Talk:2582: Data Trap

Created a barebones explanation — please expand & clarify :) Szeth Pancakes (talk) 06:40, 17 February 2022 (UTC)

I'm sure we could get into black holes (hairy or otherwise) and entropy and/or information-entropy.

But the feeling I get is that Data begets data (by analysis of the original data) and then the data that is the analysis plus the original data begs to in turn be meta-analysed. Which then gives an additional clump of data... Trapping everyone in a potential N-meta-analysis loop.

(For those wondering how the entropy of this system works, it's the additional state info of the successive analysers, like the sunlight shone onto the biosphere, that prevents the system going 'stale' and degrading to successively shorter summaries that add nothing. You get to comment upon the prior analysis's choice of trend metric, etc...)

Well, that's my take, but I wouldn't know how to authoritatively - and succinctly - put that into the explanation. I could be entirely wrong, as well. 172.70.90.173 09:34, 17 February 2022 (UTC)

You're on to something - it's about information vs data. Cueball wants to analyse the data to get hold of information that's buried somewhere in it. Usually, in terms of bits, that information is only a tiny fraction compared to the volume of data. Think of gigabytes of data giving rise to an insightful scientific publication that's only a few tens of kilobytes long. Megan seems to think that this is just a few more kB of "data" to be added to the pile, without realising that we've just gone from a jumble of confused bits to actual understanding. Of course, in doing his analysis, Cueball has added some information of his own, to wit an explanation of how he did the analysis and (implicitly) why he chose that tack. Which would make the new pile of data ripe for meta-analysis as you say.162.158.233.105 10:27, 17 February 2022 (UTC)

Megan is NOT "Thinking Cueball implies he wants to get rid of some of the data . . . ."! I have NO idea where that implication lies. 172.70.130.153 10:16, 17 February 2022 (UTC)

Done properly, analysis actually reduces the amount of information (not data) that you need to consider--that's the whole point. Rather than trying to comprehend thousands or millions of numbers, you can (for instance) reduce it to an average, or a correlation, or some other single number. Megan is missing the whole point of analyzing data. Nitpicking (talk) 12:49, 17 February 2022 (UTC)