Dave Morris

The speaker's profile picture


Please fill in this field


University of Edinburgh


Research Software Engineer

GitHub ID


TAP and the Data Models
Laurent Michel, Mireille Louys, Dave Morris, Bonnarel François

TAP is one of the big achievements of the VO. This protocol gives any relational database a high level of interoperability thanks to several IVOA standards:
- The TAP_SCHEMA : a description of the tables, their columns and the way they can be joined.
- ADQL: a query language, subset of SQL, with some astronomy-specific features
- UWS: a specification for a REST API to be used to handle service requests
These features provide a common way to discover the content of TAP services and to query them.
This works very well with relational data and we propose to investigate the possibility for TAP services to map searched data on data models. Indeed several data models have been developed by IVOA in order to tackle the complexity of the relationships between astronomical data features. Among those we can quote Photometry Data Model, Coordinates, Measurements, Transforms or MANGO that is well suited to describe source properties and relations to some datasets representing these sources. TAP services are able to host complex data bound with joins but the standard still misses important features to serve real model instances:
- A meta-data endpoint telling which models are available per table
- Storage of model meta-data into the TAP_SCHEMA
- Storage of coordinate frames in the TAP service
- Mechanism specifying the model on which the requested data must be mapped
- Mechanism returning multi-table responses for complex objects
- Preservation of model annotations in uploaded tables
The purpose of the BoF is to discuss the relevance of enabling TAP services to deal with Data Models and to refine the functionalities required to implement such a capability.

We will be able to present a proof of concept based on the VOLLT framework that can annotate on the fly query responses on two archive tables using the MANGO data model. Any other contribution and point of view on this topic will be is welcome and helpful to lift up and enrich the debate .

Grand Ballroom
Astropy, PyVO and the Radio realm
Dave Morris, Hendrik Heinl

In the past years, VO standards were widely accepted and spread and many
astronomers get more and more familiar with standards and protocols like
Cone Search, SAMP and TAP/ADQL. Being skilled in these in combination with
Astropy and PyVO opens unlimited opportunities to find, to access and to
combine different datasets for further analysis.

In this tutorial the participants will learn how to use PyVO and ObsTAP
to find services and to explore the data on these services, they will
use Daralink and SODA to perform cutouts on large images, and eventually
use PyVO and Astropy to write a SAMP handler to combine functionality of
TOPCAT and Aladin with PyvO.
The cutouts will be performed on the Astron data service on data derived
from LOFAR.
The cutouts will be performed on the Astron data service on LOFAR
derived data.

We don't expect participants to be experts in above fields after this
tutorial, but to scratch on the surface of how useful these tools are and where to turn if they want to get deeper knowledge. In particular this should

  • TAP/ADQL and related special Obscore services
  • PyVO for data discovery and data access
  • How to read a standard document to develop against this standard

The used software will be:
Python 3.6 (or newer), Astropy, PyVO, Topcat and Aladin. We will provide Python scripts in a github repository.

Grand Ballroom