Interactive Digital Worlds supply new particular person and social experiences in a huge variety of artificial realities. They also have enormous potential for the examine of how individuals work together, and how societies operate and evolve. Systematic collection and analysis of in-play behavioral knowledge will likely be invaluable for enhancing player experiences, facilitating efficient administration, and unlocking the scientific potential of online societies. This paper particulars the development of a framework to collect participant knowledge in Minecraft. We present a whole solution which may be deployed on Minecraft servers to ship collected data to a centralized server for visualization and evaluation by researchers, players, and server administrators. Utilizing MINECRAFT , we collected and analyzed over 14 person-days of lively gameplay. We constructed a classification tool to establish high-level participant behaviors from observations of their moment-by-second sport actions. Heat map visualizations highlighting spatial behavior may be used by gamers and server directors to judge game experiences. Our knowledge assortment and analysis framework offers the opportunity to know how individual conduct, environmental components, and social methods interact by way of giant-scale observational research of digital worlds.