This project develops a new computational and educational resource, the Distributome, for exploring, discovering and interacting with varieties of probability distributions. The Distributome project leverages the results of successful NSF projects that have been sustained over decades of work in developing interactive learning materials, forging technological advances, and building and sustaining digital libraries; all integrated with an effective dissemination and professional development infrastructure to ensure on-going use. There are several novel features of this project. This resource builds the infrastructure for community based development, expands and validates the distributions' meta-data that is stored, processed, searched, traversed and updated by experts, learners, and educators. The Distributome provides a graphical user interface for interactive exploration of diverse distribution resources, as well as a web-service for query, discovery and computational utilization of these distribution resources by other software programs and tools.
Specifically, this project provides an open (development and utilization), platform-agnostic, extensible and broad framework for navigation, discovery and usage of probability distributions in diverse applications. The entire framework is built using XML/JAVA/HTML/Wiki/MathML/LaTeX and is freely made available to the entire community via www.Distributome.org. The user-base of the Distributome infrastructure includes both educators (integrating these graphical tools and instructional materials in their course curricula and participating in a unique virtual community led by a cadre of activists) and most importantly learners (exploring, validating and understanding the use of probability distributions and models for practical problem solving). Probability modeling is at the root of solving driving biological, engineering, health, physical science, and social problems fundamental to the modern STEM curriculum. The Distributome infrastructure enables representation, demonstration, computation and visualization of a large number of probability distributions, their interrelations and their applications integrated with associated class and out-of-class activities to advance learning.
