When using Artificial Intelligence techniques for Knowledge management in decision support systems, the enhancement of knowledge should be based both on artificial machine learning methods and a natural human learning approach. Indeed, knowledge representation with ontologies and Case-Based Reasoning (CBR) is not enough for gaining qualitative results in decision support systems. We need to manage know-how, i.e. living knowledge. For example, enhancing biodiversity and music means teaching and learning the effectiveness of individual and living interpretations (how to observe a natural specimen, how to play a music sheet). The quality of descriptions is thus very important to correctly classify or identify marine or terrestrial organisms, or learn adequately an instrument such as the guitar or the piano. This paper introduces Sign management to tackle this qualitative learning problem in AI. Then, a Co-design methodology and a cooking method on a Creativity Platform are proposed: when dealing with such complex domains, we need to focus on the signification of knowledge construction that operates in co-designing an e-service that should be useful for reaching a more robust knowledge base. Our finding is that due to different interpretations of domain objects from subjects (persons), we need sign bases to move from written expert knowledge transmission to multimedia know-how sharing in the community for getting better results.