​Sharing Research Data: We Can Do Better!

​Today’s publishing practice is slow, inefficient, and expensive for both researchers who publish their results and those who want to access this knowledge. Datasets are skewed: there is no incentive to publish negative results (when your intervention proved to be ineffective) among other problems. We are mostly talking biological data but this conversation goes beyond biology and medicine.

​We invite you to a discussion on what's currently wrong in how we publish research papers and datasets. As conversation starter, we'll have 3 speakers to present their solutions and ideas:

​Timofey Glinin, PhD: First Approval Project (publishing annotated datasets with DOI bypassing the need to publish a paper but having the opportunity to automatically become a co-author of a paper in the future... among other things, like this student competition!)

​Peter Lidsky, PhD: Sungularis Project (Peter calls his solution a GitHub for fundamental research—I call it LessWrong for academic papers. We know how to publish, review, and discuss articles outside of academia, better technical solutions have existed for years—why aren't we updating this infrastructure for the "official part" of human knowledge base?)

​Max Koko: CrowdWise.bio (infrastructure that enables researchers "to start a pharma company in a garage": extract any data from any hospital or company, have all compliance and cybersecurity included so you don’t need a team when dealing with sensitive medical information.)