[Originally posted in May 2013 – We’re finding this article content is as viable today as it was then, so we’re re-posting]
The “I” in Information Technology is incredibly broad, so why do we specifically focus on “spatial data” when approaching integrated data science problems? Why is it first in our data areas: Geospatial, Open, Big, IoT? We get this question a lot. Our reason for focusing on Geospatial is that it is multi-dimensional. It crosses many different ways of thinking, audiences of varying maturity, progressions, sciences, models, and times.
Analyzing the History of Information
From the perspective of time, and mostly following Moore’s Law, we know technology is developing far too quickly. The long-term applicability of Moore’s Law has been questioned recently (MIT declared Moore’s Law dead in 2016, then IBM noted it was alive again in 2017). However, this rapid doubling – 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024, 2048, 5096, 10k, 20k, and so forth– has seen a 10,000-fold increase in computing and storage capability in fewer than 20 years. 90% of that increase occurring in the last 10 years alone.
To show this progress in terms of the “I” in “IT”, we have put together a few views on this rapid curve shown below. The curve measures the progression from data to information to knowledge, and to wisdom (y) over time (x).
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