R is great for data analysis and Shiny is great for interactive data visualisation, but could we use R&Shiny for efficient declarative data collection? Moreover, how can we develop web data products in R&Shiny, that are based on real-time declarative data collection with after-question and after-survey instant feedback? Users of such web data products should be able to immediately access the feedback relevant to their answers. To increase the value of the feedback, it should be dynamically customised to each respondent. This can be achieved by pre-programmed templates of feedback scenarios, which can be adaptively customised by the respondent’s answers to this or previous questions. Employing large analytical and data visualisation capabilities in R, we could try to adapt any type of instant feedback to each user. Using R, we could also combine different feedback sources: a respondent’s answers to a given question and to other questions, other users’ answers, external open data (imported into our app or available via APIs), and aggregated or summarised outcomes from reference studies. What are the possibilities and obstacles for developing such data products natively in R&Shiny? How the idea of QAF (Question, Answer, and Feedback) objects can be implemented in R&Shiny? What is the roadmap for developing ODGAR framework for On-line Data Gathering, Analysing, and Reporting? Is it possible to build mobile app in R&Shiny? I will try to answer these questions using experience gained from developing early stage prototypes.