June 2019
Nice interview with my AZ colleague Ola EngvistRT @CRiverLabs: The Computer as Drug Hunter eureka.criver.com/the-computer-a…
Google AutoDraw Turns Your Rough Scribbles Into Beautiful Icons For Free: digitalsynopsis.com/design/google-… twitter.com/EricTopol/stat…
“The way that they [newer generation of scientists] aproach describing a phenomenon is different from a scientist from an older generation that is more verbal. I can see that they think in ontologies.” - Paulo Guarnieri twitter.com/GENbio/status/…
Was reminded about this great one: "This is the pharma data version of the famous South Park underpants gnome story, where the business plan is roughly:
Step 1: Collect lots of data
Step 2:
Step 3: Insight and efficiency" twitter.com/DShaywitz/stat…
Step 1: Collect lots of data
Step 2:
Step 3: Insight and efficiency" twitter.com/DShaywitz/stat…
Great piece by @JeremyKun However, I have one reflection: Today’s dirty data was maybe representing yesterday’s reality, or will be tomorrow’s reality we are not sure of how to best represent. twitter.com/MathProgrammin…
1/3 ”We let dirty data interfere with our design and architecture, now we’re paying back all that technical debt, and as a consequence there’s no time for our human flourishing.” Math Versus Dirty Data jeremykun.com/2019/06/08/mat… via @MathProgramming
’Act as the “data product owner” - the single point of contact and owner of data as a strategic asset’ twitter.com/owenboswarva/s…
2012 was also the year when I was made aware of the problem with ”missing clincal trial data”. Later on I started to follow #AllTrials @opentrials @bengoldacre twitter.com/kerfors/status…
Tutorial on the History of #KnowledgeGraph's Main Ideas, at #ISWC2019 knowledgegraph.today Made me think of the night 7 years ago when I followed the news from Google twitter.com/kerfors/status…
”Data is like ice” I like that, much, much better than the oil metaphor. twitter.com/BernHyland/sta…