Calgary is Canada's 4th largest metropolitan centre located in the foothills of the Canadian Rockies. The University of Calgary is a major Canadian centre for radio astronomy in Canada and has close association with the National Research Council of Canada's Dominion Radio Astrophysical Observatory in Penticton. Calgary is a focus for Canadian participation in the Square Kilometre Array project, and development of cyber infrastructure for data intensive radio astronomy en route to the SKA. 


The ADASS XXIV program included invited talks, contributed papers, display sessions, tutorials, computer demonstrations, and special interest ("Birds of a Feather" or BoF) meetings.

This year CHIVO presented 2 papers:


O7.2 Evaluating a NoSQL alternative for Chilean Virtual Observatory Services

Jonathan Antognini (Universidad Técnica Federico Santa María)

Mauricio Araya, Mauricio Solar, Camilo Valenzuela, Francisco Lira. Universidad Técnica Federico Santa María

Currently, the standards and protocols for data access in the Virtual Observatory architecture (DAL) are generally implemented with relational databases based on SQL. In particular, the Astronomical Data Query Language (ADQL), language used by IVOA to represent queries to VO services, was created to satisfy the different data access protocols, such as Simple Cone Search. ADQL is based in SQL92, and has extra functionality implemented using PgSphere. An emergent alternative to SQL are the so called NoSQL databases, which can be classified in several categories such as Column, Document, Key-Value, Graph, Object, etc.; each one recommended for different scenarios. Within their notable characteristics we can find: schema-free, easy replication support, simple API, Big Data, etc. The Chilean Virtual Observatory (ChiVO) is developing a functional prototype based on the IVOA architecture, with the following relevant factors: Performance, Scalability, Flexibility, Complexity, and Functionality. Currently, it's very difficult to compare these factors, due to a lack of alternatives. The objective of this paper is to compare NoSQL alternatives with SQL through the implementation of a Web API REST that satisfies ChiVO's needs: a SESAME-style name resolver for the data from ALMA. Therefore, we propose a test scenario by configuring a NoSQL database with data from different sources and evaluating the feasibility of creating a Simple Cone Search service and its performance. This comparison will allow to pave the way for the application of Big Data databases in the Virtual Observatory.



O1.5 Exorcising the Ghost in the Machine: Synthetic Spectral Data Cubes for Assessing Big Data Algorithms

Mauricio Araya (Universidad Técnica Federico Santa María)

Mauricio Solar (Universidad Técnica Federico Santa María), Diego Mardones (Universidad de Chile), Teodoro Hochfärber (Universidad Técnica Federico Santa María)

The size and quantity of the data that is being generated by large astronomical projects like ALMA, requires a paradigm change in astronomical data analysis. Complex data, such as highly sensitive spectroscopic data in the form of large data cubes, are not only difficult to manage, transfer and visualize, but they also turn unfeasible the use of traditional data analysis techniques and algorithms. Consequently, the attention have been placed on machine learning and artificial intelligence techniques, to develop approximate and adaptive methods for astronomical data analysis within a reasonable computational time. Unfortunately, these techniques are usually sub optimal, stochastic and strongly dependent of the parameters, which could easily turn into "a ghost in the machine" for astronomers and practitioners. Therefore, a proper assessment of these methods is not only desirable but mandatory for trusting them in large-scale usage. The problem is that positively verifiable results are scarce in astronomy, and moreover, science using bleeding-edge instrumentation naturally lacks of reference values. We propose an Astronomical SYnthetic Data Observatory (ASYDO), a virtual service that generates synthetic spectroscopic data in the form of data cubes. The objective of the tool is not to produce accurate astrophysical simulations, but to generate a large number of labelled synthetic data, to assess advanced computing algorithms for astronomy and to develop novel Big Data algorithms. The synthetic data is generated using a set of spectral lines, template functions for spatial and spectral distributions, and simple models that produce reasonable synthetic observations. Emission lines are obtained automatically using IVOA's SLAP protocol (or from a relational database) and their spectral profiles correspond to distributions in the exponential family. The spatial distributions correspond to simple functions (e.g., 2D Gaussian), or to scalable template objects. The intensity, broadening and radial velocity of each line is given by very simple and naive physical models, yet ASYDO's generic implementation supports new user-made models, which potentially allows adding more realistic simulations. The resulting data cube is saved as a FITS file, also including all the tables and images used for generating the cube. We expect to implement ASYDO as a virtual observatory service in the near future.


After ADASS the IVOA Interop was held...



The International Virtual Observatory Alliance (IVOA) Fall 2014 Interoperability Meeting will be held at the Banff Park Lodge from 10-12 October 2014. The meeting is being organised by the Canadian Astronomy Data Centre. The dates and location were chosen to allow participants to also attend the 2014 ADASS Conference in nearby Calgary, Alberta.

The IVOA "Interop" workshops provide a semi-annual venue for discussion and development of virtual observatory standards and VO-based applications, and are open to those with an interest in utilizing the VO infrastructure and tools in support of observatory operations and/or astronomical research.