An Ambient semantic intelligence model for scientific research

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2016
Subaşı, Ahmet
Scientific curiosity is the key motivation behind most of the scientific and philosophical achievements of human kind. It is defined in our theory as an intrinsically motivated desire to make sense of potentially everything that are proper subjects of science and philosophy. Paradoxically, the concept of scientific curiosity itself is one of the least studied subjects in the history of science and philosophy. In an age of ‘attention economy’ where the biggest problem is not the unavailability of information but its overabundance, the need for effective information-filtering systems becomes more conspicuous. Therefore, studying the design of information systems that effectively adapt to human curiosity is a highly significant area of research. Our study first constructs a theory of scientific curiosity which provides a grounding for an effective computational model that aims at augmenting scientific curiosity and aiding scientific research. The theory initially delineates the concept of ‘scientific curiosity’ and constructs a unified framework within which various insights and data coming form a variety of research areas come together in a concise and coherent way. The basic forces that influence the direction of human curiosity among alternative items of information, i.e. content-bearing resources, are described as the cognitive dynamics of scientific curiosity. Those dynamics, which are rooted in human personality, are (1) expansion dynamics, (2) completion dynamics, (3) explication dynamics, (4) perfection dynamics and (5) interest dynamics. The influences coming from each dynamics interact in analogy to a vector space and such interactions determine the final motion of human curiosity. Those motions are formulated as patterns of selections made by scientific curiosity in the face of time constraint and the identified patterns are used for analyzing the curiosity traits of individuals. Human curiosity interacts strongly with the technological environment in line with the idea of extended cognition. With the image of a scientific researcher embedded into a library, the study clarifies the coupling of and interaction between human curiosity and the available external resources. This perspective allows for a smooth transition from a unified theory of curiosity to the question of what types of technology designs can best augment scientific curiosity and aid scientific research. After this step the available technologies are analyzed and the concept of ambient semantic intelligence for scientific research is introduced. Ambient systems are highly adaptive, personalized and context-aware systems, whereas semantic intelligence has the capabilities of representing ontology-based meaning-systems effectively, enabling semantic interoperability and filling semantic gaps via reasoners. Ambient semantic intelligence combines those features and enables systems that process ontology-based semantic information and adapt to human curiosity traits, which in turn augments human curiosity and aids scientific research in a unique way. The thesis includes a toy model that implements such a design and discusses its problems as well as significance for the future of Cognitive Science.
Citation Formats
A. Subaşı, “An Ambient semantic intelligence model for scientific research,” Ph.D. - Doctoral Program, 2016.