While many institutions have embraced open science through policies and training initiatives, creating enduring communities that sustain open practices remains a significant challenge. This panel explores strategies for developing resilient, researcher-led open science communities that persist despite institutional turnover, shifting priorities, and the project-based nature of academia.
The...
What if the pipeline for transparent, collaborative research began before university? This presentation shares a bold and scalable model for fostering open science practices in secondary school, empowering students to contribute meaningfully to research while reimagining how we train the next generation of scientists and engineers - with equity at the focal point.
Since 1998, Hathaway...
While funding agencies typically require data management plans for project proposals, this does not guarantee the eventual availability of Open Research Data (ORD) that adheres to the FAIR principles. In reality, only a small fraction of funded projects fulfills these commitments, primarily because providing ORD demands additional effort. Often, this effort occurs only after the publication of...
Nowadays, data fuels discovery, innovation, and decision-making; therefore, the ability to manage and curate data responsibly is crucial.
The [Master in Data Management and Curation (MDMC)][1] is a pioneering educational program that embraces the “FAIR-by-design” paradigm, going beyond theory to train professionals in the practical implementation of FAIR principles across the entire research...
As Artificial Intelligence becomes increasingly integrated into the research lifecycle and transforms the research landscape, achieving AI readiness is a key priority. Ensuring high quality, accessible data and workforce preparedness are fundamental to enabling responsible AI-driven innovation. However, gaps remain in data readiness, standards, and AI-specific training.
Alongside...
For science to be truly open, people need access not only to resources but also to the confidence to use them — especially in data science, where technical tools are key to sharing data and code under FAIR principles. However, the tech space remains male-dominated, and many women and newcomers feel out of place. This lack of belonging can prevent people from engaging fully.
As staff at the...
