Since 2012, the interdisciplinary field combining big data technology and artificial intelligence, which has evolved from disciplines such as statistics and computer science, has experienced unprecedented development. Most disciplines that have applied big data technology fall into the domain of natural sciences, with relatively fewer applications in social sciences. Throughout human history, the development of statistics has never occurred in isolation; instead, it has contributed to the standardization of research methods in other interdisciplinary fields, social sciences in particular.

In this era of data explosion, the advancement of data-driven social sciences is accompanied by various challenges but also presents new opportunities. Harvard University was the first to introduce the concept of "computational social science." In 2018, Tsinghua University also established a "Computational Social Science Platform" by integrating multiple disciplines. Against this backdrop, the establishment of the "Institute of Computational Social Science" at Weihai Campus aligns with the strategic vision of the Ministry of Education and Shandong University to prioritize the development of interdisciplinary studies and academic integration. This initiative can provide intellectual support for the transformation of old and new growth drivers in both China and Shandong Province.

TheNational Occupational Disease Prevention and Control Plan(2016-2020)identified a severe occupational health situation in China, noting that workers have entered a period of high incidence and prominent conflicts regarding occupational diseases, which have become a significant burden on the healthcare system. TheHealthy China Initiative (2019–2030)sets clear targets: by 2022, occupational diseases (including occupational mental illnesses) should be effectively controlled, with a gradual reduction in disability and mortality risks, and significant improvements in the health of key populations; by 2030, major health indicators for occupational diseases should reach the levels of high-income countries, with basic achievement of health equity. In this context, the center has selected "Occupational Health and Community Wellness" as its research focus.

Current research on occupational behavior and community wellness primarily falls within the fields of management, public health, and socio-economics, relying heavily on epidemiological surveys as the main methodology. The Institute will adopt a novel approach by leveraging intelligent IoT technologies to develop advanced, non-intrusive objective measurement methods, which will partially replace traditional questionnaires to obtain long-term, continuous, and precise data. The Institute will then conduct original, groundbreaking, and interdisciplinary research focusing on fundamental scientific challenges such as how to accurately measure occupational behavior and health, and how to better protect workers' health in the era of intelligent manufacturing. By attracting and gathering high-level research teams and outstanding talents, the Institute aims to foster cross-disciplinary integration and develop into an internationally influential innovation hub at the forefront of academia. This endeavor will contribute significantly to data-driven "new business studies" and the future development of interdisciplinary research in China.

The Institute's research methodology is highly interdisciplinary. Its establishment will foster an integrated academic landscape with management and statistics at the core, supported by electronics and computer science, thereby opening up entirely new research fields for relevant disciplines at Shandong University.