Evolution of the IVOA Characterisation Data Model

TL;DR

This paper presents an updated version of the IVOA Characterisation Data Model, enhancing its ability to describe complex observational datasets with detailed coverage, resolution, and sampling information across various physical axes.

Contribution

The paper introduces a new version of the IVOA Characterisation Data Model that better captures detailed variations and includes new axes for photometry, velocity, and polarimetry, addressing evolving user needs.

Findings

Improved description of variation maps for coverage, resolution, and sampling.

Addition of new axes for photometric measurements, velocity, and polarimetry.

Enhanced support for complex, composed datasets.

Abstract

The Characterisation data model is a standard of the International Virtual Observatory Alliance (IVOA) that describes observational datasets in the multi-dimensional parameter space. Defining three properties: coverage, resolution, and sampling along different physical axes (e.g. spatial, spectral, flux) with variable level of details for the description, this model has been used in several IVOA contexts: Simple Spectral Access Protocol, Spectrum Data Model, ObsTAP (Table Access Protocol for the Core Components of the Observation Data Model. Here we propose a new version which addresses more completely the most detailed level of description (level 4) dealing with variation maps of coverage, resolution, and sampling. It also introduces new specific axes in order to cover various photometric measurements, velocity and polarimetry. Special care is given for composed data sets. These improvements and add-ons follow the evolution of needs expressed to the uptake of VO tools in various observation domains for data discovery but also for data analysis requirements. This is also introduced to tackle use-cases designed to analyse scientifically datasets in the V0 context together with calibration/provenance information.