Our Initiatives
Community of Practice
An initiative to foster collaboration, innovation, and researcher-driven guidance in advancing Open Science and FAIR principles in SciLifeLab services and projects. We are building a dynamic community of 20+ members from diverse backgrounds — researchers, early-career professionals, international experts, and infrastructure developers — united by the goal of shaping SciLifeLab’s services, projects, and platforms to maximise impact for the scientific community.
Key aspects of the initiative include gathering insights early in development, driving continuous improvement through actionable feedback, fostering a collaborative and inclusive expert community. It also emphasises engaging the wider audience through outreach and networking, and recognising contributions to create impactful services and projects.
FAIR Metadata Network
An initiative aimed at promoting metadata and semantic technologies, along with the FAIR principles (Findable, Accessible, Interoperable, Reusable), to enhance data interoperability and support life sciences research.
The initiative seeks to understand how standards are being adopted, and the barriers preventing adoption, across research domains, institutions, and funding agencies. This will be achieved by building expertise and fostering collaborations among SciLifeLab researchers, fellows, and infrastructure experts.
It addresses shared challenges in metadata management, including standards, curation, and discovery, while promoting the use of semantic tools such as shared vocabularies, ontologies, and persistent identifiers. Additionally, the initiative provides personalised support, workshops, seminars, and an online presence to engage stakeholders.
Through discussions, roundtables, and a dedicated Slack community, the initiative will continuously refine its approach and expand its reach, strengthening data integration, discovery, and reuse. By doing so, it advances innovation in life science research by facilitating more effective and connected research data.
You can read more about the work that is being done here.
Open Science Monitoring Initiative
At SciLifeLab, we monitor the compliance with Open Science and FAIR principles, as displayed in the annual report, which reviews the research produced by our infrastructure units and affiliated researchers. As this process is highly resource intensive, we are procuring a software service to support large-scale, automated, and in-depth analysis of the publications and research outputs produced by SciLifeLab.
The Open Science Monitoring Initiative aims to implement an automated solution for tracking Open Science indicators. Our initial focus is on analysing the data and software shared in SciLifeLab publications. By mining this information, we will assess how closely our community aligns with Open Science practices, policies, and guidelines. Using this information, we will develop an interactive dashboard to help the community explore, interpret, and engage with the findings.
This initiative aims to deepen our understanding of Open Science practices within SciLifeLab, enhance transparency, and inform improvements in our policies, guidelines, and practices, ensuring that we remain at the forefront of Open Science innovation.
AI Network
SciLifeLab is launching an AI Network to foster a collaborative community for researchers, infrastructure users, and staff working with AI in life science. The initiative will provide a virtual meeting space where members can discuss and explore AI applications in life science research, share insights and experiences in leveraging AI for discovery and efficiency, and connect with others to learn who is working on what and identify opportunities for collaboration.
The network also aims to support the development of shared resources, tools, and workflows for AI-driven research. Members will be able to stay informed about emerging AI trends and technologies, exchange best practices for integrating these tools into their work, and access a virtual meeting space to seek advice, discuss challenges, and receive constructive feedback on AI-related projects.
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