# Understanding of Computer and Systems Sciences

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## Introduction

Computer science, as defined in Wikipedia, “is the study of processes that interact with data and that can be represented as data in the form of programs. Systems science, according to Wikipedia, “is an interdisciplinary field that studies the nature of systems in nature, society, cognition, engineering, technology and science”. Computer and systems sciences are therefore a combination of these two definitions, the study of processes that interact with data that can be represented in the form of programs and the study of where these processes lie in a system and how those systems are related to, and affect or are affected by, other systems surrounding them.

Today we are surrounded by small personal computers that we use every day and many of us do not understand what happens behind the scenes to make it possible for us to send and receive information around the globe in seconds. Prior to starting my studies at DSV my personal computers were much of a black box to me, with the inner workings of them largely a mystery to me, computer and systems sciences have the answers to how they work, why they work that way, and the implications of these questions.

## The Roots of Computer and System Sciences

The history of computer and systems science has its roots in logic, mathematics, and engineering. In the 17th century a man named Gottfried Leibniz wanted to create a language of thought, with logical operators and rules, a script for conceptual relationships, and a vocabulary for all concepts and properties. A decade later George Boole wanted to systematize and give foundation to logic with his book on ‘Laws of Thought’ and make logic more applicable. Gottlob Frege, in the 19th century then introduced predicate logic which was used to build all mathematics from the ground up from logic, so it would be on a solid foundation. Also, in the 19th century a mathematician named David Hilbert published a number of problems that directed mathematical research forward and posed the question “Can every mathematical question be decided in a finite number of steps?”. The big question progressed to “What can be computed?”, and then to “What can be automated?” .

During the 20 th century many mathematicians tried to answer this question, Alonzo Church with his lambda calculus, Emil Post with his recursive system, and Alan Turing with the Turing machine. In the mid-20th century Turing’s work began to be associated with a broader theory of computing and modern computing theory. Engineering and technology also play a very important role in computer and systems science. New machinery solutions were developed for specific problems. Herman Hollerith, for example, developed a tabulating machine which reduced the time it took to calculate the U.S. population from over seven years to only one. The Turing machine showed that computation could be automated.

The first modern computers appeared in the 1930’s and 1940’s. They became popular for large organizations for scientific computing, engineering problems, and data processing. By the end of the 1950’s computers were mass produced, the 60’s saw computers get smaller and cheaper, in the 70’s people start having their own personal computers and the first e-mails were sent. Computers spread to homes quickly and by the 1990’s they become normal household items, and WWW was born. Today each of us have our own ‘mini-computers’ in our pockets, and multiple other computers that can seamlessly integrate and communicate with each other.

## A Systems Science

Marriam-Webster defines a system as “a set of interacting or interdependent components forming an integrated whole”. A system has a set of some things, and a relation among those things. Systems have elements such as inputs, outputs, processes, feedback, interface, environment, purpose, boundary, interrelationships, and components. Systems can be classified as abstract or physical, organic or constructed, hard or soft, open or closed, simple or complex. The systems movement evolved from the roots of mathematics, computer technology, and systems thinking. Russell Ackoff, a pioneer of systems thinking, said that “when a system is taken apart, it loses its essential properties”. Systems thinking is holistic in its view that “the whole is more than the sum of its parts”. The relationships between the parts of a system are what characterize a system. Systems science became a field of science, and scientific methodology began to be used to study systems in various disciplines. Systems science progress is strongly correlated with improving computer technology.

## Information Systems

Information systems tie systems thinking together with computer technology. Information systems is defined by Wikipedia as “the study of complementary networks of hardware and software that people and organizations use to collect, filter, process, create, and distribute data”. Information systems are used everywhere, from healthcare institutions to natural science institutions, businesses, and governments where networks of computers and databases process instructions entered by users. Information systems are so widespread that they are heavily influenced by other systems, such as the economical, political, social, court systems.

## Systems Thinking

Computer and systems science is mostly about applying systems thinking into problems that are mostly technological or can be solved using technology in the form of hardware or software. It is about how we understand the systems and how all the elements of a system relate to each other. Systems are usually so interconnected that you rarely have a single system that is not either an element of another system, or that is not composed of other systems.

Interactions between components of systems and systems themselves are the most important in systems thinking. For example, in universities a rising topic in computer science is human computer interaction, and it studies how computers and humans interact and how to make these interactions more efficient. By studying interactions with a system lens, new solutions and technology often follow. Voice-activated and controlled machines now help us control our homes, without having to get off the couch. This is a good analogy to illustrate the importance of studying interactions of elements and components in systems. If before it took us 15 minutes to do everything we wanted to do what a smart home device can accomplish in 15 seconds, in the same way making interactions more efficient make our database processes exponentially faster, hardware development exponentially more powerful and the development of new technologies possible.

Systems thinking sees interactions and not things. The combination of things as a connected whole is the main scope of systems thinking, and it aims to gain understanding of an entity through the context of its relations within a whole that it is part of. Like the interaction between human and computer creates a whole larger than the sum of its parts, systems thinking is about synergies, the way the parts create that whole. It is therefore important to understand a system in its whole context, especially how the system relates to its environment. Regarding information systems, they are influenced by politics, and a case where the environment is very relevant is China, where there has been restriction to information access by the government, namely censorship of the internet. It affects everyone who lives and works in China but will also influence anyone thinking of moving there or wanting to do business there.

## Conclusion

Computer and systems sciences is one of, if not the most, important fields multi-disciplinarily. When computer and systems sciences advance, every other field seems to progress as well. Healthcare institutions, research and development departments of universities and businesses, governments, among many others all have information needs in both collecting and producing information, and as technology advances and information processing becomes cheaper, faster and more efficient, the systems and the type of technology used in those systems change very rapidly. It is very important to have a good understanding of systems and how they function in order to be able to adapt to the vast number of fields that use computers and software. Computer and systems science graduates for example will have similar job titles among themselves but can be employed in very different kinds of companies or institutions, with the goal of improving a system, whether the entire system is computerized, or improving a system using computers.

### References

Cite this paper

Understanding of Computer and Systems Sciences. (2020, Dec 06). Retrieved from https://samploon.com/understanding-of-computer-and-systems-sciences/

FAQ

## FAQ

What do you learn in basic computer science?
Basic computer science teaches fundamental concepts of programming, algorithms, data structures, and computer architecture. It also provides hands-on experience with programming languages, software development, and problem-solving techniques.
What is a system System science?
System science is an interdisciplinary field of science that studies the nature of complex systems in nature, society, and science itself. It aims to develop an understanding of a wide range of systems, from biological systems to social systems, from information systems to ecological and environmental systems.
What is computer science and why is it important?
Computer science is the study of computers and their usage. It is important because computers are used in almost every aspect of daily life.
What is the main point of computer science?
The most important aspect of computer science is problem solving , an essential skill for life. Students study the design, development and analysis of software and hardware used to solve problems in a variety of business, scientific and social contexts.
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