FAIR Data Management
Start your journey by driving digital transformation with AI-driven strategies, ensuring your data/metadata is organized and compliant with FAIR principles and data standards. The Hyve supports data curation, improving data management processes, and data governance. This can also be done by assessing data management tools or creating prototypes that support your journey.
On any FAIR journey, whether as a beginner or as an expert it helps to get an expert opinion about the FAIR Maturity of your organization. We use the Pistoia Alliance FAIR Maturity Matrix combined with the experience of our consultants to assess the maturity and provide tailored recommendations for the next steps.
Setting up data management; governance, metadata, pipelines, multi-modality, storage. Getting value from data builds on the foundation of good data management. We help design and implement the infrastructure, processes, and capabilities for large organizations or complex data networks.
Why do FAIR principles matter, how do you implement them, what is FAIR enough, and when can we expect the results? All questions will be addressed in a FAIR Data Strategy. Our consultants will help you develop the strategy and roadmap.
Data is difficult to find for researchers in any site, domain, or folder.
Users are unable to share their research data with other teams and collaborate.
Data is not integrated or reused easily within the company.
Querying data is time-consuming, complicated and involves manual processes.
Let's work together to overcome these challenges!
Pistoia Alliance is a global, not-for-profit, members’ organization with more than 100 members collaborating to lower barriers to innovation in life science and healthcare R&D. Pistoia Alliance projects intend to overcome common obstacles to innovation in these sectors and to transform R&D. The Hyve has been an active member of the alliance since 2016 and contributes to the FAIR for pharma initiatives within the community.
“I had the pleasure of working with The Hyve and together develop Metatree, a solution to store metadata on samples measured in different projects. Their commitment and expertise were evident in every aspect of our collaboration, from the initial planning stages to the final delivery.”
Frans van der Kloet, Biosystems data analysis group at SILS, University of Amsterdam
