Systems science
Systems science is the interdisciplinary field of science, which studies the nature of complex systems in nature, society, and science. It aims to develop interdisciplinary foundations, which are applicable in a variety of areas, such as engineering, biology, medicine and social sciences.
Systems sciences have roots in formal sciences like complex systems, cybernetics, dynamical systems theory, and systems theory, and applications in the field of the natural and social sciences and Engineering, such as Control theory, Operations research, Social systems theory, Systems biology, Systems dynamics, Systems ecology. Systems engineering and Systems psychology.

# Overview
Systems science and systemics are names for all research related to systems theory. It is defined as an emerging branch of science that studies holistic systems and tries to develop logical, mathematical, engineering and philosophical paradigms and frameworks in which physical, technological, biological, social, cognitive and metaphysical systems can be studied and developed.
Systems science pursues its study from a certain point of view: to understand humans and their environment as part of interacting systems. The aim is to study this interaction from multiple perspectives, holistically. Inherent to this approach is a comprehensive historical, contemporary and futuristic outlook. Systems science, with such an ambition and with its basic systems theory, provides a general language with which to tie together various areas of interdisciplinary communication. As such it automatically strives towards a universal science, i.e. to join together the many splintered disciplines with a "law of laws" applicable to them all and integrating all scientific knowledge.

## Quest against reductionism
A basic assumption of systems thinking is, that there is something missing with the way we think about our lives. What has become the dominant thinking of our time produces only a partial understanding of our reality and relates only to parts of our being, not the whole of it. To overcome this reductionism, a holistic way of thinking is needed to allow us to see through chaos and understand complexity. A thinking of interaction and design can help us to learn a new mode of living by considering various ways of seeing, doing and being in the world. We can then design new methods of inquiry, new modes of organization and a way of life, that will allow the rational, emotional and ethical choices for interdependent, yet autonomous, social beings.
This dominant reductionistic thinking is traced back to the French philosopher Rene Descartes, who tended to segregate the whole and advised to consider the parts in isolation. This scientific method is called the "analytical approach". The analytical approach contributed significantly to modern science and was the conceptual basis of the Industrial Revolution. Systems thinkers  stated, that today this is not enough: the world is now more interdependent, organizations are more complex, and so are the problems they face..

## Further characteristics
Senge (1990) described systems thinking as comprising five learning disciplines: personal mastery, meta models, shared vision, team learning, and the overarching discipline of systems thinking. Earlier, Capra (1982) identified several key characteristics of systems thinking, including a shift from an emphasis in the parts to the whole; a shift in attending to a single level to going back and forth between systems levels; a shift from analytic thinking to contexual thinking, or explaining things in terms of their context; a shift from seeing objects as being of primary importance to seeing relationships as critical component, or netwerk thinking; a shift from the metaphor of knowledge as a building to that of knowledge as a network; and a shift from objective to epistemic science, in which the method of questioning is integral to the scientific theories.
More recently Ossimitz (2007) summarized, that four characteristic dimensions can be seen as essential for systems thinking:
- Thinking in models: explicitly comprehended modeling
- Thinking in loops: a thinking in interrelated, systemic structures, recognizing causal loops.
- Dynamic thinking: a thinking in dynamic processes (delays, feedback loops, oscillations).
- Steering systems: the ability for practical system management and system control

# History
Systems thinking emerged and established itself as a transdiscipline in the in the 1940s and early 1950s. Systems ideas had emerged, stated Hammond (2003), from a broad range of disciplines: biology, ecology, social psychology and technology. These ideas came together in a General Systems movement, that wanted to replace that analytic approach with a more holistic approach. By focusing on the creation of a General Systems Theory they wanted to create a collaboration and integration between different disciplinary perspectives.
In the following decades Systems thinking developed in interaction with fields as engineering, management, organismic biology, cybernetics, information, ecology and social theory. Among these theories systems theory was the one metaphor according to Hammond that highlights the  relationships and interconnections among the biological, ecological, social, psychological, and technological dimensions of our increasingly complex lives.
Early approaches to using systems ideas in an applied manner, such as operation research, systems analysis and systems engineering, were suitable for tackling certain well-defined problems but were found to have limitations when faced with complex problems involving people with a variety of viewpoints and frequently at odds with one anonther. Systems thinkers responded with approaches such as systems dynamics and organizational cybernetics to tackle complexity; soft systems methodology, and interactive planning to handle subjectivity; critical systems heuristics to help the disadvantage in  situations involving conflict; and pragmatic pluralism to manage diversity. In theoretical terms, the positivism that had dominated systems thinking until the 1970s, was supplemented, as a source of support for applied work, by structuralism, interpretivism, radicalism and postmodernism.
Since the 1970s Peter Checkland witnessed a replacement of the old hard paradigm with a new vigorous soft paradigm. The hard pardigm was unable to deal with the anomalies arising, when applied in complex, human-centred organizational and societal situations. This has given way to a soft paradigm, which both preserves the achievements of the hard in its specialized domain of application and extends the area of successful operations of systems ideas to the behavioral and social arena.
According to Olsson (2004) the basic systems concepts and ideas from the founding fathers haven't changed very much over time. There has been a significant new development though since the 1990s in the epistemological "framing" of the established theoretical apparatus and this development constitutes a qualitative improvement of the systems approach in science.

# The field of systems science
- Chaos theory
- Complex systems
- Complexity theory
- Cybernetics
Biocybernetics
Engineering cybernetics
Management cybernetics
Medical cybernetics
New Cybernetics
Second-order cybernetics
- Biocybernetics
- Engineering cybernetics
- Management cybernetics
- Medical cybernetics
- New Cybernetics
- Second-order cybernetics
- Control theory
Affect control theory
Control engineering
Control systems
Dynamical systems
Perceptual control theory
- Affect control theory
- Control engineering
- Control systems
- Dynamical systems
- Perceptual control theory
- Operations research
- Systems biology
Computational systems biology
Synthetic biology
Systems immunology
- Computational systems biology
- Synthetic biology
- Systems immunology
- Systems dynamics
Social dynamics
- Social dynamics
- Systems ecology
Ecosystem ecology
- Ecosystem ecology
- Systems engineering
Biological systems engineering
Earth systems engineering and management
Enterprise systems engineering
Systems analysis
- Biological systems engineering
- Earth systems engineering and management
- Enterprise systems engineering
- Systems analysis
- Systems psychology
Ergonomics
Family systems theory
Systemic therapy
- Ergonomics
- Family systems theory
- Systemic therapy
- Systems theory
Biochemical systems theory
Ecological systems theory
Developmental systems theory
General systems theory
Living systems theory
LTI system theory
Sociotechnical systems theory
Mathematical system theory
World-systems theory
- Biochemical systems theory
- Ecological systems theory
- Developmental systems theory
- General systems theory
- Living systems theory
- LTI system theory
- Sociotechnical systems theory
- Mathematical system theory
- World-systems theory

# Systems thinking concepts
- Throughput, Membership, Conflict management, Decisions Systems, Learning and Control Systems.
- Openness, purposefulness, multidimensionality, emergent property, counterintuitiveness

# Systems thinking theories
Since the emerge of the General Systems Research in the 1950s systems thinking has been developed into all kinds of theoretical frameworks. The following overview will only show the most basic types.
- Soft Systems Methodology (SSM) is an approach to organisational process modelling and it can  be used both for general problem solving and in the management of change. It was developed in England by academics at the University of Lancaster Systems Department through a ten year Action Research programme.
- System Development Methodology (SDM) is a general term applied to a variety of structured, organized processes for developing information technology and embedded software systems.

# Systems scientists
Notable contributors to the field include Jay Forrester, Humberto Maturana, Stuart Kauffman, Norbert Wiener, William Ross Ashby, Heinz von Foerster and Charles Francois.
General systems scientists can be divided into three generations. The founders of the systems movement like ludwig von Bertalanffy, Kenneth Boulding, Ralph Gerard, James Grier Miller and Anatol  Rapoport were all born between 1900 and 1920. They all came from different natural and social science disciplines and joint forces in the 1950s to established the general systems theory paradigm. Along with the organization of their efforts a first generation of systems scientists rose. Among them were other scientists like Ackoff, Ashby and Churchman, who popularized the systems concept in the 1950s and 1960s. These scientists inspired and educated a second generation with more famous scientist like Ervin Laszlo (1932) and Fritjof Capra (1939), who wrote about systems theory in the 1970s and 1980s. Others got acquainted and started studying these works in the 1980s and started writing about it since the 1990s. Debora Hammond can be seen as a typical representative of these third generation of general systems scientists.

# Organizations
In the field of systems science the International Federation for Systems Research (IFSR) is an international federation for global and local societies in the field of systems science. This federation is a non-profit, scientific and educational agency founded in 1981, and constituted of some thirty member organizations from various countries. The overall purpose of this Federation is to advance cybernetic and systems research and systems applications and to serve the international systems community.
The International Society for the Systems Sciences (ISSS) is an organisation for interdisciplinary collaboration and synthesis of systems sciences. The ISSS is unique among systems-oriented institutions in terms of the breadth of its scope, bringing together scholars and practitioners from academic, business, government, and non-profit organizations. Based on fifty years of tremendous interdisciplinary research from the scientific study of complex systems to interactive approaches in management and community development. This society was initially conceived in 1954 at the Stanford Center for Advanced Study in the Behavioral Sciences by Ludwig von Bertalanffy, Kenneth Boulding, Ralph Gerard, and Anatol Rapoport.
The most known research institute in the field is the Santa Fe Institute (SFI) located in Santa Fe, New Mexico, United States, dedicated to the study of complex systems. This institute was founded in 1984 by George Cowan, David Pines, Stirling Colgate, Murray Gell-Mann, Nick Metropolis, Herb Anderson, Peter A. Carruthers, and Richard Slansky. All but Pines and Gell-Mann were scientists with Los Alamos National Laboratory. SFI's original mission was to disseminate the notion of a separate interdisciplinary research area, complexity theory referred to at SFI as complexity science.