In the late of the 20th century when the advance of technology ran up against various limitations, an innovative progress became indispensable. Just at this time there was an advent of biomimicry technology focusing on the nature’s survival principles to find out creatures’ traits so that the leap of new technology might be materialized (Lurie-Luke, 2014). Out of the human-centered thinking which had simply considered the nature as the subject of curiosity or development emerged a new way of thinking for learning from the nature to figure out solutions (Lim et al., 2018). Biomimicry a new social technology in the future which applies any basic structure or principle of the ecosystem or of the biological resource so that any environmental or social problems could be solved (Benyus, 1997; Bhushan, 2009), includes approaches for finding out environment-friendly and sustainable solutions through the mimicry of the structures optimized by their adaptation to the environment for a long time and of the efficient strategy for using material and energy (Bae et al., 2019; Geol, 2013; NIE, 2020).

Since most of the biological and ecological principles existing in the nature have the efficiency of remarkably excellent resources, they could be the superb subjects for mimicry (Dickinson, 1999; Stone et al., 2014) and have a strong potential of producing the outcome which is a solution with a high sustainability (Chakrabarti, 2014). In spite of this positive expectation and experimental proof, there exist several limitations to the development of new technology which enables the utilization of the biomimicry, a representative one of which is that, compared with the total amount of the information in the nature, what researchers and engineers can utilize themselves is too little for them to explore the knowledge on the nature for themselves, which can’t help limiting their capability of sorting out the characteristics of biomimicry that are applicable to any problem solving (Kim, 2018; Vincent et al., 2006).

Around the 2000’s, the USA led research of the methods for exploring the biological and ecological information to develop the system which enables the utilization of biomimicry principles (NIE, 2020). In conducted the research for exploring the biological and ecological information for the construction of information and search system (Kim and Lee, 2017; Nagel et al., 2017). It is known that the system providing the most biological system information as of now is furnishing the information on 21,000 genera (Kim and Lee, 2017). Most of the attempts employed for the development of biomimicry technology, however, undergo lots of trial-and-errors before finding out any solutions qualitatively, and those tools used for technology development are too extensive to produce enough solutions. In addition, it is often inevitable that related experts be equipped with not only the knowledge of engineering technology but also the expertise on biological and ecological function, structure, behavior and production so that they may develop new technology (Vincent, 2014).

Therefore, it is necessary that various consumers such as engineers, entrepreneurs and managers as well as researchers should develop a service platform which supports a practical development of biomimicry technology. We suggest a target-model after researching case investigation and interviewing those working in various fields while looking into its expectation effectiveness in order to meet the needs of consumers in different areas and provide the plans for construction and management of a knowledge service platform which enables the support for the development of biomimicry technology.


As analysis materials were used the findings from the research of 31 DB’s on biological and ecological information home and abroad, the results from the investigation of the 5 current biomimicry DB’s and the outcomes from in-depth interviews of 17 experts on biomimicry conducted from October 2019 to March 2020 both face-to-face and in written form. First, the biological and ecological information DB constructed home and abroad was analyzed for the classification of basic-data types along with the categorization of the key status of biomimicry DB construction and management into 6 items for appreciation of features. Second, a customer journey map was schematized on the basis of the findings from the interview of related experts so as to examine how those consumers explore biomimicry information and apply it to technology development. Last, a target-model was suggested that enables determining the role of biomimicry knowledge service platform and establishing the plans for its construction and management.


Biological and ecological information DB type and biomimicry DB cases

Biological and ecological basic data type

For biomimicry knowledge DB to support biomimicry technology in omnidirectional ways, it is necessary that biological and ecological information DB, which is fundamental, were analyzed. This study, not limiting the types of basic data to what is directly related to biomimicry domains, investigated the cases of 31 biological and ecological basic data including Zoology, Ecology, Bioinformatics, and OMICS DB, for it would be difficult to predetermine which data could be of indirect help for the extraction of biological and ecological principle afterward (Table 1). Some DBs are not allowed to be accessed and utilized publicly. In this case, references were used (Hulo et al., 2006; Maglott et al., 2011; Thorisson et al., 2005; Xenarios et al., 2000). The investigation found that most of the basic data require a certain license (only internal access permitted) while several DB delivery services like European Molecular Biology Lab are open for the public to access API (application programming interface) and download DB for the promotion of public interest.

Biological and ecological information DB’s were classified into two types. First, classified according to the scale of biological and ecological information, is being used for grouping the traits of biological and ecological basic data (Table 2). It was planned to track how the basic data was being utilized not only for conceiving any ideas but also for materializing finished products. To put it concretely, it is defined as biomimomic traceability matrix (BTM), which is a model modified from STM (science traceability matrix) resulting from tracing and analyzing, from the viewpoint of information flow, each decision-making process for engineering implementation of the scientific knowledge produced from the frame of NASA’s existing science projects (Martinez, 2017).

The other is the type of biological and ecological information DBʼs by industrial sector. Since the sector of biomimetic industry have different categories due to the method of its definition, the analysis was carried out on the basis of the biomimetic industrial sector defined by civil and government agencies at home and abroad (Fig. 1). Though Fermanian Business and Economic Institute (FBEI) presented that there were 12 sectors which would be influenced by biomimicry technology, it was confirmed that each country or each agency recognizes the targets which are subject to the application of biomimicry technology a bit differently. When BTM is employed to examine 12 traditional industrial sectors which will be benefited from the substantiation of biomimicry technology by FBEI (2013), the area of traditional industrial sectors and those needing biological and ecological basic data can be understood because it is possible to infer what level of biological and ecological basic data have an effect on which industrial sectors.

In Korea, North Gyeongsang and South Jeolla Provincial governments defined the category of their own biomimicry technologies when writing their reports for the attraction of biomimicry cluster, which showed some differences in their recognition on the diversity of biological and ecological basic data group based on BTM and the appreciation of biomimicry technology industrial sectors. Furthermore, it was found that the biomimicry technology category recognized by those two governments is relatively narrower than those recognized by foreign agencies (FBEI & Centre d'études et d'expertise en biomimétisme [CEEBIOS]). Given that there is not enough consideration of those areas requiring phenotypic property information and phylogenetic information, it is obvious that there is the necessity for developing biomimicry knowledge service platform with the goal of acquiring the maximum amount of international biological and ecological basic data with the 12 above industrial sectors covered.

Cases of major biomimicry DB

After the examination of 6 items such as type and information amount of biomimicry DB, search and application function and probability of tech-development support in 5 DB’s (AskNature, NatureTech, IDEA-INSPIRE, DANE, Bio-TRIZ) managed currently home and abroad, it was found that they were being managed, only in the short term, for the purpose of promoting the information on the principles of biomimicry and providing various users with interesting information (Table 3). This problem was found to be caused by the proactive and follow-up management service for the substantiation and commercialization of biomimicry technology and the intolerance of the provided biological and ecological principles. Accordingly, it was determined that future biomimicry knowledge service platform haves discrimination from biomimicry DB from the viewpoint of both short and long strategy for the purpose of service, the relevance of provided information, the support of scenario for information search and the position of service.

Customer journey map by mental model

Mental model is a behavior that users extract positive or negative elements in their existing behavior patterns consciously or unconsciously through interviews, based on which the difficulties and predicaments during their experience of substantiation and commercialization can be drawn out so that any elements needed for the substantiation and commercialization support programs may be analyzed (Jones et al., 2011). Particularly, in this study, the experience of substantiation process was schematized in the form of customer journey map.

It was found how experts was exploring the information and knowledge on biomimicry. The experts were asked what information they wanted and expected to input and output and what search methods they employed in the cases of concrete exploration (not only when searching online but also when exploring books, dissertations and their acquaintances around them). We found the mental model of the process of implementing biomimicry-ideas into products through a 5-step user journey map (Fig. 2).

The common features of those subjects found from the interview were that they wanted ‘Additional Learning’ of the knowledge on biomimicry, biology and ecology through ‘Knowledge Seeking’. It is absolutely true that the technical terms used in relevant domains must have been unfamiliar to them while acquiring the information on new domains. However, they still wanted to keep learning these new terms consistently through the process of knowledge seeking. The fact was also revealed that not only they referred to the texts and the schematized images explaining any relevant terms or methods, but they asked their acquaintances (fellow-researchers or relevant experts) very frequently during the learning process as well. On the other hand, they showed a pretty picky tendency when selecting the objects of information exploration for the satisfying reliability on the newly acquired information. The methods to secure reliability on media are seen to vary depending on the experience of each researcher, which is the reliance on the media’s reputation, or on their acquaintance’s expertise, or on the paper citation counts and article clipping number or the backward search of the context related to their own professional field among already published contents in media.

It was interesting that a great many of the interviewees had their own bias toward biomimicry. Especially those experts who had dedicated to a certain research field were found to have the firmest conviction for methodology and knowledge-seeking method used widely in their professional field while heavily relying on them. Interviewees were heavily dependent on the biological and ecological information intuitively coming to their mind to keep searching for information by using familiar methods of knowledge-seeking with any relevant keywords rather than opening their mind to completely new possibilities for searching the information or exercising their own ideas.

Through the insight from these interviews was obtained the functional requirement that there is a specific need to permit each of those experts individually specialized knowledge-seeking. Furthermore, it was determined that first of all it should be proposed as a prior task to build reliability between experts and knowledge DB with the application of the method providing the information with close relevance if any information so widely known as to be stale has the same context and content as those of what any experts try to explore.

It was summarized that there are 3 key functional requirements: (1) Function of free knowledge seeking, (2) Function of summarizing knowledge, and (3) Function of information verification. In particular, it was confirmed that the network among experts could be supported and at the same time an online-cooperation system support is indispensable for making it possible for them to collect knowledge-seeking patterns generated during networking.

Target model for biomimicry knowledge service platform

It was found that, for an efficient utilization of biomimicry knowledge service platform with all the above facts, the target model should be established by the phase of short, medium and long terms and the supporting strategy suitable for each phase is needed (Fig. 3). Ultimately all phases for substantiation of biomimicry technology should be backed up and the establishment of 5-phased strategy for biomimicry knowledge search/incubation and education-substantiation-spread and sharing is indispensable.

Biomimicry knowledge service platform of a short-term conception provides the function of searching biomimic ideas based on key social issues, restrictively supports researchers’ network for the resolution of any present issue of substantiation and promotes the examples of innovative commercialization. The biomimicry knowledge service platform with a mid-and-long term concept will be driven as a complete platform, constructed and managed with the goal of realizing the service which have a satisfying support for the inference and substantiation of the biomimicry information foothold as a functional requirement mentioned above. For this, the functions of information search and application and of support for the solution to any designing process problem and commercialization could be implemented.


Those existing biological and ecological information DB and biomimicry DB was materialized only the simple function for information search. Unlike any common information search, the knowledge-seeking for the development of biomimicry technology is able to extract creative ideas from the fragments of similar knowledge. Therefore, the biomimicry knowledge service platform should realize the pre-and-post management service for the biomimicry ideas which can support the development of biomimicry technology.

The ultimate expectation effects of biomimicry knowledge service platform are the followings: (1) Consumers of biomimicry can search any technical idea very easily and fast, (2) The innovation of biomimicry which has been impracticable due to a knowledge barrier becomes possible, (3) The industrialization of indigenous species in Nagoya Protocol can be accelerated, (4) The decision of technical standards in every industrial field interested in the industrialization of biomimicry technology will become possible, which will be helpful to guiding the development of international standards and leading technology, and finally (5) The biomimicry knowledge service platform will result in the creation of new markets and new industries and then the creation of new jobs.

Conflict of Interest

The authors declare that they have no competing interests.



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Figures and Tables
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Fig. 1

Difference in recognition of biomimicry industrial sector and diversity of biological and ecological basic data group. NGSP, North Gyeongsang Provincial Government; SJLP, South Jeolla Provincial Government; FBEI, Fermanian Business and Economic Institute; EPFL, École Polytechnique Fédérale de Lausanne; CEEBIOS, Centre d'études et d'expertise en biomimétisme.

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Fig. 2

Customer journey map by mental model utilizing biomimicry knowledge.

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Fig. 3

Mid-to-long term target model of biomimicry knowledge service platform. API, application programming interface; AWS, Amazon Web Services.

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Table 1

Types of biological and ecological information DB

Data classification Name of basic DB Development or management agency
Meta DB ConsensusPathDB ( Max Planck Institute for Molecular Genetics
Entrez (Maglott et al., 2011) National Center for Biotechnology Information
Neuroscience Information Framework
University of California, San Diego
Model Organism DB PomBase ( University of Cambridge, University College London
Nucleic Acid DB DNA Data Bank of Japan
Center for Information Biology and DNA Data Bank of Japan
EMBL ( European Molecular Biology Laboratory
National Center for Biotechnology Information
23andMe ( 23andMe
HapMap (Thorisson et al., 2005) National Human Genome Research Institute
OMIM ( Johns Hopkins University
RefSeq ( National Center for Biotechnology Information
1000 Genomes Project
EMBL - European Bioinformatics Institute
Protein Sequence DB Database of Interacting Proteins
(Xenarios et al., 2000)
University of California, Los Angeles
DisProt ( University of Padua
InterPro ( European Bioinformatics Institute
MobiDB ( University of Padua
neXtProt ( Swiss Institute of Bioinformatics
Pfam ( European Molecular Biology Laboratory
PROSITE (Hulo et al., 2006) Swiss Institute of Bioinformatics
Protein Structure DB Protein Data Bank ( World Wide Protein Data Bank
SCOP ( University of Cambridge
Taxonomy Integrated Taxonomic Information System
Smithsonian Institution
EggNOG ( European Molecular Biology Laboratory
Characteristics Map of Life ( University of Cambridge
BIOTIC ( National Marine Biological Library
TRY ( Future Earth
FishBase ( Sheryl Yap and Rainer Froese
Gene Expression DB Ensembl Genomes
European Molecular Biology Laboratory
Ensembl ( European Molecular Biology Laboratory
Ensembl Metazoa
European Molecular Biology Laboratory
Ensembl Bacteria
European Molecular Biology Laboratory
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Table 2

Biological and ecological basic DB classified by BTM

Classification Name of basic DB
Biological Traits Trait Information of Map of Life, BIOTIC, TRY, etc.
Identification information of Delta Project (in Netherlands), FishBase, etc.
Biodiversity Information of CBD, EcoBank, etc.
Organismal Complexity Taxonomy Information of ITIS, etc.
Phylogency Information of EggNOG, etc.
Genom Information of Ensembl, Ensembl Genomes, etc. Ensembl Metazoa, Bacteria
Specific Function Protein Information of DisProt, SCOP, Protein Data Bank
Ecological Information of EcologicalDataWiKi, etc.
Molecular Instantiation Nucleic Acid Information of GenBank, etc.
Biochemistry Pathway Information of ConsensusPathDB, etc.
Technological Implementation Dissertation Information of PubMed, JSTOR, etc.
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Table 3

Major biomimicry DB

DB name Institution Level of knowledge basis Degree of DB sustainability Service accessibility Expandability of connectivity to other areas Price
AskNature1) Biomimicry Institute +
Arrangement of paper abstract
Curator handwork
Access to online
DB of blog type
Cost for visiting training
Consulting & training of biomimetic expert
Nature Tech2) Tohoku University ++
SEM image included
Researcher handwork
Access to online
Limitation to biomimicry
Online platform
Knowledge on physics included
DB for test
- - - Online platform
Limitation to functional vocabulary
DB for test
Access to online
- - Online platform & education of biomimetic in middle and high school
BioTRIZ5) BioTRIZ (Univ. of Bath)(Britain) ++
Knowledge on physics included
DB for test
Visiting consulting
Interdisciplinary consultant
Large-sum consulting cost
Online platform & consulting