Data Modeling Challenges Today and Going Forward

What is data modeling and why is it important for society in general, not just business?  Increasingly the corporate world has come to dominate our culture,  and the right data at the right time is vital, yet how well does this work?  What are the implications for protection of information when so many consumers and idealists want to communicate and are so trusting?  We are at a crucial turning point with great hope and great concerns.  Higher Ed is excited, as we read in this Campus Technology article by Mary Grush, a Q&A with Ray Uzwyshyn, “Coming of Ag: The Online Data Research Repository“:

Conclusion: “Currently our largest granting agencies (including NSF, NIH, or USDA) mandate and encourage data sharing processes, so the future is bright on pragmatic levels. Historically, the advancement of scientific discovery has been predicated on the sharing of knowledge and data. This is true from Newton to Einstein. As Newton put this, “If I have been able to see a little further, it is because I have been allowed to stand on the shoulders of Giants”. The larger idea is that no researcher is working in a vacuum, but rather within a scholarly community with a past trajectory and a forward telos. Because of this, I’m encouraged by these new technological possibilities for organization and sharing from this great ocean of data opening before us. Our software infrastructures are now able to allow this next renaissance of discovery, enabling new insights and synthesis from current results. Hopefully this will also allow a few of those next intrepid explorers to stand on the shoulders of giants.”

4 thoughts on “Data Modeling Challenges Today and Going Forward”

  1. I agree, the amount of data available today is not only overwhelming with the advent of IT and the ability to store Big Data in massive data-bases; people, organizations/corporations, scientists, governments can access so much data and clean and analyze it efficiently. I know that the military also uses a lot of data modeling to predict or forecast outcomes of tactical or logistical decisions. The department of energy provides a massive amount of data on buildings across the nation regarding their energy efficiency by sector and industry. I recently did a study to see correlations between the energy efficiency score of an actual building and their energystar ratings, used regression modeling to show the correlation. Very useful data.

    1. Steve, your comment reminds me of an article in my Scientific American, June 2017 “Designing Tomorrow” featuring the “Architect of the Future” Bjarke Ingels, the chief visionary of the firm BIG (Bjarke Ingels Group). I quote from the author of the piece, Justin Davidson: “What he has in mind is not the radical, grand-scale drama of invention but a laborious process of nudging the present along a little at a time. The technological revolutions that have shaped the past few decades — the internet, supercomputing, automation — have centered on airy data. Now, he predicts, comes the tangible, buildable stuff: roads, buildings, power plants, museums. ‘If you go back 50 or 60 years, science fiction was about physical exploration,’ he says. ‘Actually, though, the physical realm hasn’t seen much innovation. The great leaps of the ’60s’ — he mentions the domed biosphere and Habitat 67, Moshe Safdie’s modular, prefab concrete apartment complex that debuted at the Montreal Expo in 1967 — ‘slowed down in the last half-century. Confidence that architecture could build the future disappeared. Now the physical world is again on the agenda’.”

    2. Steve, big data can measure poverty and famine around the world via climate analysis and satellite imaging, and now can predict this quite specifically in America. In Science Daily we read: Summary: “Unmitigated climate change will make the United States poorer and more unequal, according to a new study. The poorest third of counties could sustain economic damages costing as much as 20 percent of their income if warming proceeds unabated.”

      “We could not have done this study without the ongoing revolution in big data and computing,” said Rising, a Ciriacy-Wantrup Postdoctoral Fellow at UC Berkeley, describing the 29,000 simulations of the national economy run for the project. “For the first time in history, we can use these tools to peer ahead into the future. We are making decisions today about the kinds of lives we and our children want to lead. Had the computing revolution come twenty years later, we wouldn’t be able to see the economic hole we’re digging for ourselves.”
      Rutgers University. “Climate change damages US economy, increases inequality: Severe costs ahead especially in south and lower midwest, pioneering analysis projects.” ScienceDaily. ScienceDaily, 29 June 2017. .

      Solomon Hsiang et al. Estimating economic damage from climate change in the United States. Science, 2017 DOI: 10.1126/science.aal4369

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