| Authors : | Avinash Kumar, Avinash Ck, Ninisha Manaswini, Barenya Dev, Megha Rajoria, Arundhati Purohit, Pratik Dabhade, Ananda Hota |
| Abstract : | Here we shall briefly present RAD-RGB-maker Tool, a python-based web app that uses the power of open source to make the citizen science research collaboratory model of RAD@home, despite being zero-funding and zero-infrastructure, successful and sustainable. The python-based web application fetches FITS image data through NASA SkyView and generates a false coloured image with these data in Red-Green-Blue colour channels with contour (RGB-C). These RGB images use data from archival surveys of DSS2 IR-R-B (optical), WISE22-DSS2 R-GalexNUV (Infrared-Optical-Ultraviolet or IOU) and TGSS-DSS2R-NVSS (Radio-Optical-Radio or ROR) in the respective RGB channels which helps in the analysis and peer-discussion of the potential new discoveries in a uniform format. Participating daily (through social media), one-day events or in week-long trainings, University-level students or science-graduate citizens get skilled in these RGB-C image analysis and identifying rare/important features in the faint and fuzzy radio sources. Uniform images from the RGB-maker tool, help them discuss with others in the group and they can eventually report it as a potential new discovery. These new found sources become part of GTAC-approved GOOD-RAC project for follow up observations.. On average, the RGB-maker web page has ~15 pageviews and, in the facebook group, this leads to ~5 RGB-image comments each day. The RAD-RGBmaker tool which is being used successfully by thousands of citizen scientists in India has the potential to be part of citizen science efforts in Nepal and neighbouring countries. Through the Outreach programme of the IAU Symposia, we have started to train undergraduate participants of the conference and science graduate students/citizens of Nepal to be part of our Collaboratory for citizen science research. |
