Iris: an Extensible Application for Building and Analyzing Spectral Energy Distributions

TL;DR

Iris is a flexible, user-friendly application that enables astronomers to build, explore, and model spectral energy distributions by integrating data and models through a modular, standards-based platform.

Contribution

The paper introduces Iris, an extensible platform that simplifies SED analysis and allows custom models and data integration via a layered, standards-compliant architecture.

Findings

Supports broad-band data ingestion from multiple sources

Allows custom Python models to be integrated easily

Provides a comprehensive environment for SED analysis

Abstract

Iris is an extensible application that provides astronomers with a user-friendly interface capable of ingesting broad-band data from many different sources in order to build, explore, and model spectral energy distributions (SEDs). Iris takes advantage of the standards defined by the International Virtual Observatory Alliance, but hides the technicalities of such standards by implementing different layers of abstraction on top of them. Such intermediate layers provide hooks that users and developers can exploit in order to extend the capabilities provided by Iris. For instance, custom Python models can be combined in arbitrary ways with the Iris built-in models or with other custom functions. As such, Iris offers a platform for the development and integration of SED data, services, and applications, either from the user's system or from the web. In this paper we describe the built-in features provided by Iris for building and analyzing SEDs. We also explore in some detail the Iris framework and software development kit, showing how astronomers and software developers can plug their code into an integrated SED analysis environment.