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.