Zhang

The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST, also called the Guo Shou Jing Telescope) is a special reflecting Schmidt telescope. LAMOST's special design allows both a large aperture (effective aperture of 3.6 m-4.9 m) and a wide field of view (FOV) (5 degrees). It has an innovative active reflecting Schmidt configuration which continuously changes the mirror's surface that adjusts during the observation process and combines thin deformable mirror active optics with segmented active optics. Its primary mirror (6.67 m x 6.05 m) and active Schmidt mirror (5.74 m x 4.40 m) are both segmented, and composed of 37 and 24 hexagonal sub-mirrors respectively. By using a parallel controllable fiber positioning technique, the focal surface of 1.75 m in diameter can accommodate 4000 optical fibers. Also, LAMOST has 16 spectrographs with 32 CCD cameras. LAMOST will be the telescope with the highest rate of spectral acquisition. As a national large scientific project, the LAMOST project was formally proposed in 1996, and approved by the Chinese government in 1997. The construction started in 2001, was completed in 2008 and passed the official acceptance in June 2009. The LAMOST pilot survey was started in October 2011 and the spectroscopic survey will launch in September 2012. Up to now, LAMOST has released more than 480 000 spectra of objects. LAMOST will make an important contribution to the study of the large-scale structure of the Universe, structure and evolution of the Galaxy, and cross-identification of multi-waveband properties in celestial objects.

This paper describes the data release of the LAMOST pilot survey, which includes data reduction, calibration, spectral analysis, data products and data access. The accuracy of the released data and the information about the FITS headers of spectra are also introduced. The released data set includes 319 000 spectra and a catalog of these objects.

The fields of Astrostatistics and Astroinformatics are vital for dealing with the big data issues now faced by astronomy. Like other disciplines in the big data era, astronomy has many V characteristics. In this paper, we list the different data mining algorithms used in astronomy, along with data mining software and tools related to astronomical applications. We present SDSS, a project often referred to by other astronomical projects, as the most successful sky survey in the history of astronomy and describe the factors influencing its success. We also discuss the success of Astrostatistics and Astroinformatics organizations and the conferences and summer schools on these issues that are held annually. All the above indicates that astronomers and scientists from other areas are ready to face the challenges and opportunities provided by massive data volume.

Gaze information provides indication of users focus which complements remote collaboration tasks, as distant users can see their partner’s focus. In this paper, we apply gaze for co-located collaboration, where users’ gaze locations are presented on the same display, to help collaboration between partners. We integrated various types of gaze indicators on the user interface of a collaborative search system, and we conducted two user studies to understand how gaze enhances coordination and communication between co-located users. Our results show that gaze indeed enhances co-located collaboration, but with a trade-off between visibility of gaze indicators and user distraction. Users acknowledged that seeing gaze indicators eases communication, because it let them be aware of their partner’s interests and attention. However, users can be reluctant to share their gaze information due to trust and privacy, as gaze potentially divulges their interests.