The trade-off: a central concept for biomimetics

Abstract

Biology is gradually yielding lessons and ideas for technology, but the resulting innovation is adventitious. Biology is also very complex: currently with no underlying analytical model and so cannot adequately be interrogated by technologists. A concept which can bridge this gap is the trade-off, which leads to speciation in biology and aspects of design and problem-solving in engineering. An ontology is described which uses biological organisms as case studies. Terms have been adapted from TRIZ (the Russian system for solving problems creatively) to define trade-offs and the factors by which they can be manipulated. As an example the ontology resolves the biological trade-off "speed-accuracy", yielding factors for a biomimetic version of the trade-off. These are Feedback (e.g. errorcorrection), Dynamic Response (e.g. control of thresholds), Adaptation (e.g. ability to predict) and Consolidation (e.g. stochastic accumulation). Since much of evolution can be related to the resolution of trade-offs, it is expected that this ontology can also categorise aspects of natural selection. Multi-criteria analysis will allow more versatile numerical models to be developed.

E2BMO: Facilitating User Interaction with a BioMimetic Ontology via Semantic Translation and Interface Design

“…The aim of this paper is to draw attention to the copious tools available that facilitate the biomimicry process and to demonstrate how merging existing tools through a user interface design could potentially facilitate practitioners' navigation through the process in a more systematic and collaborative way, broadening solution discovery. Through this paper, we propose a computer-aided user interface that elaborates on a thesaurus-based functional approach to biomimicry to include complex environmental and behavioral interactions through integration with the BioMimetic Ontology (BMO) [31]. The focus of this work is to provide a portal for users to access information from within the BMO; we do not aim to make this information more interpretable to the user, we simply provide the opportunity to access it.…”

“…Upon interviewing innovation consultants actively practicing biomimicry within an industrial context, the Engineering-to-Biology (E2B) Thesaurus [19] was selected, as it fulfilled our specific criteria for usability, accessibility, and cross-domain functionality. Our second tool of choice, the BioMimetic Ontology (BMO) [31], was selected as ontologies, due to their ability to organize complex collections of data, have proven to be successful across a variety of fields, including bioinformatics and medicine [32]. Therefore, an ontology that captures the intricacies of natural systems became the obvious tool of choice.…”

“…In this way, information becomes knowledge. The BioMimetic Ontology (BMO) aims to bridge the gap between engineering and biology by using trade-offs, making biological strategies more accessible to engineering practitioners [31]. TRIZ (acronym for 'Teorija Reshenija Izobretateliskih Zadatch', which translates to 'Theory of Solving Problems Inventively'), developed in the second half of the last century by Genrich Altshuller [34], is a method for solving technical challenges.…”

“…Defining a problem in a neutral and objective manner generalizes the problem so that solutions to problems, that can be defined in the same or similar way, can offer insight. This list of potential solutions or design insights are known as the inventive principles (IPs) and are numbered 1 to 40 [31]. In short, through the 'contradiction matrix' of TRIZ, conflicts help to break down problems and find innovative solutions, called the inventive principles (IPs).…”

“…For more information, refer to Section 4. While implicit in TRIZ [31], trade-offs become the core concept of the BMO. BMO selects which TRIZ IP's recommend possible solutions or insights to a specific trade-off, based on biological literature describing how living role models resolved such trade-off.…”