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Since their introduction in 2016, the FAIR data principles have gained increasing recognition and adoption in global neuroscience.  FAIR defines a set of high level principles and practices for making digital objects, including data, software and workflows, Findable, Accessible,  Interoperable and Reusable.  But FAIR is not a specification;  it leaves many of the specifics up to individual scientific disciplines to define.  INCF has been leading the way in promoting, defining and implementing FAIR data practices for neuroscience.  We have been bringing together researchers, infrastructure providers, industry and publishers through our programs and networks.  In this session, we will hear some perspectives on FAIR neuroscience from some of these stakeholders who have been working to develop and use FAIR tools for neuroscience.  We will engage in a discussion on questions such as:  how is neuroscience doing with respect to FAIR?  What have been successes?  What is currently very difficult? Where does neuroscience need to go?


This lecture will provide an overview of Addgene, a tool that embraces the FAIR principles developed by members of the INCF Community. This will include an overview of Addgene, their mission, and available resources.

Topics covered in this lesson
  • Addgene’s nonprofit mission
  • The Addgene open biomaterials collections
  • Centralized materials and reproducible science
  • Enabling scientists for experimental success
  • Sharing around the world
  • Joining the sharing community
  • Impact data-depositing increases citations
  • Sharing to optimize research dollars
  • Bad reagents, poor outcomes
  • An information and education portal
  • Resource and information portal
  • Free educational resources
  • Platform for sharing AAV data
  • Neuroscience resources at
  • How can we help?
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