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4 minutes

Having a great R&D data management plan can provide considerable returns, both in generating the best scientific insights from your data, and in saving your organization a lot of time and money. In our experience, when life science organizations implement an R&D data management plan that follows the principles of FAIR data – thereby improving data findability, accessibility, interoperability, and reusability across the organization – they gain a competitive edge.

Want more information on our approach to R&D data management?


In this webinar, BioLizard’s experts will provide a theoretical framework and best practices for implementing and maintaining FAIR data principles, as well as present concrete client cases where we successfully supported the adoption of these principles. At the end of the webinar, you will understand the principles of FAIR data and how they can be applied to improve data findability, accessibility, interoperability, and reusability within your own life science research, as well as the benefits that this can bring to your organization.

 

This webinar is brought to you in collaboration with flanders.bio.

Are you ready to FAIRify your data? 

Reach out to us today to start discussing how we can support you!

Why work with us? At BioLizard, our expertise spans both computer science and biology – meaning that we can act as effective translators to align the needs of IT and R&D departments, and design and implement an R&D data management plan that works for all key stakeholders across your life sciences organization.

Prefer to do some more reading before you reach out to us? No problem, we have lots of free information to share with you!

  • Read this blog article to understand how R&D data management can help save your life sciences organization time, money, and headaches
  • Read this blog article for a step-by-step guide for building a successful R&D data management plan
  • Read this blog article to learn about how to stay on top of your R&D data management game once you have implemented a great R&D data management plan

 

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