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Universidad Técnica Federico Santa María Mendoza Marcelo
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Chile
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Abstract Reference: 30383
Identifier: P6.18
Presentation: Poster presentation
Key Theme: 6 Python in Astronomy

Scaling Up Data Cube Indexing Services for Content-based Searches in the Chilean Virtual Observatory (lightning talk)

Authors:
Michel Laurent, Kobersi Pauline

Content-based search tools are key building blocks for the construction of large scale virtual observatories. Recently, we create an automatic method for data cube indexing [AC16] capable of automatically detecting and recording ROIs while reducing the necessary storage space. Currently, we are putting our codes in the production pipeline of ChiVO [ChiVO], the Chilean Virtual Observatory, an initiative which belongs to IVOA and seeks to provide the capability of content-based searches on data cubes to the astronomical community. In this presentation we show how to scale up our first prototypes to a large-scale data center. Efforts involved in code migration from R-based codes [ASCL1512.010] to CASA/Python-based software give us insights for code refactoring and data integration issues that can be helpful for researchers and practitioners in astroinformatics.
[AC16] Araya, M., Candia, G., Gregorio, R., Mendoza, M., Solar, M. [2016]. Indexing data cubes for content-based searches in radio astronomy, Astronomy and Computing, 14:23-34.
[ChiVO] Chilean Virtual Observatory, http://www.chivo.cl