POSE: Phase I: An Open-Source Ecosystem for the Mimetic Operators Library Enhanced (MOLE)

Award ID: 2346255

Mathematical modeling can be used to understand and predict natural phenomena in science and areas that broadly impact human society, including medicine, geophysics, finance, economics, weather forecasting, reorganization of food production chains, transport of contaminants in oceans and soils, and propagation of diseases. Mathematical tools that can efficiently solve the partial differential equations (PDEs) that describe those phenomena enable predictions through modeling. The Mimetic Operators Library Enhanced (MOLE) is a software repository that makes it easier and faster to solve mathematical models specifically using mimetic differences. Using mimetic difference methods is favorable, as they are highly accurate, fast, easy to implement and replicate within their appropriate realms, and conserve important properties. MOLE is currently being successfully used by a few research groups around the globe. The goal of this effort is to create a detailed plan for transitioning MOLE to a self-sustaining organization so that it can be maintained and grow through ongoing collaborative development of an open-source product, designed to be publicly accessible, modifiable, and distributable by anyone under an open-source licensing model. Currently, MOLE provides MATLAB/OCTAVE and C++ versions and a basic user guide in its repository. Code contributors must adhere to a set of best practices for scientific software development that not only have solid foundations in research and experience and also improve developers' productivity and the reliability of their software. The team plans to create and support a vibrant community of developers and users, at universities, national labs, and industry. By teaching courses and participating in conferences to promote and increase adoption and collaboration and reach out to current MOLE users and potential adopters, the Open-Source Ecosystem (OSE) requirements will be developed. The project will transition MOLE's existing code base into a robust, distributed, well-documented, community-driven, and secure open-source software environment, and build infrastructure and governance for efficient software development and maintenance. In is anticipated that MOLE will be implemented in compiled and scripting programming languages to support a variety of different environments and communities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Florence Rabanal