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[go-friends] NIH RFI on Strategic Plan for Data Science: Database vs Knowledge base

Carol Bult Carol.Bult at jax.org
Tue Mar 6 12:53:07 PST 2018


I don’t think the errors in concepts are obvious to the individuals who drafted the report. Chris’ comments mirror the same points I raised in a closed session of NHGRI’s Advisory Council a few weeks ago when this report was previewed. The positive thing is that NIH realizes that they need a different approach to funding data resources and that the criteria for evaluation need to be different than for a typical R01 grant….  But the individuals on the internal NIH committee that drafted the data science plan are not data scientists and this is reflected in the lack of clarity that Chris noted. It is really important to have robust community responses to this plan to help shape the directions for future funding models of data resources at NIH.



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From: go-friends <go-friends-bounces at lists.stanford.edu> on behalf of Valerie Wood <vw253 at cam.ac.uk>
Date: Tuesday, March 6, 2018 at 3:40 PM
To: "go-friends at lists.stanford.edu" <go-friends at lists.stanford.edu>
Subject: Re: [go-friends] NIH RFI on Strategic Plan for Data Science: Database vs Knowledge base


I agree Chris, but this seems so obvious an error that its possibly just a mistake that requires correction?

v.

On 06/03/2018 19:56, Chris Mungall wrote:

The NIH has put at an RFI together with a draft strategic plan:
https://grants.nih.gov/grants/guide/notice-files/NOT-OD-18-134.html

I want to draw people's attention to p10 of the report

"NIH will distinguish between databases and knowledgebases (see text box “Databases and Knowledgebases: What’s the Difference?”) and will support each separately from one another"

OK, this is interesting. But caution advised, these are two pretty squishy terms that are used differently by different communities. For those of us with an AI background, "databases" are typically closer to the raw data, are curated at the level of metadata rather than data, whereas "knowledge bases" contain curated generalizations of the data. GO is a classic knowledge base (or Knowledge Graph, now that google has made that trendy). However it's historically been called a "database" since that is the term the community normally uses.

Anyway, the distinction that the NIH makes in the report (box at bottom of p10 of the report) doesn't make any sense to me:

  *   an example of what might be in a database is "functional annotations of gene products"
  *   an example of what might be in a knowledgebase is "protein-protein interaction networks"

To me this is precisely reversed. PPI networks are often raw data, e.g. coIP. A functional annotation is as absolutely paradigmatic case of knowledge as you could wish for.

Normally I save terminological minutiae such as "what's the difference between an ontology and terminology" to the bar or to the filing cabinet marked Pointless Discussions We Used To Have In The Early Days of GO. However, if the NIH is going to make important funding decisions based on a difference between "Database" and "Knowledge Base", it's crucial that we educate them. This is important for GO (and for other knowledge databases/repositories/resources/whatever you want to call them). Given that functional annotation is explicitly called out in the draft report, I think this calls for a specific response from the entire GO community.




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