Table 1.

A comparison of methods of acquiring biological knowledge.

Information carrier		Author	Method	Purpose	Advantage	Disadvantage
Text	AskNature	Wang pan et al.44	Proposed web-based automatic information acquisition.	To achieve the combination of portable data and portable code by combining XML and Java.	Combining programming methods to obtain information can automatically save time.	The unified description of biological information in xml limits the inspiration for design.
		Liu Wei et al.45	Used multi-biological effects to obtain the relevance between biological knowledge and products	To use the feature clustering principle and the analogy principle to transform the target product and multi-biological effects	It is very innovative to stimulate design inspiration through the influence of nature on living things	The correlation between this kind of biological knowledge and products is difficult to discover
	Relevant corpus text	Mark et al.46	Put forward the method of describing biological phenomena to develop concepts and solve a simple problem	The research provided an outline of a strategy that will be applied in the fields of biology and engineering	The biological strategies extracted have provided diverse solutions and inspirations for solving problems.	Inability to transfer information from biology to engineering
	LIFE corpus text	Nagel and Stone47	Through an algorithm, utilized the functional basis, Design Repository, MEMIC (Morphological evaluation machine and interactive conceptualizer), organized search tool and engineering to biology thesaurus to create, filter and inspire concept variants	To discover biological inspiration and circumvent the problem of knowledge needs in different fields in the early stages of design,	The computational approach could be used to assist engineering students with discovering the connections between the biology and engineering domains and find innovative solutions to the problem	There are no hyperlinks to add detailed biological information and images to be integrated into the results, and the process takes a long time
Database	The engineering-to-biology thesaurus	Nagel23	The engineering-to-biology thesaurus has the potential to aid engineering designers with the comprehension of biological contexts by substituting Functional Basis terms for commonly used biological words	The three key goals of this thesaurus are (1) to lessen the burden when working with knowledge from the biological domain by providing a link between engineering and biological terminologies; (2) to assist designers by establishing connections between the two domains; and (3) to facilitate bioinspired design	The engineering-to-biology thesaurus increases the interaction between the users and the knowledge resource and fosters one to make associations between the engineering and biological lexicons and enhances the designer's ability to use biological information	Search only in text written in natural language format, and cannot be used to search in web-based repositories
	WordNet database	Chen et al.15	An algorithm that integrates semantic similarity calculation, data normalization and corpus technology is proposed	To calculate the compound association strength of functional combination words and realize an automatic push of biological information search keywords	The designer obtains the required biological information without the biological knowledge reserve.	The similarity calculation of this algorithm is closely related to WordNet. But WordNet is a vocabulary database which will expand the scope of retrieval
		Chiu et al.12	Proposed the natural language processing and computational linguistics for potential semantic retrieval of keywords and related collocation words	Identifying words that frequently collocated with keywords and the relationship between words	Reduce the time to find relevant biological phenomena in natural language	It takes a lot of time to identify the statistics of frequently collocation words