In recent years there has been a growing effort to capture and record script or simulation executions in scientific computing. Simulation managememt tools (SMTs) such as Sumatra, Reprozip and CDE address different aspects of the problem from simple record keeping to generating a complete bundle of the environment at each execution. An SMT with full functionality must address a number of key issues including record keeping, live job inspection, meta-data capture, environment capture, as well as possibly bundling the environment for later use. In addition, a cloud platform to augment SMTs that displays and analyzes metadata for each simulation record has the potential to greatly improve the practice of simulation management in scientific computing. Recent literature [1, 2] is beginning to address the issue of standardization for simulation management records to improve simulation reproducibility, management and reliability. A cloud platform for multiple SMTs has the added benefit of providing a platform for standardizing simulation record schema.
CoRR (Cloud of Reproducible Records) is a cloud platform aimed at augmenting existing SMTs such as Sumatra. It provides services for both storing and viewing simulation records using multiple SMTs. The intent of CoRR is to be as robust and data scheme agnostic as possible so that changes to the SMT, backend model, API and frontend do not break the interactions between each element or backwards compatibility with existing record sets. The Python web framework, Flask, is used to generate the backend endpoints while the frontend is entirely HTML5, JavaScript and CSS based. The end vision of CoRR is to eventually provide a collaborative platform for sharing and comparing simulation records and to add value to the scientific workflow.
@faical-yannick-congo, can you fix the link to your name and provide a reference for the second to last sentence in the first paragraph?