Demitri Muna performed research with large data sets ranging from solar physics to experimental dark matter to large sky surveys. He developed infrastructure during his nine years on the Sloan Digital Sky Survey (SDSS) which included the design of a new web-based data interface, APIs, and data visualizations. Since then and with funding from NASA, he has focussed on creating a new data interface and design language that aims to integrate all publicly available astronomical data by removing as much of the implementation detail as possible.
Introducing the Trillian Framework and Science Data Descriptors
This demo is a hands on introduction to the newly released Trillian framework. The Python package and supporting API will allow astronomers to retrieve data by simply describing it. For example, consider the statement "all Galex images within two square degrees of ra=12°34’42”, dec=47°22’52” ”. This description completely and unambiguously defines a known set of data. The Trillian framework will allow one to directly work with data from nothing more than such a description, regardless of where the data is, what interface is required to retrieve it, what files are needed, and what format it is in. The demonstration that can be followed along with will show how multiple data sets can be accessed and how to contribute to the project to add more, plus how this framework is designed to scale from a laptop to a full cloud computing solution. A detailed description of scientific data descriptors will be also presented, a new scheme for addressing data that is one of the components of Trillian but is useful independently outside of the framework. Finally, a brief demonstration will be given of Cornish, a new Python interface around the Starlink AST library that is used to work with regions on a sphere.