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We worked together for the entirety of the three month program. During that time we prototyped... [lists 5 features]
And so we loosened up and spent three weeks playing around with knowledge search and discovery outside of biomed. We built... [lists 5 more features]
At that point, lots of postdocs had told us that some of the apps would have saved them months during their PhD, but actual viable customers were only moderately excited. It became clear that this would have to turn into another B2B SaaS specialized tool with a lot of software consulting and ongoing efforts from a sales team ...
It sounds like the authors spent 3-4 months, built a ton of stuff, and despite some traction (like post-docs saying it would save them months of effort) it wasn't high quality enough to sell to real customers. Did the authors really expect to solve such a difficult problem in such a short period of time? It seems a bit premature to declare that "literature review, search and knowledge discovery are just not that useful".
Seems likely that the value may only be realized in hindsight. The post-docs saying it would have saved them time don’t say they would have paid before they realized that. I wonder too if the time they spent was more valuable and enriching than whatever this application would provide them. You don’t become an expert without “wasting time” researching dead ends or excruciatingly manual steps.
Semantic enrichment of scientific literature seems promising as a way of unlocking the huge amount of knowledge in published documents (e.g., articles, textbooks). However, getting the enrichment process right takes a lot of effort and the enriched data doesn't provide sufficient value differentiation to 1) be worth the investment and 2) be commercially viable.
This author focuses bio-sciences; I've been collecting a list of similar efforts in Physics [0]. Those who can't do teach, and those who can't teach decorate data with semantic features.
[0]
https://derivationmap.net/other_projects
Developer finds what he thinks is a cool problem, builds something, then asks potential users whether they care, only to find that no one is willing to pay for said something.
That's Quibi's story too.
Original title: "The Business of Extracting Knowledge from Academic Publications"
TL;DR: I worked on biomedical literature search, discovery and recommender web applications for many months and concluded that extracting, structuring or synthesizing "insights" from academic publications (papers) or building knowledge bases from a domain corpus of literature has negligible value in industry.
The headline here is just wrong and clearly with an axe to grind.
So…gonna put that wasted code on GitHub?