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The accurate estimation of photometric redshifts plays a crucial role in accomplishing science objectives of the large survey projects. The template-fitting and machine learning are the two main types of methods applied currently. Based on the training set obtained by cross-correlating the DESI Legacy Imaging Surveys DR9 galaxy catalogue and SDSS DR16 galaxy catalogue, the two kinds of methods are used and optimized, such as EAZY for template-fitting approach and CATBOOST for machine learning. Then the created models are tested by the cross-matched samples of the DESI Legacy Imaging SurveysDR9 galaxy catalogue with LAMOST DR7, GAMA DR3 and WiggleZ galaxy catalogues. Moreover three machine learning methods (CATBOOST, Multi-Layer Perceptron and Random Forest) are compared, CATBOOST shows its superiority for our case. By feature selection and optimization of model parameters, CATBOOST can obtain higher accuracy with optical and infrared photometric information, the best performance ($MSE=0.0032$, $\sigma_{NMAD}=0.0156$ and $O=0.88$ per cent) with $g \le 24.0$, $r \le 23.4$ and $z \le 22.5$ is achieved. But EAZY can provide more accurate photometric redshift estimation for high redshift galaxies, especially beyond the redhisft range of training sample. Finally, we finish the redshift estimation of all DESI DR9 galaxies with CATBOOST and EAZY, which will contribute to the further study of galaxies and their properties., Comment: Accepted for publication in MNRAS. 14 pages, 9 figures, 11 tables

Astronomy education and public outreach (EPO) is one of the important part of the future development of astronomy. During the past few years, as the rapid evolution of Internet and the continuous change of policy, the breeding environment of science EPO keep improving and the number of related projects show a booming trend. EPO is no longer just a matter of to teachers and science educators but also attracted the attention of professional astronomers. Among all activates of astronomy EPO, the data driven astronomy education and public outreach (abbreviated as DAEPO) is special and important. It benefits from the development of Big Data and Internet technology and is full of flexibility and diversity. We will present the history, definition, best practices and prospective development of DAEPO for better understanding this active field.

Correlating BASS DR3 catalogue with ALLWISE database, the data from optical and infrared information are obtained. The quasars from SDSS are taken as training and test samples while those from LAMOST are considered as external test sample. We propose two schemes to construct the redshift estimation models with XGBoost, CatBoost and Random forest. One scheme (namely one-step model) is to predict photometric redshifts directly based on the optimal models created by these three algorithms; the other scheme (namely two-step model) is to firstly classify the data into low- and high- redshift datasets, and then predict photometric redshifts of these two datasets separately. For one-step model, the performance of these three algorithms on photometric redshift estimation is compared with different training samples, and CatBoost is superior to XGBoost and Random forest. For two-step model, the performance of these three algorithms on the classification of low- and high-redshift subsamples are compared, and CatBoost still shows the best performance. Therefore CatBoost is regard as the core algorithm of classification and regression in two-step model. By contrast with one-step model, two-step model is optimal when predicting photometric redshift of quasars, especially for high redshift quasars. Finally the two models are applied to predict photometric redshifts of all quasar candidates of BASS DR3. The number of high redshift quasar candidates is 3938 (redshift $\ge 3.5$) and 121 (redshift $\ge 4.5$) by two-step model. The predicted result will be helpful for quasar research and follow up observation of high redshift quasars., 16 pages, 8 figures, 12 tables, accepted for publication in Monthly Notices of the Royal Astronomical Society Main Journal

LAMOST Data Release 5, covering $\sim$17,000 $deg^2$ from $-10^{\circ}$ to $80^{\circ}$ in declination, contains 9 millions co-added low resolution spectra of celestial objects, each spectrum combined from repeat exposure of two to tens of times during Oct 2011 to Jun 2017. In this paper, We present the spectra of individual exposures for all the objects in LAMOST Data Release 5. For each spectrum, equivalent width of 60 lines from 11 different elements are calculated with a new method combining the actual line core and fitted line wings. For stars earlier than F type, the Balmer lines are fitted with both emission and absorption profiles once two components are detected. Radial velocity of each individual exposure is measured by minimizing ${\chi}^2$ between the spectrum and its best template. Database for equivalent widths of spectral lines and radial velocities of individual spectra are available online. Radial velocity uncertainties with different stellar type and signal-to-noise ratio are quantified by comparing different exposure of the same objects. We notice that the radial velocity uncertainty depends on the time lag between observations. For stars observed in the same day and with signal-to-noise ratio higher than 20, the radial velocity uncertainty is below 5km/s, and increase to 10km/s for stars observed in different nights., Comment: 21 pages, 15 figures

Astronomical observation data require long-term preservation, and the rapid accumulation of observation data makes it necessary to consider the cost of long-term archive storage. In addition to low-speed disk-based online storage, optical disk or tape-based offline storage can be used to save costs. However, for astronomical research that requires historical data (particularly time-domain astronomy), the performance and energy consumption of data-accessing techniques cause problems because the requested data (which are organized according to observation time) may be located across multiple storage devices. In this study, we design and develop a tool referred to as AstroLayout to redistribute the observation data using spatial aggregation. The core algorithm uses graph partitioning to generate an optimized data placement according to the original observation data statistics and the target storage system. For the given observation data, AstroLayout can copy the long-term archive in the target storage system in accordance with this placement. An efficiency evaluation shows that AstroLayout can reduce the number of devices activated when responding to data-access requests in time-domain astronomy research. In addition to improving the performance of data-accessing techniques, AstroLayout can also reduce the storage system’s power consumption. For enhanced adaptability, it supports storage systems of any media, including optical disks, tapes, and hard disks.

The WorldWide Telescope(WWT) is a scientific visualization platform which can browse deep space images, star catalogs, and planetary remote sensing data from different observation facilities in a three-dimensional virtual scene. First launched and then open-sourced by Microsoft Research, the WWT is now managed by the American Astronomical Society (AAS). Hierarchical Progressive Survey (HiPS) is an astronomical data release scheme proposed by Centre de Donn\'ees astronomiques de Strasbourg (CDS) and has been accepted as a recommendation by International Virtual Observatory Alliance (IVOA). The HiPS solution has been adopted widely by many astronomical institutions for data release. Since WWT selected Hierarchical Triangular Mesh (HTM) as the standard for data visualization in the early stage of development, data released by HiPS cannot be visualized in WWT, which significantly limits the application of WWT. This paper introduces the implementation method for HiPS dataset visualization in WWT, and introduces HiPS data projection, mesh rendering, and data index implementation in WWT. Taking Chang'E-2 lunar probe data as an example, this paper introduces how to convert planetary remote sensing data into a HiPS dataset and integrate it into WWT. This paper also compares the efficiency and memory consumption of WWT loading its native data and HiPS data, and illustrates the application of HiPS in scientific data visualization and science education in WWT., Comment: 22 pages, 15 figures

Public observatory is playing more and more important role in astronomy education, citizen science and scientific research. It is developing rapidly and has made some progress through a variety of approaches. As relative small number and high operating costs of professional observatories, it leads that only just a few students benefit. As a result, amateur astronomers begin to build their own remote observatories, but they also face great challenge, especially in hardware technology experience and construction funds. Their self-designed hardware connection and control system often breaks down, and then a stable hardware integration system becomes very critical. According to requirement investigation to dozens of the amateur, we propose an amateur public observatory model, and a hardware integration system as a bridge between observatory equipment and observation software. It not only can satisfy hardware requirement for multiple control modes, but also saves cost. It has great significance in promoting citizen science and astronomy education.

With the development of modern science and technology, astronomy has entered the era of data-intensive scientific discovery. Cyber-infrastructure is becoming a crucial part of both key national science projects and daily research in astronomy. In this chapter, cyber-infrastructure requirements and implementation status of five cutting-edge astronomical projects are described, namely the five-hundred-meter aperture spherical radio telescope (FAST), the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), the MingantU SpEctral Radioheliograph (MUSER), the Chinese–French SVOM mission, and the Square Kilometer Array (SKA). Furthermore, as a common cyber-infrastructure for astronomy research, a brief overview of Virtual Observatory including its research and development history and current applications is given. Several suggestions are listed in the end of the paper for further development of scientific research cyber-infrastructure.

The Beijing-Arizona Sky Survey (BASS) is a wide and deep imaging survey to cover a 5400 deg$^2$ area in the Northern Galactic Cap with the 2.3m Bok telescope using two filters ($g$ and $r$ bands). The Mosaic $z$-band Legacy Survey (MzLS) covers the same area in $z$ band with the 4m Mayall telescope. These two surveys will be used for spectroscopic targeting of the Dark Energy Spectroscopic Instrument (DESI). The BASS survey observations were completed in 2019 March. This paper describes the third data release (DR3) of BASS, which contains the photometric data from all BASS and MzLS observations between 2015 January and 2019 March. The median astrometric precision relative to {\it Gaia} positions is about 17 mas and the median photometric offset relative to the PanSTARRS1 photometry is within 5 mmag. The median $5\sigma$ AB magnitude depths for point sources are 24.2, 23.6, and 23.0 mag for $g$, $r$, and $z$ bands, respectively. The photometric depth within the survey area is highly homogeneous, with the difference between the 20\% and 80\% depth less than 0.3 mag. The DR3 data, including raw data, calibrated single-epoch images, single-epoch photometric catalogs, stacked images, and co-added photometric catalogs, are publicly accessible at \url{http://batc.bao.ac.cn/BASS/doku.php?id=datarelease:home}., Comment: published in ApJS

Astronomy cloud computing environment is a cyber-Infrastructure for Astronomy Research initiated by Chinese Virtual Observatory (China-VO) under funding support from NDRC (National Development and Reform commission) and CAS (Chinese Academy of Sciences). Based on virtualization technology, astronomy cloud computing environment was designed and implemented by China-VO team. It consists of five distributed nodes across the mainland of China. Astronomer can get compuitng and storage resource in this cloud computing environment. Through this environments, astronomer can easily search and analyze astronomical data collected by different telescopes and data centers , and avoid the large scale dataset transportation.

The search and follow-up observation of electromagnetic (EM) counterparts of gravitational waves (GW) is a current hot topic of GW cosmology. Due to the limitation of the accuracy of the GW observation facility at this stage, we can only get a rough sky-localization region for the GW event, and the typical area of the region is between 200 and 1500 square degrees. Since GW events occur in or near galaxies, limiting the observation target to galaxies can significantly speedup searching for EM counterparts. Therefore, how to efficiently select host galaxy candidates in such a large GW localization region, how to arrange the observation sequence, and how to efficiently identify the GW source from observational data are the problems that need to be solved. International Virtual Observatory Alliance has developed a series of technical standards for data retrieval, interoperability and visualization. Based on the application of VO technologies, we construct the GW follow-up Observation Planning System (GWOPS). It consists of three parts: a pipeline to select host candidates of GW and sort their priorities for follow-up observation, an identification module to find the transient from follow-up observation data, and a visualization module to display GW-related data. GWOPS can rapidly respond to GW events. With GWOPS, the operations such as follow-up observation planning, data storage, data visualization, and transient identification can be efficiently coordinated, which will promote the success searching rate for GWs EM counterparts., Comment: 12 pages, 8 figures, published by Publications of the Astronomical Society of the Pacific

The three Antarctic Survey Telescopes (AST3) aim to carry out time domain imaging survey at Dome A, Antarctica. The first of the three telescopes (AST3-1) was successfully deployed on January 2012. AST3-1 is a 500\,mm aperture modified Schmidt telescope with a 680\,mm diameter primary mirror. AST3-1 is equipped with a SDSS $i$ filter and a 10k $\times$ 10k frame transfer CCD camera, reduced to 5k $\times$ 10k by electronic shuttering, resulting in a 4.3 deg$^2$ field-of-view. To verify the capability of AST3-1 for a variety of science goals, extensive commissioning was carried out between March and May 2012. The commissioning included a survey covering 2000 deg$^2$ as well as the entire Large and Small Magellanic Clouds. Frequent repeated images were made of the center of the Large Magellanic Cloud, a selected exoplanet transit field, and fields including some Wolf-Rayet stars. Here we present the data reduction and photometric measurements of the point sources observed by AST3-1. We have achieved a survey depth of 19.3\,mag in 60 s exposures with 5\,mmag precision in the light curves of bright stars. The facility achieves sub-mmag photometric precision under stable survey conditions, approaching its photon noise limit. These results demonstrate that AST3-1 at Dome A is extraordinarily competitive in time-domain astronomy, including both quick searches for faint transients and the detection of tiny transit signals., 12 pages, 8 figures, accepted for publication in MNRAS, the dataset is public in http://explore.china-vo.org/

This paper presents the second data release (DR2) of the Beijing-Arizona Sky Survey (BASS). BASS is an imaging survey of about 5400 deg$^2$ in $g$ and $r$ bands using the 2.3 m Bok telescope. DR2 includes the observations as of July 2017 obtained by BASS and Mayall $z$-band Legacy Survey (MzLS). This is our first time to include the MzLS data covering the same area as BASS. BASS and MzLS have respectively completed about 72% and 76% of their observations. The two surveys will be served for the spectroscopic targeting of the upcoming Dark Energy Spectroscopic Instrument. Both BASS and MzLS data are reduced by the same pipeline. We have updated the basic data reduction and photometric methods in DR2. In particular, source detections are performed on stacked images, and photometric measurements are co-added from single-epoch images based on these sources. The median 5$\sigma$ depths with corrections of the Galactic extinction are 24.05, 23.61, and 23.10 mag for $g$, $r$, and $z$ bands, respectively. The DR2 data products include stacked images, co-added catalogs, and single-epoch images and catalogs. The BASS website (http://batc.bao.ac.cn/BASS/) provides detailed information and links to download the data., Comment: 23 pages, published in AJ

The Beijing-Arizona Sky Survey (BASS) is a new wide-field legacy imaging survey in the northern Galactic cap using the 2.3m Bok telescope. The survey will cover about 5400 deg$^2$ in the $g$ and $r$ bands, and the expected 5$\sigma$ depths (corrected for the Galactic extinction) in the two bands are 24.0 and 23.4 mag, respectively. BASS started observations in January 2015, and has completed about 41% of the whole area as of July 2016. The first data release contains both calibrated images and photometric catalogs obtained in 2015 and 2016. The depths of single-epoch images in the two bands are 23.4 and 22.9 mag, and the full depths of three epochs are about 24.1 and 23.5 mag, respectively., Comment: 16 pages, published by AJ

The Beijing-Arizona Sky Survey (BASS) is a wide-field two-band photometric survey of the Northern Galactic Cap using the 90Prime imager on the 2.3 m Bok telescope at Kitt Peak. It is a four-year collaboration between the National Astronomical Observatory of China and Steward Observatory, the University of Arizona, serving as one of the three imaging surveys to provide photometric input catalogs for target selection of the Dark Energy Spectroscopic Instrument (DESI) project. BASS will take up to 240 dark/grey nights to cover an area of about 5400 deg$^2$ in the $g$ and $r$ bands. The 5$\sigma$ limiting AB magnitudes for point sources in the two bands, corrected for the Galactic extinction, are 24.0 and 23.4 mag, respectively. BASS, together with other DESI imaging surveys, will provide unique science opportunities that cover a wide range of topics in both Galactic and extragalactic astronomy., Comment: 10 pages, submitted to PASP

Virtual Observatory (VO) is a data-intensively online astronomical research and education environment, which takes advantages of advanced information technologies to achieve seamless and global access to astronomical information. AstroCloud is a cyber-infrastructure for astronomy research initiated by Chinese Virtual Observatory (China-VO) project, and also a kind of physical distributed platform which integrates lots of tasks such as telescope access proposal management, data archiving, data quality control, data release and open access, cloud based data processing and analysis. It consists of five application channels, i.e. observation, data, tools, cloud and public and is acting as a full lifecycle management system and gateway for astronomical data and telescopes. Physically, the platform is hosted in six cities currently, i.e. Beijing, Nanjing, Shanghai, Kunming, Lijiang and Urumqi, and serving more than 17 thousand users. Achievements from international Virtual Observatories and Cloud Computing are adopted heavily. In the paper, backgrounds of the project, architecture, Cloud Computing environment, key features of the system, current status and future plans are introduced., Comment: 5 pages, 8 figures, to appear in the Proceedings of "The 3rd International Conference on Wireless Communication and Sensor Network (WCSN 2016)"

We propose and preliminarily implement a data-mining based platform to assist ex- perts to inspect the increasing amount of spectra with low signal to noise ratio (SNR) generated by large sky surveys. The platform includes three layers: data-mining layer, data-node layer and expert layer. It is similar to the GalaxyZoo project and VO-compatible. The preliminary experiment suggests that this platform can play an effective role in managing the spectra and assisting the experts to inspect a large number of spectra with low SNR. With the telescopes established and the surveys ongoing, such as the Guoshoujing telescope (LAMOST, Zhao 1999), more and more spectra are collected and released. Unfortunately, except the qualified data, there still exist many spectra unclassified by the automated pipeline. Usually most of these spectra are too low SNR to be classified because of the limited magnitude of the instruments or other reasons. Some important new discoveries are probably hidden in these unknown spectra. Therefore, we should not give up these seemingly useless data, even though they are quite defective. How to handle these unknown spectra is one of the biggest challenges to the modern statistics and data mining techniques as well as eyeball check. In order to ensure the accuracy of the results, we have to motivate experts to check these spectra by visual inspection. Owing to huge amount of such spectra generated continuously by the large sky surveys, it will spend much time and efforts to check spectra one by one. Consequently, a platform to efficiently manage and coarsely classify these unqualified data is in great requirement for the large surveys.

We present seeing measurements of the Guoshoujing Telescope (formerly named the Large Sky Area Multi-Object Fiber Spectroscopic Telescope- LAMOST) site at Xinglong station during the period from 2007 March 12 to April 25. The mea- surements were carried out with the Differential Image Motion Monitor (DIMM), and a total of 9259 data sets was obtained. The median seeing was measured to be 1.1 '' , with 25% being better than 0.8 '' and 75% better than 1.5 '' . The experiment shows that the DIMM exposure time has significant effects on the res ults of seeing mea- surements. An SBIG Polaris seeing monitor, which had been planned to be installed on the LAMOST site for long-term monitoring, was also employed during the DIMM observations. The results show that the SBIG seeing monitor is easily affected by gusty wind, resulting in larger seeing values. Considering the pr evious seeing measurements at Xinglong station over the last 15 yr, we conclude that an acceptable seeing condition at Xinglong station is around 1 '' -2 '' .

The SCUSS is a deep $u$-band imaging survey in the south Galactic cap using the 2.3m Bok telescope. The survey observations were completed in the end of 2013, covering an area of about 5000 square degrees. We release the data in the region with an area of about 4000 deg$^2$ that is mostly covered by the Sloan digital sky survey. The data products contain calibrated single-epoch images, stacked images, photometric catalogs, and a catalog of star proper motions derived by Peng et al, 2015. The median seeing and magnitude limit ($5\sigma$) are about 2".0 and 23.2 mag, respectively. There are about 8 million objects having measurements of absolute proper motions. All the data and related documentations can be accessed through the SCUSS data release website of \url{http://batc.bao.ac.cn/Uband/data.html}., Comment: 13 pages, 7 figures, accepted by AJ

The South Galactic Cap u-band Sky Survey (SCUSS) is a deep u-band imaging survey in the Southern Galactic Cap, using the 90Prime wide-field imager on the 2.3m Bok telescope at Kitt Peak. The survey observations started in 2010 and ended in 2013. The final survey area is about 5000 deg2 with a median 5-sigma point source limiting magnitude of about 23.2. This paper describes the survey data reduction process, which includes basic imaging processing, astrometric and photometric calibrations, image stacking, and photometric measurements. Survey photometry is performed on objects detected both on SCUSS u-band images and in the SDSS database. Automatic, aperture, point-spread function (PSF), and model magnitudes are measured on stacked images. Co-added aperture, PSF, and model magnitudes are derived from measurements on single-epoch images. We also present comparisons of the SCUSS photometric catalog with those of the SDSS and CFHTLS., 24 pages, 20 figures, published online (AJ, 150, 104)

We study the integral Galactic extinction and reddening based on the galaxy catalog of the South Galactic Cap U-band Sky Survey (SCUSS), where $u$ band galaxy number counts and $u-r$ color distribution are used to derive the Galactic extinction and reddening respectively. We compare these independent statistical measurements with the reddening map of \citet{Schlegel1998}(SFD) and find that both the extinction and reddening from the number counts and color distribution are in good agreement with the SFD results at low extinction regions ($E(B-V)^{SFD}0.12$ mag), the SFD map overestimates the Galactic reddening systematically, which can be approximated by a linear relation $��E(B-V)= 0.43[E(B-V)^{SFD}-0.12$]. By combing the results of galaxy number counts and color distribution together, we find that the shape of the Galactic extinction curve is in good agreement with the standard $R_V=3.1$ extinction law of \cite{ODonnell1994}.

Data access and interoperability module connects the observation proposals, data, virtual machines and software. According to the unique identifier of PI (principal investigator), an email address or an internal ID, data can be collected by PI's proposals, or by the search interfaces, e.g. conesearch. Files associated with the searched results could be easily transported to cloud storages, including the storage with virtual machines, or several commercial platforms like Dropbox. Benefitted from the standards of IVOA (International Observatories Alliance), VOTable formatted searching result could be sent to kinds of VO software. Latter endeavor will try to integrate more data and connect archives and some other astronomical resources., Comment: 4 pages, 4 figures, to be published in ADASS XXIV Proceedings. 5-9 October 2014 in Calgary, Canada

We present preliminary results of the quasar survey in Large Sky Area Multi- Object Fiber Spectroscopic Telescope (LAMOST) first data release (DR1), which includes pilot survey and the first year regular survey. There are 3921 quasars identified with reliability, among which 1180 are new quasars discovered in the survey. These quasars are at low to median redshifts, with highest z of 4.83. We compile emission line measurements around the H{\alpha}, H{\beta}, Mg II, and C IV regions for the new quasars. The continuum luminosities are inferred from SDSS photo- metric data with model fitting as the spectra in DR1 are non-flux-calibrated. We also compile the virial black hole mass estimates, and flags indicating the selec- tion methods, broad absorption line quasars. The catalog and spectra for these quasars are available online. 28% of the 3921 quasars are selected with optical- infrared colours independently, indicating that the method is quite promising in completeness of quasar survey. LAMOST DR1 and the on-going quasar survey will provide valuable data in the studies of quasars., Comment: accepted for publication in AJ

Although the roles of data centers and computing centers are becoming more and more important, and on-line research is becoming the mainstream for astronomy, individual research based on locally hosted data is still very common. With the increase of personal storage capacity, it is easy to find hundreds to thousands of FITS files in the personal computer of an astrophysicist. Because Flexible Image Transport System (FITS) is a professional data format initiated by astronomers and used mainly in the small community, data management toolkits for FITS files are very few. Astronomers need a powerful tool to help them manage their local astronomical data. Although Virtual Observatory (VO) is a network oriented astronomical research environment, its applications and related technologies provide useful solutions to enhance the management and utilization of astronomical data hosted in an astronomer's personal computer. FITSManager is such a tool to provide astronomers an efficient management and utilization of their local data, bringing VO to astronomers in a seamless and transparent way. FITSManager provides fruitful functions for FITS file management, like thumbnail, preview, type dependent icons, header keyword indexing and search, collaborated working with other tools and online services, and so on. The development of the FITSManager is an effort to fill the gap between management and analysis of astronomical data., Comment: 12 pages, 9 figures, Accepted for publication in New Astronomy

With the implementation of many ambitious observation projects, including LAMOST, FAST, and Antarctic observatory at Doom A, observational astronomy in China is stepping into a brand new era with emerging data avalanche. In the era of e-Science, both these cutting-edge projects and traditional astronomy research need much more powerful data management, sharing and interoperability. Based on data-grid concept, taking advantages of the IVOA interoperability technologies, China-VO is developing a VO-driven astronomical data grid environment to enable multi-wavelength science and large database science. In the paper, latest progress and data flow of the LAMOST, architecture of the data grid, and its supports to the VO are discussed., Comment: 4 pages, 3 figures. To appear in Proc. ADASS XIX (Sapporo, Japan, 2009)

Astronomy research has entered an increasingly data-intensive, or “big data” era. Exponential growth in the size of astronomical archives brings with it completely new requirements and challenges for data storage, computing power, networks, software, algorithms, and even research methods. Astronomers and experts in information and computation technology (ICT) are working together to simplify knowledge discovery within these massive data sets. Worldwide astronomical archives are connected through the virtual observatory (VO) framework, which provides interoperability standards and services that have allowed the creation of a global astronomical data grid. Astroinformatics, a bridge between astronomy and ICT and applied computer science, aims to engage a broader community of researchers both as contributors to and as consumers of the new methodology for data-intensive astronomy, thus building upon the data-grid foudations established by the VO framework. Data mining (DM), knowledge discovery in databases (KDD), machine learning, and visualization techniques have become a necessity. In this paper, the challenges facing modern astronomical research are briefly described, the concepts underlying the VO and astroinformatics and the latest progress in these fields are introduced, and the need for DM and KDD techniques in astronomy is discussed.

The Chinese Astronomical Data Center (CAsDC) is a member of World Data System, hosted at National Astronomical Observatories, Chinese Academy of Sciences(NAOC). The CAsDC keeps close collaboration with IVOA, WDS and CODATA. The whole set of LAMOST data, including raw data and data products, are hosted at the CAsDC. Data resources and services of the CAsDC are introduced.

As the cyber-infrastructure for Astronomical research from Chinese Virtual Observatory (China-VO) project, AstroCloud has been archived solid progresses during the last one year. Proposal management system and data access system are re-designed. Several new sub-systems are developed, including China-VO PaperData, AstroCloud Statics and Public channel. More data sets and application environments are integrated into the platform. LAMOST DR1, the largest astronomical spectrum archive was released to the public using the platform. The latest progresses will be introduced., 4 pages, 4 figures, ADASS XXV Proceedings

AstroCloud is a cyber-Infrastructure for Astronomy Research initiated by Chinese Virtual Observatory (China-VO) under funding support from NDRC (National Development and Reform commission) and CAS (Chinese Academy of Sciences). The ultimate goal of this project is to provide a comprehensive end-to-end astronomy research environment where several independent systems seamlessly collaborate to support the full lifecycle of the modern observational astronomy based on big data, from proposal submission, to data archiving, data release, and to in-situ data analysis and processing. In this paper, the architecture and key designs of the AstroCloud platform are introduced, including data access middleware, access control and security framework, extendible proposal workflow, and system integration mechanism., Comment: 4 pages, 4 figures, to be published in ADASS XXIV Proceedings. 5-9 October 2014 in Calgary, Canada

The Large sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) is the largest optical telescope in China. In last four years, the LAMOST telescope has published four editions data (pilot data release, data release 1, data release 2 and data release 3). To archive and release these data (raw data, catalog, spectrum etc), we have set up a data cycle management system, including the transfer of data, archiving, backup. And through the evolution of four software versions, mature established data release system., 4 pages, 4 figures, ADASS XXV Proceedings