More thoughts on dark nothing

In defining the word dark as a generalization in the use of dark matter and dark energy, I am working with the idea of dark data.  Dark data is missing data that we don’t know anything about but we use some concept in its place.   The concept is treated a single idea even though for all we know it may be collection of a lot of different things.  Like dark matter may be entire catalog of unknown particles that exist far outside the reach of human laboratories, it is unified by the idea of dark.

I’ve been thinking more about an earlier post where I wondered if the very idea of the empty space is a dark concept just as mysterious as dark matter or dark energy.   It escapes our attention just like the number 0.  Empty space is what remains after removing everything else.   There is some scientific investigation into the hypothesis that empty space may actually not be empty afterall.  That isn’t my point, my point is that I am questioning the concept of empty space as a dark concept.

Perhaps there are different kinds of emptiness?   I suggested maybe the emptiness that separates electrons from protons is different from the emptiness that separates molecules in a fluid or solid and that is different from the emptiness that separates the planets from the sun, and that is different the emptiness between stars, and that is different from the emptiness that separates the galaxies.

It seems that we have jumped to the conclusion that emptiness is self-evidently the same in all cases.   This is despite our realization that we had to rejigger our math for quantum-scale dimensions.  The rejiggering works and preserved the idea of consistent emptiness.

Maybe the rejiggering is more analogous to the epicycles added the the ptolemaic model of the planets, postponing a realization that we are not thinking about the problem the right way.   I suggested that empty space may be fundamentally different at different scales and this can change how we account for motions within galaxies and between galaxies.   The properties of these spaces are outside of the reach of human experimentation but they could be different than what we experience in our local planetary system.

Many of my prior posts concerned my particular interest in studying data and in particular the problems I find in dealing with missing data.  The industry has coined the phrase data scientist but as career label to make it easier to recruit talent.   Taking the name seriously, I wonder if there is a science to data.  Physics explains the particles, mass, forces, and energies.  An earlier post asked the question what is the physical explanation that accounts for data.   Like empty space, data exists self-evidently.  Both concepts are independent of the universe.  Their existence is what prompts us to study physics.   If they didn’t exist then there wouldn’t be anything to think about.

After writing my post on taking history seriously, I realized I can restate the data problem as what makes history possible.  In my posts about data science I refer to historical data but this is redundant.  All data is a some record about something occurring in the past, all history is past events recorded somehow.

So what ultimately makes history possible?

We have a model that describes the universe as having four dimensions: three spacial dimensions plus time.   Time is special because the arrow of time is only one way and moves along relentlessly.    But it is orthogonal to the other three dimensions.   This is not hard to imagine because we experience three-dimensional objects as changing over elapsed time.

Time is also different from the other dimensions because it is absolute.  One database uses clock that counts the number of 100-nanosecond ticks since the first year of the common era.  The number is constantly increasing.  Any moment in the common era has a identifying number.   Nothing surprising about this.

But time is not an independent variable because we measure distances in each of the spacial dimension using a unit proportional to time.   Any distance can be stated as the distance light travels in a particular time.   Removing the proportionality constant and we can measure distances in units of time.  We do exactly this for astronomical distances and even terrestrially with radars.

How can time be a measuring unit of the other dimensions and at the same time be an independent variable from the other dimensions.    Ultimately everything depends on time, and except for the instant occurring at the present, all of time is historical.  Time is all historical except for a negligible increment of the current instant.

There appears to be only one independent dimension (time) and it apparently has an absolute reference point of 0 somewhere.

In other words, the entirety of reality is historical plus a negligible and only locally significant present.

When I was being schooled, there was a joke about each discipline of science thinking it was the only science or the foundation of all of the other sciences.   Everything is physics, or everything is chemistry, or everything is biological.

I’m doing the same thing now by elevating data science as the ultimate foundation of all science.  As I discussed earlier, hard and soft sciences can instead be distinguished as present-tense science and past-tense science.  In that formation the foundation science is the one that explains the possibility of history, of data.

It seems to me we completely skip over this question.  The self evidence of history is an example of what I call dark data.   It is unchallenged makeup data to fill in for our ignorance.   As with other forms of dark data (placeholders for ignorance) it deserves our continued suspicions even as we find it useful to get us through the current instant of time.

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5 thoughts on “More thoughts on dark nothing

  1. Pingback: Information supply chain is source of intelligible data for analytics | kenneumeister

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  4. Pingback: Nanoseconds don’t listen to milliseconds | Hypothesis Discovery

  5. Pingback: Improving government with frequently updated laws: rule by data | Hypothesis Discovery

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