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Register a new userIVOA Recommendation: IVOA Document Standards Version 1.2
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This document describes the types of official IVOA documents and the process by which documents are advanced from Working Drafts to formal Recommendations.
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This document describes the linking of data discovery metadata to access to the data itself, further detailed metadata, related resources, and to services that perform operations on the data. The web service capability supports a drill-down into the details of a specific dataset and provides a set of links to the dataset file(s) and related resources. This specification also includes a VOTable-specific method of providing descriptions of one or more services and their input(s), usually using parameter values from elsewhere in the VOTable document. Providers are able to describe services that are relevant to the records (usually datasets with identifiers) by including service descriptors in a result document.
This document discusses the definition of the Parameter Description Language (PDL). In this language parameters are described in a rigorous data model. With no loss of generality, we will represent this data model using XML. It intends to be a expressive language for self-descriptive web services exposing the semantic nature of input and output parameters, as well as all necessary complex constraints. PDL is a step forward towards true web services interoperability.
The IVOA VOEvent Recommendation defines a means of describing transient celestial events but, purposely, remains silent on the topic of how those descriptions should be transmitted. This document formalizes a TCP-based protocol for VOEvent transportation that has been in use by members of the VOEvent community for several years and discusses the topology of the event distribution network. It is intended to act as a reference for the production of compliant protocol implementations.
The Photometry Data Model (PhotDM) standard describes photometry filters, photometric systems, magnitude systems, zero points and its interrelation with the other IVOA data models through a simple data model. Particular attention is given necessarily to optical photometry where specifications of magnitude systems and photometric zero points are required to convert photometric measurements into physical flux density units.
The Simple Spectral Access (SSA) Protocol (SSAP) defines a uniform interface to remotely discover and access one dimensional spectra. SSA is a member of an integrated family of data access interfaces altogether comprising the Data Access Layer (DAL) of the IVOA. SSA is based on a more general data model capable of describing most tabular spectrophotometric data, including time series and spectral energy distributions (SEDs) as well as 1-D spectra; however the scope of the SSA interface as specified in this document is limited to simple 1-D spectra, including simple aggregations of 1-D spectra. The form of the SSA interface is simple: clients first query the global resource registry to find services of interest and then issue a data discovery query to selected services to determine what relevant data is available from each service; the candidate datasets available are described uniformly in a VOTable format document which is returned in response to the query. Finally, the client may retrieve selected datasets for analysis. Spectrum datasets returned by an SSA spectrum service may be either precomputed, archival datasets, or they may be virtual data which is computed on the fly to respond to a client request. Spectrum datasets may conform to a standard data model defined by SSA, or may be native spectra with custom project-defined content. Spectra may be returned in any of a number of standard data formats. Spectral data is generally stored externally to the VO in a format specific to each spectral data collection; currently there is no standard way to represent astronomical spectra, and virtually every project does it differently. Hence spectra may be actively mediated to the standard SSA-defined data model at access time by the service, so that client analysis programs do not have to be familiar with the idiosyncratic details of each data collection to be accessed.
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