The goal is to develop an interactively explorable, graphical application for analyzing the historical development and contemporary use of disciplinary and transdisciplinary concepts of synergy.
Synergy (Greek: interaction, cooperation) generally refers to cooperative interactions that lead or should lead to a new quality. Psychology, neuroscience, linguistics, sociology, economics and theology were inspired to new theoretical considerations by the influential teaching of the architect and philosopher Richard Buckminster Fuller on synergetic planning and design and by the synergetics, which the physicist Hermann Haken scientifically founded for the interdisciplinary description of complex self-organizing systems.
The term has become highly en vogue and overused, its origin and meaning though remain fairly vague. Nevertheless, it is a key concept in many disciplines, and even more, a prospective and promising way of thinking. The Wiki platform SynergieWissen has been created as a room for open exchange on synergy and has been tracing and discussing concepts and synergetic approaches in religion, the humanities, natural sciences, technology, and the arts. The idea behind it is to create a digital note box that can be used as a tool for transparent research and new knowledge generation; an open-access encyclopedia. Moreover, SynergieWissen offers the opportunity for collaboration with IT in order to develop creative tools for generating new knowledge.
For an introduction in the diversity of meaning of 'synergy' see http://www.zflprojekte.de/synergie/doku.php?id=features:einfuehrung_in_die_synergie
Adopting a suitable data analysis procedure for extracting concepts and semantic information from non-coded text files, tags, and notes at the DokuWiki SynergieWissen (http://www.zflprojekte.de/synergie/)
The objectives of the thesis are the development, application, and testing of DokuWiki plugins for natural language processing and data visualization.
Using e.g. n-gram, entity extraction (Standford), tag clouds, concept maps (WordNet), and methods of graph clustering