Thread by @ETognoli

#radioactive commentary, w/ apologies to all admirable people of #BrainSTOA working hard on #DataSharing. This highlights a need to broaden #sharing to #computations & #insights. Premises were clear in Ngai’s “data resource development”, Bjaalie’s “modeling workflow” #Teamscience

Data sharing is good. Too much data creation, objectionable. Overreliance of data might be used to obfuscate gaps in theory, analysis and interpretation. Data is also a currency for misused scientific power. #InclusiveScience

At this point, we should also focus on sharing #ComputationalTools (and explaining them, and building expertise in using them). #ComputationalNeuroscience.

We should enhance collective vetting of our interpretations of their meaning.

We developed a cult for data because reliance on soft thoughts processes failed us in the past. But we went to far and lost the enormous respect due to computing and (collective) thinking. #BalanceTheoryExperiment

If only I could have had 1M$ each time I heard a B.R.A.I.N. initiative PI say: “I have sh!tloads of data, don’t know what to do with them, will give you crumbs for help analyze!” #gatekeepers

To pollinate Data Sharing, I think #BRAINSTOA and other agencies need to invest in sharing, training for their computational analysis tools. This was too discretely mentioned yesterday morning.
#ComputationalNeuroscience

#BRAINSTOA and other federations/agencies could also invest in collective forms of debate to vet data, analysis and interpretation and create a more integrated theory of the brain. #SharingTheories Publishing incentivize against meaning integration.