IVOA Provenance data model: hints from the CTA Provenance prototype

We present the last developments on the IVOA Provenance data model, mainly based on the W3C PROV concept. In the context of the Cherenkov astronomy, the data processing stages imply both assumptions and comparison to dedicated simulations. As a consequence, Provenance information is crucial to the end user in order to interpret the high level data products. The Cherenkov Telescope Array (CTA), currently in preparation, is thus a perfect test case for the development of an IVOA standard on Provenance information. We describe general use-cases for the computational Provenance in the CTA production pipeline and explore the proposed W3C notations like PROV-N formats, as well as Provenance access solutions.Comment: 4 pages, 3 figures, to appear in ADASS XXV proceedings, edited by N. P. F. Lorente, & K. Shortridge (San Francisco: ASP), ASP Conf. Se

Implementation feedback of the IVOA Provenance data model

The IVOA Provenance Data model defines entities, agents and activities as container classes to describe the provenance of datasets, with the executed tasks and responsibilities attached to agents. It also provides a set of classes to describe the activities type and their configuration template, as well as the configuration applied effectively during the execution of a task. Here we highlight lessons learned in the implementation of the CDS ProvHiPS service distributing provenance metadata for the HST HiPS data collections, and for the HST archive original images used to produce the HiPS tiles. ProvHiPS is based on the ProvTAP protocol, the emerging TAP standard for distributing provenance metadata. ProvTAP queries may rapidly become very complex. Various graph representation strategies, including ad hoc solutions, triplestore and SQL CTE have been considered and are discussed shortly.Comment: 4 pages, to appear in proceedings of ADASS XXIX, ASP Conf. Serie

Radio Astronomy visibility data discovery and access using IVOA standards

Enhancing interoperable data access to radio data has become a science priority within the International Virtual Observatory Alliance (IVOA). This lead to the foundation of the IVOA Radio astronomy Interest Group. Several radio astronomers and project scientists enrolled in various projects (NRAO, ASKAP, LOFAR, JIVE, ALMA, SKA, INAF, NenuFAR, etc.) have joined. Together they are paving the way to a better integration of their services in the virtual observatory (VO) infrastructure and propose extension of IVOA standards to help achieving this goal. Calibrated radio datasets such as cubes, images, spectra and time series can already be searched and retrieved using the ObsCore/ObsTAP specification defined in the IVOA, or by data product-specific services like SIAv2, SODA, SSA and ConeSearch. However, properties of radio visibility data are not fully implemented in the VO landscape yet. We need specific features to refine data discovery and selection that are adapted to radio astronomers' need. In this context the VO team at the Centre de Donn\'{e}es astronomiques de Strasbourg (CDS) proposes to consider the ObsCore/ObsTAP specification and to establish cross-walks between the ObsCore and the existing Measurement Set (MS) metadata profile for data discovery of radio visibility data (VD). In order to account for the difference in granularity between radio VD datasets and science-ready datasets of the VO, the approach splits a MS data file into a list of datasets served by an ObsTAP service, thus enabling coarse grain discovery in the multi-wavelength context. Radio specific metadata such as number of antennae, frequency ranges, $uv$ plane coverage plots, frequency-phase and frequency-amplitude plots, primary and synthesized beams are also provided either by adding column metadata or by using the DataLink technique.Comment: 4 pages, 2 figures, ADASS XXX Conference Proceedings Nov 202

IVOA Recommendation: Data Model for Astronomical DataSet Characterisation

This document defines the high level metadata necessary to describe the physical parameter space of observed or simulated astronomical data sets, such as 2D-images, data cubes, X-ray event lists, IFU data, etc.. The Characterisation data model is an abstraction which can be used to derive a structured description of any relevant data and thus to facilitate its discovery and scientific interpretation. The model aims at facilitating the manipulation of heterogeneous data in any VO framework or portal. A VO Characterisation instance can include descriptions of the data axes, the range of coordinates covered by the data, and details of the data sampling and resolution on each axis. These descriptions should be in terms of physical variables, independent of instrumental signatures as far as possible. Implementations of this model has been described in the IVOA Note available at: http://www.ivoa.net/Documents/latest/ImplementationCharacterisation.html Utypes derived from this version of the UML model are listed and commented in the following IVOA Note: http://www.ivoa.net/Documents/latest/UtypeListCharacterisationDM.html An XML schema has been build up from the UML model and is available at: http://www.ivoa.net/xml/Characterisation/Characterisation-v1.11.xsdComment: http://www.ivoa.ne

The ALADIN Interactive Sky Atlas

The Aladin interactive sky atlas, developed at CDS, is a service providing simultaneous access to digitized images of the sky, astronomical catalogues, and databases. The driving motivation is to facilitate direct, visual comparison of observational data at any wavelength with images of the optical sky, and with reference catalogues. The set of available sky images consists of the STScI Digitized Sky Surveys, completed with high resolution images of crowded regions scanned at the MAMA facility in Paris. A Java WWW interface to the system is available at: http://aladin.u-strasbg.fr/Comment: 8 pages, 3 Postscript figures; to be published in A&

IVOA Recommendation: IVOA Photometry Data Model

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