A framework for scientific knowledge generation

This paper investigates the notional development of various approaches claiming to add value in knowledge generation during the 20th century, with the aim to identify what it is that enhances productiveness in knowledge generation. Observing that knowledge generation is a complex phenomenon, an approach is used for the investigation that was developed specifically to study un–deterministic complex systems. A list of salient features for scientific knowledge generation is presented as a result. In addition to these features, various problem types are identified from literature. These two are then integrated to provide a proposed framework for scientific knowledge generation, which is trans–disciplinary and useful for scientific problem–solving in a pluralist reality. A case study illustrates the implementation of this framework.