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The ominous warnings of a `data deluge' in the life sciences from high-throughput DNA sequencing data are being supplanted by a second deluge, of cliches bemoaning our collective scientific fate unless we address the genomic data `tsunami'.…
The recent explosion of recorded digital data and its processed derivatives threatens to overwhelm researchers when analysing their experimental data or when looking up data items in archives and file systems. While current hardware…
In this review, we explore the historical development and future prospects of artificial intelligence (AI) and deep learning in astronomy. We trace the evolution of connectionism in astronomy through its three waves, from the early use of…
Astrophysics has become a domain extremely rich of scientific data. Data mining tools are needed for information extraction from such large datasets. This asks for an approach to data management emphasizing the efficiency and simplicity of…
Astronomy has entered the big data era and Machine Learning based methods have found widespread use in a large variety of astronomical applications. This is demonstrated by the recent huge increase in the number of publications making use…
Astronomical datasets are growing in size and diversity, posing severe technical problems. At the same time scientific goals increasingly require the analysis of very large amounts of data, and data from multiple archives. The Virtual…
Most domains of science are experiencing a paradigm shift due to the advent of a new generation of instruments and detectors which produce data and data streams at an unprecedented rate. The scientific exploitation of these data, namely…
Astronomy is experiencing a rapid growth in data size and complexity. This change fosters the development of data-driven science as a useful companion to the common model-driven data analysis paradigm, where astronomers develop automatic…
Observational astronomy has changed drastically in the last decade: manually driven target-by-target instruments have been replaced by fully automated robotic telescopes. Data acquisition methods have advanced to the point that terabytes of…
Over the past decades and even centuries, the astronomical community has accumulated a signif-icant heritage of recorded observations of a great many astronomical objects. Those records con-tain irreplaceable information about long-term…
Modern scientific data mainly consist of huge datasets gathered by a very large number of techniques and stored in very diversified and often incompatible data repositories. More in general, in the e-science environment, it is considered as…
The global climate crisis poses new risks to humanity, and with them, new challenges to the practices of professional astronomy. Avoiding the more catastrophic consequences of global warming by more than 1.5 degrees requires an immediate…
We are pleased to present a Special Section on Statistics and Astronomy in this issue of the The Annals of Applied Statistics. Astronomy is an observational rather than experimental science; as a result, astronomical data sets both small…
While both society and astronomy have evolved greatly over the past fifty years, the academic institutions and incentives that shape our field have remained largely stagnant. As a result, the astronomical community is faced with several…
It is well known that the best way to understand astronomical data is through machine learning, where a "black box" is set up, inside which a kind of artificial intelligence learns how to interpret the features in the data. We suggest that…
In time-domain astronomy, we need to use the relational database to manage star catalog data. With the development of sky survey technology, the size of star catalog data is larger, and the speed of data generation is faster. So, in this…
With the volume and availability of astronomical data growing rapidly, astronomers will soon rely on the use of machine learning algorithms in their daily work. This proceeding aims to give an overview of what machine learning is and delve…
Astronomy has always been at the forefront of information technology, moving from the era of photographic plates, to digital snapshots and now to digital movies of the sky. This has brought about a data explosion with multi- terabyte…
Many astronomy data centres still work on filesystems. Industry has moved on; current practice in computing infrastructure is to achieve Big Data scalability using object stores rather than POSIX file systems. This presents us with…
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…