Raul Infante-Sainz

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Physics degree at the University of Granada (UGR). Master in Astrophysics by the University of La Laguna (ULL). Doctor by the University of La Laguna / Instituto de Astrofísica de Canarias (IAC). Postdoc at the Centro de Estudios de Física de Aragón (CEFCA).


Centro de Estudios de Física del Cosmos de Aragón (CEFCA)


Postdoctoral researcher


Postal address

Centro de Estudios de Física del Cosmos de Aragón (CEFCA)
Plaza San Juan 1, planta 3, 44001, Teruel, Spain


Gnuastro hands-on tutorial for astronomical data analysis
Raul Infante-Sainz, Zahra Sharbaf

Gnuastro is an official GNU package of a large collection of programs to enable easy, robust, and most importantly fast and efficient, data analysis directly on the command-line. For example it can perform arithmetic operations on image pixels or table columns/rows, visualize FITS images as JPG or PDF, convolve an image with a given kernel or matching of kernels, perform cosmological calculations, crop parts of large images (possibly in multiple files), manipulate FITS extensions and keywords, and perform statistical operations. In addition, it contains
programs to make catalogs from detection maps, add noise, make mock profiles with a variety of radial functions using monte-carlo integration for their centers, match catalogs, and detect objects in an image among many other operations. Gnuastro is written to comply fully with the GNU coding standards and integrates well with all Unix-like operating systems. This enables astronomers to expect a fully familiar experience in the building, installing and command-line user interaction that they have seen in all the other GNU software that they use (core components in many Unix-like operating systems). Gnuastro's extensive library is also installed for users who want to build their own unique/custom programs.

Breakout 1
Maneage: Managing data lineage for archivable reproducibility
Mohammad Akhlaghi, Raul Infante-Sainz

The increasing volume, diversity, and role of data and software in modern research has been very fruitful. However, these same factors, have also made it harder to describe or archive (in sufficient detail) the processing behind a scientific result within the confines of a traditional paper/report. It is thus becoming harder and harder to reproduce results (i.e., critically review by coauthors, referees or larger community) that define scientific progress. In this talk, Maneage (MANaging data linEAGE) is introduced as a working solution to this problem. Maneage (a template, in the form of a Git branch) that provides a framework to exactly reproduce a scientific analysis (from the input data and software, to the processing and creation of final report/paper/dataset. It contains instructions to download and build the necessary software (from the low-level C compiler and shell, to the higher-level science programs and all their dependencies) with the predefined configuration and without third-party package managers. It also includes instructions to run the software on the input data sets to produce the final result (all as plain-text files). Maneage will finally produce a "dynamic" PDF using LaTeX macros: any change in the analysis will automatically update the relevant parts of the PDF (for example numbers, tables or figures). A project defined in this template is fully managed and published in plain text and only consumes a few hundred kilo-bytes (unlike binary multi-gigabyte blobs like containers). It is thus easily to publish and archive for future usage, for example on arXiv (with the paper's LaTeX source) or Software Heritage. Maneage was a recepient of an RDA-Europe adoption grant for best adoption of the "Workflows for Research Data Publishing" guidelines. For more, please see, or its main webpage:

Grand Ballroom