The present work discusses the use of a weakly-supervised deep learning algorithm that reduces the cost of labelling pixel-level masks for complex radio galaxies with multiple components. The algorithm is trained on weak class-level labels of radio galaxies to get class activation maps (CAMs). The CAMs are further refined using an inter-pixel relations network (IRNet) to get instance segmentation masks over radio galaxies and the positions of their infrared hosts. We use data from the Australian Square Kilometre Array Pathfinder (ASKAP) telescope, specifically the Evolutionary Map of the Universe (EMU) Pilot Survey, which covered a sky area of 270 square degrees with an RMS sensitivity of 25–35 $\mu$Jy beam$^{-1}$. We demonstrate that weakly-supervised deep learning algorithms can achieve high accuracy in predicting pixel-level information, including masks for the extended radio emission encapsulating all galaxy components and the positions of the infrared host galaxies. We evaluate the performance of our method using mean Average Precision (mAP) across multiple classes at a standard intersection over union (IoU) threshold of 0.5. We show that the model achieves a mAP$_{50}$ of 67.5% and 76.8% for radio masks and infrared host positions, respectively. The network architecture can be found at the following link: https://github.com/Nikhel1/Gal-CAM

We present a set of peculiar radio sources detected using an unsupervised machine learning method. We use data from the Australian Square Kilometre Array Pathfinder (ASKAP) telescope to train a self-organizing map (SOM). The radio maps from three ASKAP surveys, Evolutionary Map of Universe pilot survey (EMU-PS), Deep Investigation of Neutral Gas Origins pilot survey (DINGO), and Survey With ASKAP of GAMA-09 + X-ray (SWAG-X), are used to search for the rarest or unknown radio morphologies. We use an extension of the SOM algorithm that implements rotation and flipping invariance on astronomical sources. The SOM is trained using the images of all ‘complex’ radio sources in the EMU-PS which we define as all sources catalogued as ‘multi-component’. The trained SOM is then used to estimate a similarity score for complex sources in all surveys. We select 0.5% of the sources that are most complex according to the similarity metric and visually examine them to find the rarest radio morphologies. Among these, we find two new odd radio circle (ORC) candidates and five other peculiar morphologies. We discuss multiwavelength properties and the optical/infrared counterparts of selected peculiar sources. In addition, we present examples of conventional radio morphologies including: diffuse emission from galaxy clusters, and resolved, bent-tailed, and FR-I and FR-II type radio galaxies. We discuss the overdense environment that may be the reason behind the circular shape of ORC candidates.

We present the data and initial results from the first pilot survey of the Evolutionary Map of the Universe (EMU), observed at 944 MHz with the Australian Square Kilometre Array Pathfinder (ASKAP) telescope. The survey covers $270 \,\mathrm{deg}^2$ of an area covered by the Dark Energy Survey, reaching a depth of 25–30 $\mu\mathrm{Jy\ beam}^{-1}$ rms at a spatial resolution of $\sim$ 11–18 arcsec, resulting in a catalogue of $\sim$ 220 000 sources, of which $\sim$ 180 000 are single-component sources. Here we present the catalogue of single-component sources, together with (where available) optical and infrared cross-identifications, classifications, and redshifts. This survey explores a new region of parameter space compared to previous surveys. Specifically, the EMU Pilot Survey has a high density of sources, and also a high sensitivity to low surface brightness emission. These properties result in the detection of types of sources that were rarely seen in or absent from previous surveys. We present some of these new results here.

IAU Commission 5, Documentation and Astronomical Data, continued its mission of promoting and supporting sound practices of data management, data dissemination, and data preservation over the past three years. The Commission also prepared its proposal for continuation, with some changes in emphasis, after the IAU's commission restructuring program. Below we report on the activities of the various Working Groups and the one Task Force in Commission 5.

IAU Commission 5 (http://www.nao.ac.jp/IAU/Com5/) deals with data management issues, and its working groups and task group deal specifically with information handling, with data centers and networks, with technical aspects of collection, archiving, storage and dissemination of data, with designations and classification of astronomical objects, with library services, editorial policies, computer communications, ad hoc methodologies, and with various standards, reference frames, etc. FITS (Flexible Image Transport System), the major data exchange format in astronomy, has been standardized, maintained and updated by the FITS working group under Commission 5.

At the 2003 Sydney IAU meeting, Marion Schmitz (Caltech, USA) took over the chair of the Commission 5 Working Group Designations, succeeding Helene Dickel. The Working Group Designations of IAU Commission 5 clarifies existing astronomical nomenclature and helps astronomers avoid potential problems when designating their sources. The most important function of WG Designations during the period 2003-2005 was overseeing the IAU REGISTRY FOR ACRONYMS (for newly discovered astronomical sources of radiation: see the website <http://cdsweb.u-strasbg.fr/cgi-bin/DicForm>) which is sponsored by the WG and operated by the Centre de Données de Strasbourg (CDS). The Clearing House, a subgroup of the WG, screens the submissions for accuracy and conformity to the IAU Recommendations for Nomenclature (<http://cdsweb.u-strasbg.fr/iau-spec.html>). From its beginning in 1997 through August 2006, there have been 132 submissions and 111 acceptances. Attempts to register asterisms, common star names, and suspected variable stars were rejected. The past three years saw 61 acronyms submitted with 50 of them being accepted. (GIRL - yes; WOMEN - no).

We present a summary of the major contributions to the Special Session on Astronomical Data Management held at the IAU XXVI General Assembly in Prague in 2006. While recent years have seen enormous improvements in access to astronomical data, and the Virtual Observatory aims to provide astronomers with seamless access to on-line resources, more attention needs to be paid to ensuring the quality and completeness of those resources. For example, data produced by telescopes are not always made available to the astronomical community, and new instruments are sometimes designed and built with insufficient planning for data management, while older but valuable legacy data often remain undigitised. Data and results published in journals do not always appear in the data centres, and astronomers in developing countries sometimes have inadequate access to on-line resources. To address these issues, an ‘Astronomers' Data Manifesto’ has been formulated with the aim of initiating a discussion that will lead to the development of a ‘code of best practice’ in astronomical data management.

Recent proliferation of large radioastronomical source surveys and resulting data products are reviewed, and attention is drawn to their poor archival status. First practical steps are proposed to establish a radio source data base from published source catalogues, proceeding with time from the bigger and recent ones to the smaller and older ones. At later stages the data base could assimilate unpublished data, spectral-line data and also images.