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Theory Standards for the Virtual Observatory

Theory Standards for the Virtual Observatory. SimDB + SimDAP. John Hibbard http://www.cv.nrao.edu/~jhibbard/n4038/n4038.html. NASA/CXC/SAO/G. Fabbiano et al. gas pressure. electron density. gas temperature. Courtesy Alexis Finoguenov, Ulrich Briel, Peter Schuecker, (MPE).

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Theory Standards for the Virtual Observatory

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  1. Theory Standards for the Virtual Observatory SimDB + SimDAP

  2. John Hibbard http://www.cv.nrao.edu/~jhibbard/n4038/n4038.html NASA/CXC/SAO/G. Fabbiano et al. gas pressure electron density gas temperature Courtesy Alexis Finoguenov, Ulrich Briel, Peter Schuecker, (MPE) Complex observations ...

  3. ... require complex models Courtesy Volker Springel Toomre & Toomre, 1972 Courtesy Volker Springel Di Matteo, Springel and Hernquist, 2005

  4. Survey planning Model fitting Observed galaxy catalogues and synthetic counterparts from Millennium Run see: http://www.mpa-garching.mpg.de/millennium HST observation of the PN central star LSV4621 vs. a theoretical SED which considers all elements H - Ni. Courtesy Thomas Rauch

  5. Existing DAL standardscan be used, sometimes • If end products similar • SSAP • theory spectra • SCS-like • mock catalogues • SIAP-like • visualisation services

  6. New, theory specific standards in progress: SimDB + SimDAP • Discovery: Simulation Database (SimDB) • Publish • Describe • Search • Compare • Access: Simulation Data Access Protocol (SimDAP) • Retrieve • Filter • Analyse • Visualise • Combine

  7. SimDB • Supports discovery of interesting simulation results. • and links to (SimDAP) services for accessing them • Rich data model describing simulations and post-processing products • Focused on 3+1D simulations • but easily extended

  8. SimDB approach • Build a model containing the required features • Create representations in standard modelling languages • Define access services for publishing and querying • Here we explain the model in some detail. • See http://code.google.com/p/volute/wiki/TheoryHome for details

  9. Model must support common questions • What was simulated? • LSS, galaxy merger, rings of Saturn • What physics was included? • gravity only, hydrodynamics, chemistry • How is the world represented? • N bodies, adaptive mesh, spherically symmetric 1D • What properties are calculated? • position, velocity, mass, temperature, density, chemical abundances • How do I get access? • etc.

  10. File Somewhere there is a file containing data of interest

  11. The data may also reside in a database. In general, there is some storage container somewhere. Storage

  12. In our model, the data is of interest because it is the result of an astronomical experiment. Results of Experiments

  13. For SimDB, we consider for example Simulation and ClusterExtraction as special cases of such experiments. We could also consider observations, but that is a different model. Experiments

  14. Experiments are performed according to a well defined protocol. Examples of this are simulator codes. The same protocol can be reused for describing many experiments done with it. Protocol

  15. Protocols define input parameters, different experiments will give different values to these parameters. Parameters

  16. For search purposes it is important to be able to describe the goal of an experiment. We model this using a collection of targets. These describe scientific content of the experiments. E.g. a galaxy merger was simulated, or a stellar spectrum. Target

  17. In reality the results of experiments are hardly ever stored simply, in a standardised manner. So we introduce web services that can be called to access specific experiments and their results. Web service

  18. The SimDB data model (in progress) The SimDB ata model deviates in the details, but the philosophy is the same.

  19. The SimDB data model is not more complex than other models in the VO. Complex? Registry data model Spectrum Data Model STC SDSS SkyServer etc.

  20. To work with the model we need ot define representations of it in specific languages. Representations • (Generated)* • XML Schemas • Protocol: PDR code (courtesy Franck LePetit + Laurent Bourges) • Simulation: Millennium Run • Ideally generated from simulation and post-processing pipe-lines • Relational Database Schema • Java code • HTML * http://code.google.com/p/volute/wiki/TheoryHome

  21. E.g.: XML Representation

  22. Implementation prototypes • CNRS • GalMER: http://galmer.obspm.fr/ • ITVO • Trieste: http://wwwas.oats.inaf.it/IA2/ITVO • Catania: http://itvo.oact.inaf.it • Under development • SimCat (UCSD) • PDR/SimDB (Paris) • Horizon/GalICS (Lyon) • MPA Simulations (GAVO, Generated)

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