As usual, Brother Steve is seeing this at a much higher conceptual and
process level than I am.
>From the perspective of Analytic Journalism, if we're dealing with a large
data set -- say 10K to 1 million records -- we would first draw a sample of
a small TK percent to develop and test our assumptions, methods, and
process. Once it's stable, run it against a larger sample. If it is still
stable, then throw it against the total dataset.

At least that's what I thought this guy was talking about.
Tom

On Thu, Feb 5, 2026 at 2:21 PM Steve Smith <[email protected]> wrote:

>
>
> https://uknow.uky.edu/research/nsf-career-award-supports-faster-smarter-use-massive-scientific-data
>
> Sounds like a semi-new vocabulary for what many of us have been doing for
> years. So where's our $500k check?
>
> Def fits some of my work in 2005-6 at LBL on using the compression indices
> in massive data sets to identify "interesting" (low-compression ==> high
> entropy ==> interesting)) subsets/slices/views of massive data sets.  My
> only published work from that was actually in providing visualization of
> the compression itself as a diagnostic for the multi-scale effectivity of
> the compression on various data sets, but I believed that the whole process
> could have been inverted to actually enhance efficient analysis.
> Unfortunately it was the Data Storage folks funding/driving the work, not
> the Viz or Data Mining folks.
>
> We also touched on deriving CFD familiar-measures like Div/Curl over
> non-obvious data sets, once again as a meta-field to try to intuit within.
>  This was part of a DHS-funded "visual analytics" effort, unfortunately
> managed by a rival lab who managed to undermine most project proposals not
> lead by their lab...   bah-humbug!  I wasn't directly active in it, but
> LANL had a 1 year LDRD project funding the normalization of a broad suite
> of graph-metric algorithms for the same purpose (INCAA?) I don't know of
> any applications of it beyond the principles on the project re-using their
> tools and understanding going forward.  Meta-Tools often don't get good
> traction?
>
> I'm generally a fan of "early career" funding like this even though it
> naturally fosters jealousy among peers, etc.  My elderDotter was in the
> running for several of those types of things about 10 years go (wow, time
> flies!) when there was a pause in the program and her eligibility timed out
> while the system took that pause.
>
> It still rankles her that she missed that boat.   She also missed the
> CRISPR boat by an inch or two (coulda been a contender for a position in
> Doudna Lab just before that unfolded) but for personal life constraints!
>
>  All the counterfactuals we conjure when we reflect and ideate!
>
> *I coulda been a contendah!*
>
>
>
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Tom Johnson - [email protected]
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Santa Fe, New Mexico USA

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