Related papers: Extracting Knowledge From Massive Astronomical Dat…

The publication of the Gaia Data Release 2 (Gaia DR2) opens a new era in Astronomy. It includes precise astrometric data (positions, proper motions and parallaxes) for more than $1.3$ billion sources, mostly stars. To analyse such a vast…

The situation of data sharing in astronomy is positioned in the current general context of a political push towards, and rapid development of, scientific data sharing. Data is already one of the major infrastructures of astronomy, thanks to…

Despite almost all being acquired as photons, astronomical data from different instruments and at different stages in its life may exist in different formats to serve different purposes. Beyond the data itself, descriptive information is…

Perhaps more than other physical sciences, astronomy is frequently statistical in nature. The objects under study are inaccessible to direct manipulation in the laboratory, so the astronomer is restricted to observing a few external…

From the moment astronomical observations are made the resulting data products begin to grow stale. Even if perfect binary copies are preserved through repeated timely migration to more robust storage media, data standards evolve and new…

The increase in the number of researchers coupled with the ease of publishing and distribution of scientific papers (due to technological advancements) has resulted in a dramatic increase in astronomy literature. This has likely led to the…

Astronomical data take on a multitude of forms -- catalogs, data cubes, images, and simulations. The availability of software for rendering high-quality three-dimensional graphics lends itself to the paradigm of exploring the incredible…

The Grist project (http://grist.caltech.edu/) is developing a grid-technology based system as a research environment for astronomy with massive and complex datasets. This knowledge extraction system will consist of a library of distributed…

The NASA/IPAC Extragalactic Database (NED) is a comprehensive online service that combines fundamental multi-wavelength information for known objects beyond the Milky Way and provides value-added, derived quantities and tools to search and…

Machine learning techniques offer a precious tool box for use within astronomy to solve problems involving so-called big data. They provide a means to make accurate predictions about a particular system without prior knowledge of the…

We present initial results on the use of Mixture Models for density estimation in large astronomical databases. We provide herein both the theoretical and experimental background for using a mixture model of Gaussians based on the…

Nowadays medium-large size astronomical projects have to face the management of a large amount of information and data. Dedicated data centres manage the collection of raw and processed data and consequently make them accessible, typically…

Astronomical phenomena are governed by processes on all spatial and temporal scales, ranging from days to the age of the Universe (13.8,Gyr) as well as from km size up to the size of the Universe. This enormous range in scales is contrived,…

Classification is a popular task in the field of Machine Learning (ML) and Artificial Intelligence (AI), and it happens when outputs are categorical variables. There are a wide variety of models that attempts to draw some conclusions from…

Astronomy datasets can be challenging to use for high school astronomy classes. Data science education pedagogy can be leveraged to create astronomy activities in which students interrogate data, create visuals, and use statistical thinking…

The extensible N-Dimensional Data Format (NDF) was designed and developed in the late 1980s to provide a data model suitable for use in a variety of astronomy data processing applications supported by the UK Starlink Project. Starlink…

As we are fast approaching the beginning of a paradigm shift in the field of science, Data driven science (the so called fourth science paradigm) is going to be the driving force in research and innovation. From medicine to biodiversity and…

Scientists in all domains face a data avalanche - both from better instruments and from improved simulations. We believe that computer science tools and computer scientists are in a position to help all the sciences by building tools and…

We discuss statistical techniques for detecting and quantifying bimodality in astronomical datasets. We concentrate on the KMM algorithm, which estimates the statistical significance of bimodality in such datasets and objectively partitions…

We present CosmoHub (https://cosmohub.pic.es), a web application based on Hadoop to perform interactive exploration and distribution of massive cosmological datasets. Recent Cosmology seeks to unveil the nature of both dark matter and dark…