This project is to design and develop a platform, dubbed “Translational Visual Data Platform (TVDP)”, to collect, manage, analyze urban visual data which enables participating users connected not only to enhance their individual operations but also to smartly incorporate visual data acquisition, access, analysis methods and results among them. Specifically, we focus on geo-tagged visual data since location information is essential in many multimedia applications and provides a fundamental connection in managing and sharing data among collaborators. Furthermore, our study targets for an image based machine learning platform to prepare users for upcoming era of machine learning and AI applications. TVDP will be used to pilot, test, and apply various visual data intensive applications in a collaborative way. New data, methods, and extracted knowledge from one application can be effectively translated into other applications, ultimately making visual data and analysis as an infrastructure. The goal is to make value creation through visual data and their analysis as broadly available as possible, thus to make social and economic problem solving more distributed and collaborative among users.