In recent years, with the rapid growth of science and innovation, plenty of constantly-updated scientific achievements containing innovative knowledge can be acquired and used to solve problems. However, most undergraduate students and non-researchers cannot use them efficiently. In traditional teacher-centric education, education for sustainability is often marginalized and the interdisciplinary demand is neglected. Additionally, it fails to provide education for learners to connect abstract knowledge with actual world problems. This paper presents the design of a scientific publication management model to integrate scientific metadata based on the knowledge graph and data analysis technologies. Based on this model, an interdisciplinary transregional multiple application platform could be realized for scientific resource retrieval and analysis, the purpose of which is to enhance scientific retrieval efficiency and reduce learning difficulty in the scientific domains and encourage non-researchers to utilize scientific resources in their study and work. Finally, to evaluate this model, the use of the case of an entrepreneurship scientific publication management prototype system was implemented. This work not only favors student’s learning for sustainability through analysis and knowledge management functions, but also promotes their awareness, comprehensive thinking, and the skills to deal with the issues of sustainability in their future work.

In the past 40 years, with the changes to dietary structure and the dramatic increase in the consumption of meat products in developing countries, especially in China, encouraging populations to maintain their previous healthy eating patterns will have health, environmental, and economic co-benefits. Healthy diet education plays an important role in the promotion of people’s healthy behavior. However, in the modern age, the data regarding healthy diets available on the internet is increasing rapidly and is distributed on multiple sources. It is time-consuming for users to learn about healthy diets on the internet: they need to search data on multiple platforms, choose and integrate information, and then understand what they have learned. To help people retrieve and learn healthy diet knowledge more efficiently and comprehensively, this paper designs a knowledge graph to integrate healthy diet information on the internet and provides a semantic retrieval system. In the knowledge graph, five main concepts are defined, including food material, dish, nutritional element, symptom, and crowd, as well as the relationships among them. In addition, Chinese dietary culture elements and traditional Chinese medicine (TCM) theory are also contained in the knowledge graph. The preliminary results show that by using the system, users learn healthy diet knowledge more quickly and comprehensively and they are more inclined to have balanced diets. This work could be regarded as a retrieval and education tool, which can assist healthcare and national sustainable development.