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Hello!

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Title: Hello!


1
Hello!
2
Virtual Observatories
Ajit Kembhavi IUCAA Pune, India
3
Data Storage and Retrieval
The Astronomer Vermeer 1632-1675
The Library of Alexandria 3rd
Century BC
4
The Data Avalanche
Immense amounts of data are being produced by
large telescopes using large area detectors.
Terabytes of data are now available, and
Petabytes will soon be available from frequent
all sky imaging.
Vast databases are also being produced through
simulations.
5
Astronomical Data Explosion
100 Gb/night
P. Quinn
6
Data Explosion
Peter Quinn
7
Wavelength Coverage
The data spans the electromagnetic spectrum from
the radio to the gamma-ray region.
Obtaining, analysing and interpreting the data in
different wavebands involves highly specialised
instruments and techniques.
The astronomer needs new tools for using this
wealth of data in multiwavelength studies.
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Stars in the Milky Way
10
The Hertzsprung-Russell Diagram
11
The Alliance
Members of the IVOA
12
Interactions
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Virtual Observatories
  • Provide tools for data analysis, visualization
    and mining.
  • Develop interoperability concepts to make
    different databases seamless.
  • Manage vast data resources and provide these
    on-line to astronomers and other users.
  • Empower astronomers by providing sophisticated
    query and computational tools, and computing
    grids for producing new science.

15
IVOA Technology Initiatives
  • The IVOA has identified six major
    technical initiatives to fulfill the scientific
    goal of the VO concept.

IVOA-LISTS
16
  • REGISTRIES These collect metadata about
    data resources and information services into a
    queryable database. The registry is distributed.
    A variety of industry standards are being
    investigated.
  • DATA MODELS This initiative aims to define
    the common elements of astronomical data
    structures and to provide a framework to describe
    their relationships.
  • UNIFORM CONTENT DESCRIPTORS These will
    provide the common language for for metadata
    definitions for the VO.

17
  • DATA ACCESS LAYER This provides a
    standardized access mechanisms to distributed
    data objects. Initial prototypes are a Cone
    Search Protocol and a simple Image Access
    Protocol.
  • VO QUERY LANGUAGE This will provide a
    standard query language which will go beyond the
    limitations of SQL.
  • VOTable This is an XML mark-up standard for
    astronomical tables.

18
Science Initiatives
  • Many IVOA projects have active Science Working
    Groups consisting of astronomers from a broad
    cross-section of the community representing all
    wavelengths.
  • The focus here is to develop a clear perception
    of the scientific requirements of a VO.
  • Projects within the working groups will develop
    new capabilities for VO based analysis.
  • This will enable the community to create new
    research programs and to publish their data and
    research in a more pervasive and scientifically
    useful manner.

19
Virtual Observatory -India
A collaboration between IUCAA and PSPL, with a
grant from the Ministry of Communications and
Information Technology
20
IUCAA
21
Persistent Systems Pvt. Ltd., Pune
22
Virtual Observatory - India
23
Data Archives and Mirrors at VO-I
SDSS 2Mass 2DFGRS
2QZ
FIRST
NVSS
Chandra
Vizier, Aladin, ADS

24
Fast Computing
Four alpha server ES-45 nodes, each
with 4 processors, each node with 8 GB
RAM Fast, Low latency interconnect Memory
Channel Architecture Trucluster clustering
environment (Tru64 Unix, DecMPI, openMP)
25
VO-India Software Projects
VOPlot Visualizer for catalogue data VOTable
C Parser VOTable Streaming writer
Data Converters Fits
Browser User interfaces and
query tools Applications
beyond astronomy All tools have web-based and
stand alone versions
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The VOPlot Collaboration
Visualization and simple statistics of catalogue
data. Integration with sky atlases.
28
The VOPlot Tool
  • A VO-I CDS collaboration
  • First conceived as a web-based tool for Vizier
  • Then integrated with Aladin
  • VOPlot is now also a stand alone system
  • It has been integrated with many data
    bases

VOPlot
Sonali Kale, K.D. Balaji et. Al.
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Colour-magnitude diagram
parallax
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Catalog Data Interface Tool
  • A tool to query catalog data.
  • Simple, customizable, graphic interface.
  • Not specific to type of data or
    catalogue.
  • SQL queries for expert users.
  • VO tools available for
    analysis
  • VOPlot, Aladin, VOStat, SIMBAD, NED...

40
Data Organization and Architecture
41
Browse Server Database

Back
42
Create Views

Back
43
On-the-fly GUI

Back
44
Query using a Form

Back
45
Query using SQL Directly

Back
46
Results in VOPlot

Back
47
Results in Aladin

Back
48
Himalaya Chandra Telescope Data Archives
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SDSS J125637-022452 High proper motion L-subdwarf
Optical spectra of mixed late M and mid L
type Only the third L subdwarf known
52
Positions 1986-2000
Proper motion 0.617 arcsec / yr
53
Thank You
54
AVO Prototype Demo Astrogrid Astronomy Catalogue
Extractor AVO AladinSED VO-IndiaVOPlot
55
FITS Manager
View, create and add to FITS files Convert to
other formats Pallavi Kulkarni
Fits-manager
56
VOTable Java Streaming Writer
Acts on a data array in memory to convert it to
the VOTable form, which is streamed row by
row to an output file. Very large VOTables can
be written without excessive memory. Pallavi
Kulkarni
VOTable-Java
57
VOTable
  • This is a new data exchange standard produced
    through efforts led by Francois Ochsenbien of
    CDS, Strasbourg and Roy Williams of Caltech.
  • VOTable is in XML format. Physical quantities
    come with sophisticated semantic information.

58
VOTable
  • The format enables computers to easily parse the
    information and communicate it to other
    computers.
  • Federation and joining of information become
    possible and Grid computing is easier.
  • VOTable parsers have been developed in Perl, Java
    and C.
  • Enhancements and extensions are being considered.

Streaming Parser
Non-streaming Parser
59
VOTable Data
  • The data part in a VOTable may be represented
    using one of three different formats
  • FITS VOTable can be used either to encapsulate
    FITS files, or to re-encode the metadata.
  • BINARY Supported for efficiency and ease of
    programming, no FITS library is required, and the
    streaming paradigm is supported.
  • TABLEDATA Pure XML format for small tables.

60
C VOTable Parser
  • Motivation
  • Provide a library for API based access to VOTable
    files.
  • APIs can be directly used to develop VOTable
    applications without having to do raw VOTable
    processing.
  • Streaming and Non-streaming versions are
    available.

Sonali Kale, Sudip Khanna
61
C VOTable Parser
  • Salient Features
  • Implemented as a wrapper over XALAN-C.
  • XALAN-C is a robust implementation of the W3C
    recommendations for
  • XSL Transformations (XSLT) and the
  • XML Path language (XPath).
  • XPath queries can be used to access the VOTable
    data.

62
Project Design
VTable
Metadata
Link Collection
Link
Field
Field Collection
Link
Link Collection
Values
Table Data
minimum
Row Collection
maximum
Row
Option Collection
Column Collection
Options
63
IUCAA HPC Facility Hercules
  • HPC Team
  • Sarah Ponthratnam
  • Sunu Engineer
  • Rajesh Nayak
  • Anand Sengupta
  • Co-proposed by
  • Ajit Kembhavi
  • T. Padmnabhan
  • Tarun Souradeep
  • Four Alpha Server ES-45 machines
  • Each with 4 processors Alpha (21264C)
  • 1.25 GHz clock speed
  • Cache on chip 64 Kb I, 64 Kb-D
  • Cache 16 Mb ECC DDR
  • RAM 3 x 8 Gb 12 Gb
  • Fast, Low latency interconnect
  • Memory channel Architecture (MCA)
  • High volume Storage
  • 1 Tera-byte SCSCI
  • Trucluster clustering environment (Tru64 Unix,
    DecMPI, openMP)

gt 30 G flops Preliminary HPL benchmark
ES-45 Specfp2000 1327 Linpack 1000x1000 6847
64
Virtual Observatory - India
Persistent Systems
IUCAA
65
Caltech, Fermilab, JHU, NASA/HEARC, Microsoft,
NCSA/UIUC, NOAO, NRAO, Raytheon ITS, SDSC/UCSD,
SAO/CXC, STScI, UPenn, UPitts/CMU, UWis, USC,
USNO, USRA, CVO
  • NVO-People

66
Virtual Observatory - India
Ajit Kembhavi Inter-University Centre for
Astronomy and Astrophysics Pune, India

67
Virtual Observatories
  • Provide tools for data analysis, visualization
    and mining.
  • Develop interoperability concepts to make
    different databases seamless.
  • Manage vast data resources and provide these
    on-line to astronomers and other users.
  • Empower astronomers by providing sophisticated
    query and computational tools, and computing
    grids for producing new science.

68
Terapix
Jodrell Bank
69
Registry and DIS
70
High Volume Storage
Raid 5, 4 Terabyte
71
CVO Collaborations
  • There are three major projects at the CVO
    involving collaborations with other VO.
  • CVO is collaborating with the German
    Astrophysical VO to incorporate ROSAT X-ray data
    and catalogues into the CVO system.
  • CVO is collaborating with the Australian VO.to
    incorporate 2Qz and 2DF galaxy spectra into the
    CVO database.
  • CVO is an associate member of NVO and is have put
    in place some components of the NVO galaxy
    morphology demo.

72
Science Initiatives
  • Many IVOA projects have active Science Working
    Groups consisting of astronomers from a broad
    cross-section of the community representing all
    wavelengths.
  • The focus here is to develop a clear perception
    of the scientific requirements of a VO.
  • Projects within the working groups will develop
    new capabilities for VO based analysis.
  • This will enable the community to create new
    research programs and to publish their data and
    research in a more pervasive and scientifically
    useful manner.

73
Australian VO Collaborations
  • The distributed volume renderer (dvr) software,
    is a tool for rendering large volumetric data
    sets using the combined memory and processing
    resources of Beowulf like clusters.
  • A collaboration between the Melbourne site of
    Aus-VO and AstroGrid aims to develop the existing
    dvr software into a grid-based volume rendering
    service.
  • Users will be able to select FITS-format cubes
    from a number of "Data Centres",have the data
    transferred to a chosen rendering cluster, and
    then proceed to visualise the volume of data
    remotely (See Demo).

74
C VOTable Parser
  • Initial version
  • - Released on May 31st , 2002.
  • - Support only for reading of tables.
  • - Support only for pure-XML TABLEDATA and not
    for BINARY or FITS data streams.
  • - Runs on Windows NT 4.0, Windows 2000 and
  • RedHat Linux 7.1.
  • Future enhancements
  • - Can be incorporated quickly and
    efficiently.

75
Parser Design
  • Class Details
  • VTable In memory representation of a single
    ltTABLEgt
  • from the ltRESOURCEgt element in VOTable
  • TableMetaData Contains MetaData (Fields, Links
    and Description)
  • Resource Represents the ltRESOURCEgt element in
    the VOTable.
  • TableData Contains Rows
  • Field Representation of ltFIELDgt from VOTable
  • Row Representation of ltTRgt from VOTable
  • Column Representation of ltTDgt from VOTable

76
Parser Design
  • API Typical Operations
  • File Level I/O Routines
  • Open VOTable file
  • Close VOTable file
  • Table I/O Operations
  • Get number of rows
  • Get number of columns
  • Get column(field) information (column name,
    column number, etc.)
  • Accessing table data

77
Parser Implementation
  • Development on Windows NT 4.0 platform using
    VC. Ported to RedHat Linux 7.1/gcc-2.96 with
    zero effort.
  • 18 C classes representing various elements of
    the VOTable format.
  • 8500 lines of C code written for V1.1 release
  • Project start date April 7th 2002
  • V1.1 Release May 31st 2002
  • Current status V1.2 design in progress

78
What is in Release V1.1
  • Parser to serve as a building block for
    developing VOTable based applications.
  • Can be easily used by users of CFITSIO library.
  • Supports powerful XPath queries against VOTable
    files.
  • The first version of the VO Table parser can now
    be downloaded
  • http//vo.iucaa.ernet.in/voi/html/infopage.h
    tml

79
VOTable Parser Demo
  • Serves as a tutorial to help understand the basic
    APIs provided by the VOTable parser.
  • Demonstrates how to access the data and metadata
    elements of a VOTable file.

80
Future Work
  • Develop APIs for writing data in VOTable format.
  • Develop APIs for supporting IMAGE data and FITS
    files in VOTable.
  • Enhance existing API set to allow more elaborate
    and flexible operations on VOTable files.
  • Support future VOTable versions.
  • Develop applications for conversion between FITS
    and VOTable formats.

81
References
  • The first version of the C parser can now be
    downloaded from the VO-India website
  • http//vo.iucaa.ernet.in/voi
  • VOTable Details
  • http//vizier.u-strasbg.fr/doc/VOTable/
  • XALAN
  • http//xml.apache.org/xalan-c/index.html
  • XPATH
  • http//www.w3.org/TR/xpath

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Virtual Observatory - India
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Star Positions
88
  • REGISTRIES These collect metadata about data
    resources and information services into a
    queryable database. The registry is distributed.
    A variety of industry standards are being
    investigated.
  • DATA MODELS This initiative aims to define the
    common elements of astronomical data structures
    and to provide a framework to describe their
    relationships.
  • UNIFORM CONTENT DESCRIPTORS These will provide
    the common language for for metadata definitions
    for the VO.

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VO Schema
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