Cellular automata (CA) are mathematical models used to simulate complex systems or processes. In several fields, including biology, physics, and chemistry, CA are employed to analyze phenomena such as the growth of plants, DNA evolution, and embryogenesis. In the 1940s John von Neumann formalized the idea of cellular automata in order to create a theoretical model for a self-reproducing machine. Von Neumann's work was motivated by his attempt to understand biological evolution and self-reproduction.

John von Neumann was a Hungarian mathematician who made important contributions to mathematics, physics, computer science, and the area of artificial life. He was born in Budapest, Hungary, on 28 December 1903. His mother was Margit von Neumann and his father was Max von Neumann. His work on artificial life focused on the problem of the self-reproduction of machines. Von Neumann initially discussed self-reproducing machines in his Hixon Symposium paper "The General and Logical Theory of Automata" published in 1948. He continued to write about this topic in his book Theory of Self-Reproducing Automata, which was completed and published after his death by Arthur Walter Burks in 1966.

In 1991, Hugo de Garis' article "Genetic Programming: Artificial Nervous Systems, Artificial Embryos and Embryological Electronics" was published in the book Parallel Problem Solving from Nature. With this article de Garis hoped to create what he envisioned as a new branch of artificial embryology called embryonics (short term for "embryological electronics"). Embryonics is based on the idea of adapting the processes found in embryonic development to build artificial systems.

The Game of Life, or just Life, is a one-person game that was created by the English mathematician John Horton Conway in the late 1960s. It is a simple representation of birth, death, development, and evolution in a population of living organisms, such as bacteria. Martin Gardner popularized the Game of Life by writing two articles for his column "Mathematical Games" in the journal Scientific American in 1970 and 1971. There exist several websites that provide the Game of Life as a download or as an online game.

In 1952 the article "The Chemical Basis of Morphogenesis" by the British mathematician and logician Alan M. Turing was published in Philosophical Transactions of the Royal Society of London. In that article Turing describes a mathematical model of the growing embryo. He uses this model to show how embryos develop patterns and structures (e.g., coat patterns and limbs, respectively). Turing's mathematical approach became fundamental for explaining the developmental process of embryos. In the 1970s, for instance, scientists Alfred Gierer and Hans Meinhardt used Turing's model to work out how the patterns on seashells develop.

Alan Mathison Turing was a British mathematician and computer scientist who lived in the early twentieth century. Among important contributions in the field of mathematics, computer science, and philosophy, he developed a mathematical model of morphogenesis. This model describing biological growth became fundamental for research on the process of embryo development.

Computational tools in the digital humanities often either work on the macro-scale, enabling researchers to analyze huge amounts of data, or on the micro-scale, supporting scholars in the interpretation and analysis of individual documents. The proposed research system that was developed in the context of this dissertation, known as the Quadriga System, works to bridge these two extremes by offering tools to support close reading and interpretation of texts, while at the same time providing a means for collaboration and data collection that could lead to analyses based on big datasets.

Computational tools in the digital humanities often either work on the macro-scale, enabling researchers to analyze huge amounts of data, or on the micro-scale, supporting scholars in the interpretation and analysis of individual documents. The proposed research system that was developed in the context of this dissertation ("Quadriga System") works to bridge these two extremes by offering tools to support close reading and interpretation of texts, while at the same time providing a means for collaboration and data collection that could lead to analyses based on big datasets. In the field of history of science, researchers usually use unstructured data such as texts or images. To computationally analyze such data, it first has to be transformed into a machine-understandable format. The Quadriga System is based on the idea to represent texts as graphs of contextualized triples (or quadruples). Those graphs (or networks) can then be mathematically analyzed and visualized. This dissertation describes two projects that use the Quadriga System for the analysis and exploration of texts and the creation of social networks. Furthermore, a model for digital humanities education is proposed that brings together students from the humanities and computer science in order to develop user-oriented, innovative tools, methods, and infrastructures.