Domain Bridging Associations Support Creativity

This paper proposes a new approach to support creativity through assisting the discovery of unexpected associations across di↵erent domains. This is achieved by integrating information from heterogeneous domains into a single network, enabling the interactive discovery of links across the corresponding information resources. We discuss three di↵erent pattern of domain crossing associations in this context. 1 Data-driven Creativity Support The amount of available data scientists have access to (and should consider when making decisions) continues to grow at a breath-taking pace. To make things worse, scientists work increasingly in interdisciplinary teams where information needs to be considered not only from one research eld but from a wide variety of di erent domains. Finding the relevant piece of information in such environments is di cult since no single person knows all of the necessary details. In addition, individuals do not know exactly where to look or what to look for. Classical information retrieval systems enforce the formulation of questions or queries which, for unfamiliar domains or domains that are completely unknown, is di cult if not impossible. Methods that suggest unknown and interesting pieces of information, potentially relevant to an already-known domain can help to nd a focus or encourage new ideas and spark new insights. Such methods do not necessarily answer given queries in the way traditional information retrieval systems do, but instead suggest interesting and new information, ultimately supporting creativity and outside-the-box thinking. In [1] Weisberg stipulates that a creative process is based on the ripeness of an idea and the depth of knowledge. According to Weisberg this means that the more one knows, the more likely it is that innovation is produced. According to Arthur Koestler [2] a creative act, such as producing innovation, is performed by operating on several planes, or domains of information. In order to support creativity and help trigger new innovations, we propose the integration of data from various di erent domains into one single network, thus enabling to model the concept of domain-crossing associations. These domain-bridging associations do not generate new hypotheses or ideas automatically, but aim to support creative thinking by discovering interesting relations