- How Galileo’s invention of Telescope (New Technology) ushered in details about the Solar System and beyond
- How Newton’s discovery of Calculus (New Mathematics) helped us start a revolution in the Physical Sciences.
Computing and Computer Science are concerned with working with information and numbers. And Science is all about making accurate models (containing information and numbers) of the world. So naturally Computer Science has been playing a significant role in the Sciences.
And as I explain below, Computer Science will play an increasingly central role in Sciences in the near future.
- Theoretical Computer Science and Computational Thinking as tools for Scientific Models
- Big Data processing makes Big Sciences approachable
- Computing for Scientific Information Management
- Computers as tools for Communication and Collaboration
Theoretical Computer Science and Computational Thinking as tools for Scientific Models
Science is all about building accurate “Model”s of the world.
Before the advent of computers, the models, mostly used in science, were equations, which relate numerical measures of physical quantities.
For example, the famous E = mc^2 relates Energy, Mass and the speed of light and it’s an accurate “Model” of a particular domain of the world.
But Computer Science gave us new Models with which to describe what happens in the world in condensed forms.
For example, Computer Science helped to flourish Graph Theory and later, Network Theory. These two models (Graphs – Interconnected nodes; Networks – Dynamic Interconnected Nodes the topology of which change with time) help us “model” new domains of the world.
Examples include modeling social networks, telecommunication networks, Genetic regulatory networks in Cells and other networks.
You couldn’t model these phenomena with 19th Century Mathematics (Differential Equations).
DNA is a Discrete Information Storage Medium.
Computers are “discrete” information processing devices.
Computer Science provides us with the right tools to model and work with DNA sequences.
Big Data Processing makes Big Sciences approachable
Sciences such as Biology, Particle Physics, Astronomy and Cosmology, Atmospheric and Earth Sciences, Neurosciences and Bio-Imaging generate huge volumes of data.
It’s not possible for humans to sift through the Terabytes and Petabytes of data to find interesting patterns.
So the only way to work with the enormous volume of data that these fields currently generate is to use Computers.
Computing for Scientific Information Management
As an example, consider Pubmed  searches for searching research articles or consider how Google and Citeseer have revolutionized Scientific and Engineering research.
Computers as tools for Communication and Collaboration
Science today is largely seen as large scale collaborative effort. Computers help scientists scattered around the globe to communicate and collaborate on large scale.