provenance

Topics: Provenance, reproducibility, standards, image creation Skills: Python, JSON, Bash scripting, Linux, image creation and deployment Difficulty: Medium Size: Large (350 hours) Mentors: Raül Sirvent Project Idea Description The COMPSs programming model provides an interface for the programming of a sequential application that is transformed in a workflow that, thanks to the COMPSs runtime, is later scheduled in the available computing resources.

This post describes our midterm work status and some achievements we have made so far in our project proposal for noWorkflow. For a more friendly introduction to our work, please, refer to this tutorial available.

This post describes our midterm work status and some achievements we have done so far in the project for the noWorkflow package. The initial weeks I started doing a bibliographical review on reproducibility in the Data Science (DS) and Machine Learning (ML) realms.

Hello everyone, my name is Jesse and I’m proud to be a fellow in this 2023 Summer of Reproducibility program, contributing to noWorkflow project. My proposal was accepted under the mentorship of João Felipe Pimentel and Juliana Freire and aims to work mapping and testing the capture of the provenance in typical Data Science and Machine Learning experiments.

The noWorkflow project aims at allowing scientists to benefit from provenance data analysis even when they don’t use a workflow system. Also, the goal is to allow them to avoid using naming conventions to store files originated in previous executions.