Comment on Watch the Sun Age Through the Last Decade

YouTube – nagG8w3v_JA

I would have filled in the gaps with estimations, and cut the jumps and jitters. Too distracting. This is a wonderful dataset, but you shared it in an undocumented and lossy format. Of low scientific value, unless somehow people will simply memorize the good stuff and jump to deep insights from just using their eyeballs.

It is too fast. Even slowing down to 0.25 playback speed, the frames blur and take time to look for common processes and patterns. Of course, even if there “looks” to be something the pixels are so mushed up, they are nearly worthless for fine detail. And, what, you gave a low resolution version too? So lossy, low resolution, undocumented is that best that NASA, best of the best, can do in sharing 10 years of massive scientific effort to study and help the human race understand flows, textures, patterns and processes on the sun?

[ Come on, YouTube, you should be global experts on video image processing and data sharing for scientific and technical data in frame time series form. What? You can’t learn how to put out a lossless format? Too busy with TicTok? ]

What camera(s) took these pictures, how often, what frequency, statistics on pixels and regions? Come on, quit serving out “eye candy” and give the whole world real scientific data. It is easier to do that, than to put out partial information into the global human consciousness, that then has to be removed later

Live Science? Science means, to the best of your ability, lossless and precise data that can be used in subsequent investigations. It means using those data to develop many algorithms and models – which are fully documented, clear, and immediately useful – so that individuals and groups worldwide and over time can share in a common effort. If you want to contribute to human knowledge, then try a little harder if you are going to share with 100,000 people, or a million, or a billion. You had that many people and only a tiny fraction gave you a thumbs up. That should tell you something. You may have just copied someone else’s work at best. But you will be rewarded on YouTube, and the world, by what value you add to something like this. YouTube is often new insights and views. Often, at the core of laughter and uneasiness are the roots of new scientific discoveries, new technologies, new products and new human insights to help the world.

If you took you name literally, you could bring “Science” “live” onto YouTube and for the world — NOT in lossy “eye candy” formats, but real streams of raw pixels from some source that is hard to process, but then could be used by classroom, new researchers, learner, experimenters, designers of the coming generations. Global learning won’t converge to new industries if you only share lossy data streams. Science and technology and society’s core processes run on precision, repeatability, shared units and dimensions, shared data, shared models and visualization, shared ideas and discussions, and tests and tests and tests. I really hope you will try again. I have hope for someone who cared enough to put these beautiful pictures here. Your motives are about right, but it needs follow through.

Me, I would like to count, catalog, curate and condense the many small patterns embedded in this time series. But for it to have lasting value, it should be done with lossless real data pixels. Try it. Find a FITS exact image, export it to the best compressed JPEG or video format. Then compare pixel-by-pixel the intensities. You will find most every pixels is distorted. You want to understand these solar processes where each pixels is “huge”? How big are your pixels, across the sun’s disk, remembering the distance from earth to sun in changing constantly?

Best wishes,
Richard Collins, Director, The Internet Foundation

Richard Collins

About: Richard Collins

Sculpture, 3D scanning and replication, optimizing global communities and organizations, gravitational engineering, calibrating new gravitational sensors, modelling and simulation, random neural networks, everything else.


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