A comprehensive report on how the Aligning Science Across Parkinson’s research initiative has worked toward its goals of promoting OS and collaboration to date. It presents procedures, templates, and findings (metrics) on the approach since the project was launched in 2019 and is updated regularly.
Developing metrics, practices, and software for open source projects in community health; one goal is to identify all contributions made in this sphere and the organizations and individuals that make them; another to improve the transparency and actionability of open source tools.
This project has developed a values-based open source implementation and assessment program, crucial to developing a trustworthy data analysis ecosystem. While building standardized, easily accessible epidemiological software tools, Epiverse will be applying this values-based framework to metrics gauging the initiative’s success.
A global data analysis ecosystem creating standardized, accessible epidemiological software tools to solve real-world health problems. Three prongs include TRACE – the interoperable tools and software; BUILD – scaffolding for interdisciplinary engagement; and CONNECT – global community dedicated to innovation and health equity.
Developing metrics that reflect team members’ collaborative research activities – e.g., sharing/posting early research, reviewing, revising, commenting – as well as the rapid, open dissemination of their findings.
As more research outputs are shared, a common schema and nomenclature will improve discoverability and reproducibility, increase resuse, and enable meta-analyses. All outputs need categorization, tagging, adequate metadata, and persistent idenfitiers.
SPORR is an NIH-funded program for promoting and implementing best practices in research rigor and reproducibility. The goal is to provide education, training, and resources in principles and tools that optimize efficiency, validity, and reproducibility. For instance, they’ve created templates for CVs and data management plans, and researchers are rewarded for innovations such as an open source lab manual of best practices for reproducibility of computational workflows.