It is crucial to share interdisciplinary toolboxes based on practical experience, so as to facilitate more efficient, profound, and effective interdisciplinary collaboration. Photo: TUCHONG
Interdisciplinary collaboration, also known as cross-disciplinary collaboration, is an important approach to facilitate scientific and technological innovation as well as academic breakthroughs. Through interdisciplinary collaboration, humanity discovered DNA, developed the theory of general relativity, and invented the computer, radar, spacecraft, and atomic bomb. In fact, 41% of Nobel laureates earned their prize for work involving interdisciplinary collaboration. It is fair to say that interdisciplinary collaboration is one of China’s major strategies for developing science and technology.
Examples of interdisciplinary collaboration
Interdisciplinary collaboration can emerge from the bottom up, driving academic innovation in basic research, or it can be organized from the top down to benefit engineering projects and serve major national strategic needs. Regardless of how it is initiated, its core characteristic is the integration of knowledge: scholars from different disciplines learn from each other’s fields, understand each other’s research needs, and form a multidisciplinary understanding of the research object.
An example of interdisciplinary collaboration is the 3/4-power law [also known as Kleiber’s law], which states that metabolic rate scales at the 3/4th power of its body mass. Ecologists believe that a living organism’s metabolic rate is related to its mass, and that its internal metabolism depends on its branching networks, such as the vascular system. Physicists hypothesized that this network extends fractally. Based on the consensus reached on the internal network of living organisms, they developed a complex network model that successfully explained the observed scaling of metabolic rates with body mass.
A more comprehensive example is the Netherlands’ national canal project. Experts from various fields, including architecture, soil hydrology, engineering, historiography, pedagogy, art and aesthetics, heritage conservation, and ecology came together to redefine and reach a consensus on the concept of “l(fā)andscape quality.” This shared understanding served as the foundation for designing a comprehensive plan for the development and conservation of the landscapes surrounding the canal.
It is important to note that such consensuses can occur across different aspects, including technologies, methods, tools, perspectives, or theories, or a combination of these. Interdisciplinary collaboration is effective only when such a consensus is reached. However, the process of reaching a consensus is often time-consuming and laborious, which inevitably increases the risk for scholars involved in interdisciplinary collaboration.
Mechanisms of pseudo-interdisciplinary collaborations
Pseudo-interdisciplinary collaboration stands in stark contrast to effective cooperation. It occurs when researchers from different disciplines are simply brought together without a shared knowledge base, leading to a scenario where each participant works independently rather than collaboratively. Such “collaborations” often appear superficially impressive but ultimately squander research funds that were intended to support genuine interdisciplinary work, thereby encroaching on the space needed for teams that have successfully integrated their knowledge. Even in collaborations without funding, pseudo-interdisciplinary work tends to negatively impact scientific research. Han Qide, an academician of the Chinese Academy of Sciences, has criticized this phenomenon, pointing out that interdisciplinary collaboration is not just about making a mixed platter.
It is worth mentioning that interdisciplinary collaboration does not deprive scholars of their rights to consider their own disciplinary interests. In fact, these interests often serve as the starting point of collaboration and the driving force for scholars to develop phased achievements into theoretical or applied innovations within their respective disciplines. However, scholars should not cling so tightly to these disciplinary interests that they overlook the importance of knowledge integration.
At present, the academic community has identified three major mechanisms that contribute to the formation of pseudo-interdisciplinary collaborations.
The first mechanism is irresponsible project management. Many scientific research projects involve collaboration between advisors and their students, particularly doctoral students. In pseudo-interdisciplinary collaborations, advisors from various disciplines jointly construct a research narrative, using it to secure interdisciplinary funding. However, once funding is obtained, these advisors often become preoccupied with managing other projects, leaving their students with tasks that require long-term, continuous communication based on specific disciplinary knowledge and perspectives as well as the direction of interdisciplinary collaboration. However, most students are not capable of completing such communication tasks, resulting in the failure of achieving knowledge integration. In reality, the entire process of interdisciplinary collaboration requires a high degree of intellectual attention. The collaborators must continuously update the knowledge consensus based on the existing consensus and new research findings. Knowledge integration is never achieved overnight.
The second mechanism is epistemic oversight. The collaborating parties may fail to recognize that different disciplines may assign different meanings to the same concept or term. Although this problem might be identified during the research process by comparing interim research results with initial expectations, it significantly reduces the efficiency of interdisciplinary work and can easily undermine mutual trust. Even when researchers from different disciplines collaborate with utmost sincerity, they are often susceptible to the hidden assumptions in their own disciplines. These assumptions can either be a theoretical logical premise, such as the assumption of Homo economicus in economics, or an epistemological premise, such as the assumption that everything can be quantified in computer science.
The third mechanism is disciplinary compromise. Sometimes, at the early stage, collaborating scholars might find it difficult to reach a consensus on a topic, research concept, or even methodological approach due to their respective academic interests. For example, a mathematician involved in an interdisciplinary project might feel that they are “working for” other disciplines, such as biology or physics, and will thus ask their partners to also provide the data needed to develop new mathematical algorithms. However, such data may not be directly relevant to what the biologists or physicists wish to gain from the project. When an agreement cannot be reached, collaborators may temporarily set aside the dispute and focus on “getting the project done first.” Consequently, the collaboration often devolves into a situation where each participant works independently.
Avoiding pseudo-interdisciplinary collaborations
The academic community has yet to develop a reliable method for automatically identifying pseudo-interdisciplinary collaborations. In practice, funding agencies around the world remain reliant on the expertise of academic committees to make these judgments. Bethany Laursen and her colleagues [from Michigan State University] pointed out that the development of a reflective interdisciplinary toolbox can help scholars avoid pseudo-interdisciplinary collaborations. This toolbox refers to a set of specially designed and organized tools, methods, and resources aimed at promoting interdisciplinary and cross-domain collaboration. These tools and resources usually include conceptual frameworks, techniques, reflexive questions, models, and practical guidelines, which act as “translation tools” for interdisciplinary and cross-field projects. They help team members from different disciplinary backgrounds overcome communication barriers caused by disciplinary differences, so that collaborators can better understand each other’s viewpoints and methods.
Interdisciplinary toolboxes originate from specific interdisciplinary projects. Collaborators compile their experiences, including specific cases, problems encountered, detours taken, corresponding solutions, and final reflections. As such, these toolboxes are by no means instruction manuals for interdisciplinary work; rather, their application must be tailored to the specific contexts in which they are used. They also offer a valuable resource for analyzing and testing interdisciplinary approaches.
These toolboxes cannot only help scholars establish, promote, or organize interdisciplinary collaborations, but also aid funders and project evaluators in assessing the effectiveness of interdisciplinary projects. Laursen et al. introduced four such toolbox systems as follows.
The first is the “td-net” toolbox, developed by the Network for Transdisciplinary Research in Switzerland. It is widely used in interdisciplinary collaborations across Europe within fields like environmental studies, public health, and sustainable development. It provides tools to help researchers define research problems, set goals, and design research methodology. For example, the problem definition tool can help teams clarify their respective disciplinary perspectives and expectations at the beginning of a project. It also emphasizes stakeholder involvement, offering tools such as consensus workshops and stakeholder analysis to help research teams better interact with external stakeholders and ensure the social applicability of research results. Moreover, it provides methods and tools for integrating knowledge across disciplines, such as the knowledge integration matrix, which helps teams systematically combine information from different fields, to assess the effectiveness and impact of interdisciplinary work.
The second is the Integration and Implementation Insights (“i2Insights”), a blog and repository of resources maintained by a global community of interdisciplinary researchers. Founded in 2015 by Gabriele Bammer, a professor at the Australian National University, it is an open knowledge sharing platform where researchers can publish and access articles, tools, methodologies, and case studies related to interdisciplinary research. It is not only a repository of resources, but also a platform for global researchers to interact, promoting experience exchange and knowledge transfer in interdisciplinary fields.
The third is the Integrated Research Toolkit, which is mainly aimed at interdisciplinary research in the field of environmental science. This toolkit aims to help research teams integrate data and knowledge across different disciplines, especially in the face of complex environmental issues like climate change, biodiversity conservation, and ecosystem management. A key feature of this toolbox is its provision of data integration tools, such as the geographic information system (GIS) tools, which help teams to integrate data from ecology, meteorology, and social sciences.
The fourth toolbox is Shaping Interdisciplinary Practices in Europe (“SHAPE-ID”). Funded by the EU, this project focuses on advancing interdisciplinary collaboration between the humanities and social sciences with the natural sciences, technology, and medicine. It is particularly applicable to research projects involving collaboration between the humanities and social sciences and other fields, especially in the fields of cultural studies, social policy, and educational innovation.
It is advisable for Chinese scholars to build and share their own interdisciplinary toolboxes based on their own practical experience, so as to help more scholars facilitate more efficient, profound, and effective interdisciplinary collaborations.
Dai Lianghao is deputy dean of the Department of Sociology at Zhejiang University.
Edited by REN GUANHONG