ASTR633 Astrophysical Techniques Course slides Big Data
https://www.youtube.com/watch?v=VXIWeUBb2Jk&t=1713s � 2
Your thoughts (>1 person) • Open access to data => broadening of talent pool / large collaborations (“the sky is flat”) • Four paradigms of science discovery • Challenge of visualizing high dimensional data • Data-driven science is not about data, its about knowledge extraction • Computer science is the new mathematics • The limitations of human bandwidth and memory • Theory produces datasets now, not formulae • Any individual will only do a small fraction of the science with a (large) dataset that is inherently there � 3
Your thoughts (1 person) • Growing need to bridge gap between astronomy and computer science (X-informatics) • You can show at most ~10 (probably less) dimensions on paper • Applied CS and IT is creating a new scientific methodology • Science may progress more through incremental advances in collaborations more than paradigm shifts by a super genius � 4
Some additional thoughts (some yours, some mine) • for the first time in history, most data will not be seen by humans • data mining algorithms don't extrapolate to large datasets well => new interesting research areas • most data and constructs cannot be comprehended by humans directly => we need machine assisted discovery • but we still need good scalable data exploration and mining tools • e ff ective visualization is the bridge between quantitative information and human intuition; how do you do this for multi- dimensional space? � 5
Some additional thoughts (some yours, some mine) • Implications for education and training from open/flat skies? • the complexity of data sets and meaningful constructs is starting to exceed the cognitive capacity of the human brain “ science on the carbon-silicon interface” • data fusion + data mining + machine learning = 4th paradigm � 6
Some additional thoughts (some yours, some mine) • computer science is the "new mathematics" and the key to interdisciplinary science / crossing 19th century science boundaries • dealing with data is just the first step; knowledge discovery should be the primary focus • we need good scientists to lead archives & virtual observatories � 7
Some additional thoughts • Science is changing focus from ownership of data to ownership of expertise • implications for our “unfair” Hawaii advantage? � 8
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