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Radio astronomy observations in the coming decade will require new levels of sensitivity while mapping large regions of space with much greater efficiency than is achieved with current telescopes. This requires new instrumentation with the…

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…

Data mining techniques, including clustering and classification tasks, for the automatic information extraction from large datasets are increasingly demanded in several scientific fields. In particular, in the astrophysical field, large…

We review the statistical properties of the main populations of radio sources, as emerging from radio and millimeter sky surveys. Recent determinations of local luminosity functions are presented and compared with earlier estimates still in…

The current deepest radio surveys detect hundreds of sources per square degree below 0.1mJy. There is a growing consensus that a large fraction of these sources are dominated by star formation although the exact proportion has been debated…

Over the past decade, sky surveys such as the Sloan Digital Sky Survey have proven the power of large data sets for answering fundamental astrophysical questions. This observational progress, based on a synergy of advances in telescope…

In the last three decades, about 50 radio supernovae have been detected as a result of targeted searches of optically discovered supernovae in the local universe. Despite this relatively small number some diversity among them has already…

Recent and forthcoming advances in instrumentation, and giant new surveys, are creating astronomical data sets that are not amenable to the methods of analysis familiar to astronomers. Traditional methods are often inadequate not merely…

Astronomical observations already produce vast amounts of data through a new generation of telescopes that cannot be analyzed manually. Next-generation telescopes such as the Large Synoptic Survey Telescope and the Square Kilometer Array…

Object detection in astronomical images, generically referred to as source finding, is often performed before the object characterisation stage in astrophysical processing work flows. In radio astronomy, source finding has historically been…

The analysis and an efficient scientific exploration of the Digital Palomar Observatory Sky Survey (DPOSS) represents a major technical challenge. The input data set consists of 3 Terabytes of pixel information, and contains a few billion…

We present a technique-led review of the progression of precise radio astrometry, from the first demonstrations, half a century ago, until to date and into the future. We cover the developments that have been fundamental to allow high…

An array of large observational programs using ground-based and space-borne telescopes is planned in the next decade. The forthcoming wide-field sky surveys are expected to deliver a sheer volume of data exceeding an exabyte. Processing the…

Astronomy has been at the forefront of the development of the techniques and methodologies of data intensive science for over a decade with large sky surveys and distributed efforts such as the Virtual Observatory. However, it faces a new…

Machine Learning algorithms are good tools for both classification and prediction purposes. These algorithms can further be used for scientific discoveries from the enormous data being collected in our era. We present ways of discovering…

All sciences, including astronomy, are now entering the era of information abundance. The exponentially increasing volume and complexity of modern data sets promises to transform the scientific practice, but also poses a number of common…

Large area astronomical surveys will almost certainly contain new objects of a type that have never been seen before. The detection of 'unknown unknowns' by an algorithm is a difficult problem to solve, as unusual things are often easier…

Some attempts to predict the very distant future of Radio Astronomy are given. It is not easy to predict a list of the first priority problems which may appear, but the facilities potential is more predictable. It is suggested, that in…

The era of data-intensive astronomy is being ushered in with the increasing size and complexity of observational data across wavelength and time domains, the development of algorithms to extract information from this complexity, and the…

Large digital sky surveys, over a broad range of wavelengths, both from the ground and from space observatories, are becoming a major source of astronomical data. Some examples include the Sloan Digital Sky Survey (SDSS) and the Digital…