Open Life Science Proposal for Seeds to Systems - Developed for CZI (Funded in 2024)
The OLS (Open Life Science) team proposes an advanced cohort-based training and coaching focused on essential competencies and skills needed to navigate the research funding landscape, along with access to fiscal sponsorship infrastructure for sustainable management of research projects. Referred to as the ‘Seeds to Systems’ Program, this project builds upon the success of OLS's cohort-based training and mentoring program, known as Open Seeds. Since its establishment in 2019, OLS has delivered eight cohorts, engaging over 500 learners and practitioners who have worked on nearly 300 projects worldwide (over 70 countries). We have seen the transformative impact of our approach, especially for members from underrepresented minority groups, who have greatly benefited from expert mentoring, peer-based knowledge exchange, and curated opportunities for professional development and funding, both during and beyond their participation in OLS programs Through the Seeds to Systems, we proposed an extension to the OLS services, aiming to level the playing field for researchers and teams applying for funding to advance their research projects. With a goal to advance and sustain research with open source/science solutions in biomedical and related fields, we will offer specialized training to researchers, especially those from underrepresented groups and LMICs. The Seeds to Systems will contribute to advancing research through funding, guidance on maintenance and mentored support on ensuring the sustainability of research outcomes in a FAIR (Findable, Accessible, Interoperable and Reusable) manner. Leveraging the open science network and partners of OLS, this program will engage practitioners, collaborators, and communities openly, making knowledge, expertise, collaboration and opportunities around funding open and accessible.
Institutions
- Herman Miller (United States) (US)
- OLS
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-03-14
- DOI
- https://doi.org/10.5281/zenodo.15729808
- Primary Topic
- Research Data Management Practices
- Type
- article
- Field-Weighted Citation Impact
- 0.00