We introduce SoFiA, a flexible software application for the detection and parameterization of sources in 3D spectral-line datasets. SoFiA combines for the first time in a single piece of software a set of new source-finding and parameterization algorithms developed on the way to future H I surveys with ASKAP (WALLABY, DINGO) and APERTIF. It is designed to enable the general use of these new algorithms by the community on a broad range of datasets. The key advantages of SoFiA are the ability to: search for line emission on multiple scales to detect 3D sources in a complete and reliable way, taking into account noise level variations and the presence of artefacts in a data cube; estimate the reliability of individual detections; look for signal in arbitrarily large data cubes using a catalogue of 3D coordinates as a prior; provide a wide range of source parameters and output products which facilitate further analysis by the user. We highlight the modularity of SoFiA, which makes it a flexible package allowing users to select and apply only the algorithms useful for their data and science questions. This modularity makes it also possible to easily expand SoFiA in order to include additional methods as they become available. The full SoFiA distribution, including a dedicated graphical user interface, is publicly available for download.

Asymmetries in the neutral hydrogen gas distribution and kinematics of galaxies are thought to be indicators for both gas accretion and gas removal processes. These are of fundamental importance for galaxy formation and evolution. Upcoming large blind H i surveys will provide tens of thousands of galaxies for a study of these asymmetries in a proper statistical way. Due to the large number of expected sources and the limited resolution of the majority of objects, detailed modelling is not feasible for most detections. We need fast, automatic and sensitive methods to classify these objects in an objective way. Existing non-parametric methods suffer from effects like the dependence on signal to noise, resolution and inclination. Here we show how to correctly take these effects into account and show ways to estimate the precision of the methods. We will use existing and modelled data to give an outlook on the performance expected for galaxies observed in the various sky surveys planned for e.g. WSRT/APERTIF and ASKAP.