Interactive Digital Worlds provide new individual and social experiences in an enormous variety of artificial realities. They even have huge potential for the examine of how people work together, and the way societies function and evolve. Systematic collection and analysis of in-play behavioral data can be invaluable for enhancing player experiences, facilitating efficient administration, and unlocking the scientific potential of online societies. This paper details the development of a framework to gather participant information in Minecraft. We present an entire resolution which can be deployed on Minecraft servers to send collected data to a centralized server for visualization and analysis by researchers, gamers, and server directors. Utilizing the framework, we collected and analyzed over 14 particular person-days of energetic gameplay. We built a classification device to identify high-level participant behaviors from observations of their moment-by-second recreation actions. Heat map visualizations highlighting spatial habits could be utilized by players and server directors to evaluate recreation experiences. Our knowledge collection and analysis framework affords the opportunity to understand how particular person behavior, environmental factors, and social systems interact by massive-scale observational studies of digital worlds.