Keywords

1 Introduction

Transdisciplinary research has become a keyword in the scientific debate on sustainability and social transformation. Developing strategic options for policy and articulating or preparing recommendations for the relevant policymakers from a scientific perspective is not sufficient in the light of a transdisciplinary understanding of research practice [1, 2]. On the one hand, no scientific consensus exists on many factual issues. This implies that researchers and practitioners need to develop a common understanding of the underlying problems and to co-create options for action in a joint problem exploration and resolution activity. The goal is to develop, in the context of a joint deliberative discourse, a solution space from which concrete actions can be prepared. On the other hand, there are factual topics on which—as in the climate change issue—scientific consensus has existed for decades, but on which the nexus between knowledge, beliefs, and action is not functioning because of the complexity of the factual information and its range of interpretations [3, 4]. Given this situation, transdisciplinary approaches require establishing useful links between plural truth claims, diverse societal goals and objectives, and the choice of concrete policies. More specifically, Renn [5] attributes three major properties to the concept of transdisciplinarity:

  • Firstly, it addresses research practices that, in addition to the scope of the disciplines involved, adapt research topics, methods, and approaches to non-scientific problems and issues, and develop solutions to socially complex problems independently of disciplines [6, 7];

  • Secondly, transdisciplinary research relies on an intensive exchange between knowledge producers and knowledge recipients across all phases of the cognitive and research process [8]. Those who want to use scientific knowledge for political decisions and to apply it concretely need to know not only the results of the research but also the context conditions and the areas of validity. Without this expanded concept of knowledge, a proper interpretation of the results is not possible. Moreover, the users and producers of knowledge are engaged in a mutual dialogue in which both sides add knowledge as well as experience to the learning process of developing a common understanding of the problems and a solution space for policy options; and

  • Thirdly, the transdisciplinary approach is characterized by the deliberate integration of knowledge carriers outside of science [9]. For addressing complex questions, experiential knowledge and often also contextual knowledge of the actors dealing with this question in society are relevant in order to develop not only theoretically conclusive but also practical solutions.

It is contested in the literature how such transdisciplinary communication processes between knowledge bearers and knowledge recipients can and should be organized in concrete terms [8, 10]. Essential characteristics of such a process are (i) the early involvement of all relevant knowledge carriers; (ii) a learning discourse with the users of knowledge in parallel with each research phase (from agenda-setting to interpretation); and (iii) the use of innovative, communicative procedures that enable an intensive exchange of arguments, observations, and experiences [11].

The transdisciplinary approach goes, however, beyond the participation of stakeholders in individual phases of the research process. Transdisciplinary research is aimed at a jointly supported, integration-oriented merging of different forms of knowledge that are needed for the analysis of a situation and/or for problem-solving [12]. In the literature on transdisciplinary research, there is (so far) hardly any agreement or consent on the different approaches, methods, and procedures for how transdisciplinary research can be implemented in practice. It is not enough to gather stakeholders around a round table and hope that added value would result from the mere fact of having a joint discussion. What is needed is a structured and, above all, a reflected process that is based on the profound knowledge of the conditions that govern transdisciplinary discourses. Such process knowledge needs to be theoretically sound, empirically tested, and methodologically reproducible.

This chapter is an attempt to develop a conceptual framework that combines the rigor of (transdisciplinary) science with the transformative effect of transdisciplinarity. The need for robust and valid scientific insights is crucial for dealing with complex issues since intuition and common sense are likely to fail in these circumstances. At the same time, producing valid descriptions of complex structures is insufficient for developing and implementing evidence-informed policy options. How to combine these two aspects of transdisciplinarity will be the main focus of this chapter. First, I will give a brief review of the various schools and concepts that have emerged over the last two decades. I will show that neither one of these concepts, as valuable as they may be, provides a clear concept of how to accomplish scientific excellence and practical relevance. Based on this analysis, I will propose a new modular approach for integrating transdisciplinary scientific knowledge into societal transformation discourses and democratic policymaking.

2 Traditions and Concepts of Transdisciplinarity

The concept of transdisciplinarity emerged in the 1970s to the 1990s as a new approach to tackling complex and controversial issues. Transdisciplinary approaches gained ground in connection with efforts to address wicked problems [13], the debate on post-normal science [14], and the division of scientific approaches into Mode 1 and Mode 2 research [15, 16]. These approaches differed from the more established concepts of multi- and interdisciplinary research in the way that they integrated practitioners, and not just other scientific disciplines, into the research process. This transdisciplinary involvement of practitioners was seen as a prerequisite for dealing with problems characterized by complex causal structures and interconnections, uncertainties around the relationship(s) between causes and effects, and challenging ambiguities [2]. In particular, transdisciplinary approaches were expected to prove their worth in addressing the tensions between the contextuality and universality of scientific knowledge [17].

Over time, some different perspectives and concepts relating to the theoretical foundations and practical implementation of transdisciplinary approaches emerged worldwide. At the beginning of the debate, two major concepts evolved: the transgressive school inspired by Nicolescu [18, 19] and the so-called Swiss (polycentric) school, mainly represented by European authors who laid down the foundations of their understanding in a seminal conference in Zurich, Switzerland [17, 20] as reviewed in [21, 22]. This crude dualism has given rise to a multitude of competing and complementing concepts that all relate to the theoretical roots of addressing wicked problems utilizing knowledge integration. It is not possible to cover all of these approaches in detail here. In what follows, I present a brief outline of five concepts that are particularly relevant for the present status of interdisciplinary research (with an emphasis on European traditions):

  • The Anglo-Saxon concept of a new inner-scientific orientation towards the treatment of complex and socially controversial questions, especially about sustainability science, which emerged in response to the conditions that initially prompted the development of transdisciplinary approaches as noted most prominently in [23, 24];

  • The approach proposed by Jürgen Mittelstraß, Martin Scheringer, Jochen Jaeger, and others, which focusses on real-world problems and the associated changes in the scientific system and research practice [25, 26];

  • The concept put forward by the German socio-ecological tradition, which focusses on integrating rigid scientific methods and practice in collaboration with affected people and groups [27];

  • The concept of epistemic integration envisioning transdisciplinarity as a mutual learning process in which scientists and practitioners integrate systematic knowledge and experience as equally valid forms of knowledge [28]; and

  • The concept of common good orientation views transdisciplinarity as a form of discourse between scientists and practitioners oriented towards negotiating societal improvements of public welfare [29, 30].

All these proposals for transdisciplinary research provide orientations for informing transdisciplinary research. However, there are three major shortcomings:

  • The relationship between transdisciplinary, interdisciplinary, and disciplinary concepts remain vague and often confusing [31]. What is the role of classic science approaches in transdisciplinary research? How are conflicts been handled when scientific truth claims contrast with the experiential knowledge of stakeholders? The main body of transdisciplinary literature recommends reliance on robust knowledge, excellent science, and evidence-informed judgments [32]. However, it is not clear how this is accomplished and how conflicts are adequately addressed;

  • The tension between curiosity-driven research and advocacy for a special cause (as noble as it may be) is often mentioned in the literature [33, 34]. Suggesting joint fact-finding methods and engaging in a deliberative discourse may produce procedural forms of resolving this tension. However, it is not clear how these tensions can be addressed substantively. In a very critical review, Strohschneider [35], the former president of the German Science Foundation, criticized transdisciplinary research as being torn between the need for rigorous scientific methods combined with an impartial search for a causal explanation and the normative orientation of promoting sustainability or other political objectives.Footnote 1 Such a tension, so his analysis could lead to wishful thinking, partialized truth claims, and in the end to a delegitimization of science as an impartial broker [38];

  • The tensions between epistemic and democratic ideals in research have also been addressed by critical reviews [2, 39]. Maasen et al. [40] have emphasized the unresolvable tension that arises between normative and epistemological demands when scientific research is expected to be both reliable and justifiable. In the course of transdisciplinary research, they believe that normative constraints move from the periphery to the epistemic core of science, encouraging a shift in the role of scientists from analysis to intervention. The criticism of Maasen and her colleagues centres on the question of how to deal in a responsible way with the fact that participation in science is generally discussed in the context of the normative goal of democratising science with the ultimate aim of expanding the democratisation process itself but not to enhance our knowledge about the causal and functional relationships in the natural and social world. Maasen and Dickel [41] also point out potential conflicts of including non-epistemological values into scientific research such as sustainability, ethical acceptability, and productivity.

In my view, these three questions have not been adequately addressed in the literature on transdisciplinarity. In particular, the integration of (i) classic, curiosity-driven science (disciplinary and interdisciplinary); (ii) goal-oriented, often advocacy science; and (iii) non-scientific actors in a deliberative forum of co-production of knowledge is still an unresolved topic in the conceptual literature and also in the practical guidelines for transdisciplinary research. The following paragraphs attempt to address these problems and develop a hybrid approach of transdisciplinarity as a combination of curiosity-driven, goal-oriented, and catalytic research traditions.Footnote 2

3 Transdisciplinarity: Merger of Three Research Traditions

The following section is a translation of an earlier version of this paper that has been published in German in the Journal GAIA [5]. Similar thoughts can also be found in [42]. The version here is updated and also includes more international references.

3.1 The Curiosity-Driven Research Concept

To locate the appropriate function of science and research for transdisciplinary research in the context of current transformations, it seems important to differentiate between three basic concepts of scientific research traditions and the types of knowledge associated with each of them.

The first concept comprises the classical understanding of curiosity-driven research (classic science) [43]. Agar has characterized the evolution of curiosity-driven research by referring to development from ‘basic science’ to ‘mission-oriented science’ and to ‘curiosity-driven research.’ This evolution “has provided important tools used to create and manage the apparent social autonomy that is functional in sustaining science. The social contract has been that science will deliver, if left autonomous” [44].

Scientific activities in this scientific tradition aim to find valid insights into as yet unknown connections between phenomena or dynamic developments. The driving force behind these activities is curiosity; the aim is to uncover causal or functional relationships without any specific goal of application or implementation in mind using proven methods of gaining knowledge and to integrate these new discoveries into a consistent body of existing insights. All parties in society thus receive the necessary background knowledge to inform themselves on factual issues and get to know the status of systematic knowledge. This enlightenment function of science without consideration of interests, social preferences, and political contexts is not a sign of ivory-tower thinking, as so often caricatured, but a necessary and indispensable corrective against wishful thinking and ideological blinkers [45, 46]. Science is never unconditional, but it is based on normative assumptions and conventions and can produce findings in the space beyond interests. These findings help to prevent unpleasant surprises for all those involved.

The results of curiosity-driven research, therefore, provide insights into causal or functional processes. Such knowledge is relevant for politics and business (mainly if Mode 1 issues are addressed). If a research team found out, for example, which incentives could lead to greater energy efficiency or energy savings among consumers, policymakers could consciously introduce these incentives as policy options in order to better achieve the goal of energy system transformation.

A better understanding of complex and wicked problems (Mode 2) requires, however, more than just disciplinary knowledge. Rather, an integrative approach is needed that simultaneously illuminates the various aspects of the phenomenon to be investigated and, above all, captures their interactions. The term systems knowledge has become established in the specialist literature for this purpose [9, 11]. This refers to knowledge that describes and analyses the various facets of a phenomenon in their systemic interaction and understands them in their holistic interrelationships [3]. Systems knowledge is, therefore, almost always interdisciplinary, i.e., it is aimed at uncovering relationship patterns that encompass and integrate the scope of several disciplines. Yet, the research design may still be curiosity-driven and governed by the traditional quality standards of each scientific discipline involved [47].

No doubt that there are a number of problems associated with the classic understanding of science. One major problem is that in the case of complex and stochastic interrelationships, a clear causal or even functional understanding of the relationships is hard, if not impossible, to accomplish [48]. Moreover, even if knowledge of functional interrelationships is available, a direct translation into political action is often impeded by unfavorable context conditions [49]. Investigators may be able to identify particularly effective incentives for energy-saving behavior through laboratory experiments. When applied to everyday political life, these incentives may not work at all, either because the framework conditions do not match the experimental context or because other political or social circumstances weaken the effect of all the chosen incentives. After all, in a concrete political situation, there are always many actors operating at the same time, whose interactions are difficult to grasp by scientific methods [12, 50].

3.2 The Goad-Oriented Research Concept

To design research agendas to specific situations and contexts, there is a second concept of scientific research, which can best be described by the term “goal-oriented research” (mission-oriented, or more provocative advocacy science). Goal-oriented research dissolves the distinction between basic and applied research, which has become obsolete [51]. Rather, it is the acquisition of knowledge-oriented towards a specific benefit or problem-solution that can be approached systematically with both basic and applied research.Footnote 3 Goal-oriented research produces knowledge that policymakers can use as strategies for achieving goals or solving problems. In this concept, policymakers or other shapers of social reality (such as business or civil society groups) either set goals for science that are to be achieved by a certain point in time (e.g., energy system transformation) or address problems that are to be solved using the best evidence available. In the literature on forms of contemporary policy advice, this function of science is often described as strategic or instrumental [52].

Goal orientation comes in two variants. In the first case, social groups set targets. These can be targets for energy system transformation, such as the 100% replacement of fossil fuels by renewable energy sources by 2050. In the second case, the research addresses conditions that are regarded as “problematic” by certain groups or by policymaking bodies. These problems should be resolved towards a more desirable state, such as more sustainable food production or finding more equitable solutions when distributing income. That what is regarded as desirable is defined in advance, ideally in an orientation discourse. In many cases, consent of what is regarded as desirable may be based on an implicit consensus in society (more climate protection is better than less) or may have been negotiated in a political discourse involving ethical expertise (for example, more investment in resilience after experiencing a pandemic crisis). In other cases, scientific advice is demanded partial, interest-based goals or group-specific problem views. This is normally associated with advocacy research [53]. For example, environmental protection groups or business associations can commission expert reports that consider the problems and develop strategies that serve their specific objectives. Irrespective of the client and their interests or concerns, the common feature of goal-oriented research is to provide options or propose solutions for clients from politics, business, and civil society that, to the best of their knowledge, meet specified goals within the specified time frame or help solve specific problems in an appropriate way and reflect the values of the respective policymakers. It is obvious that this research tradition is value-based and not driven by curiosity.

Similar to the curiosity-driven research tradition, goal-oriented research also faces numerous problems and pitfalls. One major problem is that, as the name suggests, the research team is tied into a predetermined corset of objectives [55]. It is possible, for example, that other objectives could better implement the original intentions associated with the objectives at a higher level. Perhaps there are also other variants which, with fewer side effects, can achieve the originally intended purposes just as effectively (or even more effectively). In climate protection, for example, one might think of negative emissions or drastic lifestyle changes. After all, goals are not set in stone, and they have to be constantly adapted in the social discourse and reflected upon again and again.

Moreover, with the goal-oriented variant, there is always the danger that in the conflict between the achievement of goals and the results of scientific research, loyalty to the goals carries more weight than loyalty to the methodological rules of finding knowledge in the respective sciences [56]. This danger is even more pronounced if the topic itself requires an interdisciplinary approach since it is then more likely to be associated with great uncertainties and ambiguities from a scientific perspective. Also, goal-oriented research is often conducted by scientists who themselves share these goals and may be biased against any evidence that may contradict these goals or may suggest much more effort to reach them in time.

3.3 The Catalytic Research Concepts

The last and third variant of scientific research is less clearly defined and has been labeled as participatory [57], deliberative [58], or reflective [59]. It aims to integrate knowledge outside of the scientific communities and provide models for deliberation in which knowledge claims, interests, values, and preferences can be considered for designing policy options. In my own writing, I have referred to this concept as the catalytic approach to research [5, 42]. To my knowledge, this term has rarely been used in the context of transdisciplinary policy advice, and it may represent a new category of scientific self-understanding. In this understanding, science assumes the role of a catalyst. Its task is to systematically collect the knowledge from scientific communities and also from other sources of knowledge, which may be instrumental for problem-solving, to reorganize it, and to process it to create a mutual understanding among all participants [3, 60]. Above all, conflicts are to be identified, the underlying knowledge assumptions, but also the values, interests, and preferences associated with them are to be disclosed, and joint approaches to solutions are to be developed, which are based on robust knowledge, generally accepted normative principles, and fair negotiation of interests. According to this concept, the systematically collected knowledge elements are transferred into a new format that is understandable and comprehensible for all participants, so that a proper discourse appropriate to the plural values can be conducted [61, 62]. In this discourse, the different knowledge carriers meet with the knowledge users and discuss the initial situation, jointly reflect the different views of the problem (frames), and develop evidence-informed policymaking for society as a whole [63].

The catalytic understanding of science is more than just a new domain for the social sciences and especially the communication sciences aimed at conflict management and discourse design. It puts science in the role of an “honest broker”, a mediator between competing truth claims, options for action, and moral justifications of distribution keys for public goods and burdens (impositions) [38]. In the spirit of Jürgen Habermas’ Rational Discourse, the catalytic research team explores and implements the structural and procedural conditions necessary for a factually sound formation of judgment that adequately reflects the plurality of values [64, 65]. It is a matter of the institutional and organizational conditions that guarantee an effective and fair exchange of arguments (speech acts), in which not the status of the speaker, but the claims to validity associated with each statement are used as a yardstick for a collective agreement. The aim is an understanding-oriented action through which all actors can bring in their claims to validity and jointly redeem them [66]. This requires not only a robust knowledge-based process of scientific methods, procedures, and testing procedures but also communicative competencies and skills, which can be described using catalytic knowledge and can be entrusted to non-scientific actors with a high level of communicative competence [61]. A catalytic research team has the mandate to explore, empirically test, and structure the design, but it does not need to moderate the process itself. In the literature on policy advice, the catalytic task of science is often described by using the term co-creation (co-generation or co-production) of knowledge [67, 68]. However, co-creation describes the goal of such deliberation but not the way to accomplish it. Catalytic science compiles the necessary process of knowledge of how co-creative processes can succeed in the context of the various policy fields in their sequencing and structuring. It does not ignore existing power relations or socio-political contextual conditions, but systematically examines whether a co-creative solution to a problem supported by all can be achieved and implemented and, if so, under which conditions and what type of discourse architecture. It is a matter of structural and process knowledge that guarantees fair treatment of all positions in conflicts and a factually solid and socially balanced formation of judgments in political discourse [62, 69].

Catalytic science has the task of researching and reviewing the architecture for such discourses for handling complex problems and of incorporating this knowledge into political discourse [70]. Especially in a time when political populism and simplistic claims to truth are gaining more and more weight, a counter-movement that builds up institutional, organizational and process-related knowledge for an adequate treatment of complexity, uncertainty, and ambiguity is of particular importance [71].

Like the other two concepts, the concept of catalytic research also has a number of problems and deficits. First of all, it only collects and organizes the expert knowledge without contributing to the substance of the issue in question. Catalytic research is, therefore, dependent on at least one of the other two concepts (curiosity-driven or goal-oriented) to bring relevant expertise into the process. Secondly, the generation of process and structural knowledge to shape discourses that are appropriate to the subject matter and reflective of the underlying values and interests is particularly context-dependent and makes it difficult to provide universally valid insights that go beyond the individual case [72]. Therefore, developing a systematic knowledge base design depends on the compilation of empirical case studies and interpersonal experience.

3.4 Synopsis of the Three Concepts

In short, the three concepts of scientific research (curiosity-driven, goal-oriented, and catalytic) complement each other and have overlapped at the margins but are not functionally equivalent. They are, as explained in the next section, modules of a comprehensive transdisciplinary understanding of science. In Table 1, the essential characteristics of the three concepts are summarized in a compact form.

Table 1 Three concepts of scientific research for policymaking purposes
Full size table

4 Transdisciplinarity as an Integrative Hybrid of the Three Concepts

How can this triad of curiosity-driven (disciplinary and interdisciplinary), goal-oriented, and catalytic research concepts be integrated into a coherent and interconnected pattern of transdisciplinarity, and how can this integration address the problems and shortcomings mentioned in Sect. 3.4?

The three concepts of research complement each other and constitute analytically separate but closely intertwined modules in the process of co-producing knowledge, developing options for policymaking, and generating normative orientations. All three research concepts are constitutive for the transdisciplinary exchange and provide a platform for interactions between science, society, and politics.

First, it is crucial for transdisciplinary discourse to examine truth claims with the authority of the sciences and to differentiate “fake news” from “true news” in a deliberative setting [73]. Also, curiosity-driven research teams are also needed for the transdisciplinary discourse in order to provide the discourse participants with the appropriate factual knowledge according to scientifically recognized standards and to respond to factual questions that participants may raise. Here, the ideology-critical function of science is also called to uncover misjudgments based on wishful thinking and intuitively plausible but often misleading rules of thumb and plausibility assumptions, and to share these critical insights with all parties involved in the discourse as well [60, 74].

Secondly, the transdisciplinary discourse thrives on the targeted knowledge of experts who point out realistic ways to achieve the goals sought by politics, business, and non-governmental organizations (NGOs) and develop policy options that promise to be effective in light of the goals that the participants want to accomplish. They develop strategies together with the discourse participants. At the same time, it is there mandate to point to the possible positive and negative side effects that each strategy is likely to produce. The associated goal-oriented research is closely aligned with the problems to be solved and, especially in complex and uncertain decision-making contexts, helps to design scientifically robust options for action and to assess their consequences [75].

Thirdly, transdisciplinary processes are based on a deliberative discourse involving all relevant groups. This discursive treatment for designing policy options is necessary because of the uncertainty, ambiguity, and frame-dependence of scientific problem descriptions. Non-scientific actors have valuable experience or local knowledge to contribute, and they are often the best judges of what knowledge is relevant for addressing the problem at hand [76]. Also, the ever-increasing diversity of evaluations, beliefs, interpretations, and value judgments requires a discourse that promotes integration and resolves conflicts [57]. Organizing such discursive processes of acquiring and sharing relevant knowledge and embedding it in an argumentative discourse based on weighing each argument and reflecting on common values and interests lies at the heart of a transdisciplinary process. How to ensure the high quality of such a process and how to integrate the scientific communities (curiosity-driven and goal-oriented) as well as stakeholders and representatives of the public in such a discursive setting is literally science in itself, which I have called the catalytic research concept. Catalytic expertise provides evidence-informed and experience-based instructions for designing a discourse architecture that increases the probability of accomplishing the main goal of transdisciplinarity: to find scientifically valid, socially negotiated, environmentally sustainable, and morally superior options for dealing with wicked problems.

In my view, the integration of the three concepts (curiosity-driven, goal-oriented, and catalytic) into processes of deliberative policymaking is the essential contribution of the sciences to promote transformations towards more sustainable futures. Such processes require more than scientific knowledge. It is precisely a characteristic of transdisciplinary approaches to integrate knowledge from different sources and areas of experience [77]. But how this integration is to be shaped epistemically, organizationally, and procedurally is a new task for science, in this case, its catalytic mandate. Moreover, in deliberative discourses, robust causal or functional elements of knowledge, as well as strategic options for achieving predetermined goals or solving problems, are urgently needed, in particular, if problems are complex, laden with uncertainty and ambiguity, and potential solutions are highly contested in society. To ignore scientific insights in those circumstances is normally an invitation to disaster. Replacing robust knowledge by power or interests or being guided by wishful thinking has rarely helped to address a matter of problem effectively and fairly. At the same time, however, social experience, local familiarity, interest- or value-based judgments, social preferences, and cherished routines are important elements of any policy, and those elements are best contributed by non-scientific actors [68]. Transdisciplinary science is, thus, not a monolithic block. Nor does it require a fundamental reorientation of the sciences. Rather, in my understanding, transdisciplinary science is a synthesis of different modules, each with a clear orientation, function, and methodology. These modules can be integrated into transformative discourses, and thus represent an important and irreplaceable contribution to complex policymaking.

5 Conclusion

Policymaking for dealing with wicked and complex problems requires a robust knowledge base for assessing the likely consequences of each policy option and is based on balancing conflicting goals taking into account the diversity of interests, preferences, and values of society. This requires better integration of scientific expertise for informing policymaking so that the relevant knowledge base can be used in the preparation of evidence-informed, socially acceptable, and morally substantiated decisions. The best way to inform policymaking is by implementing transdisciplinary research methods. Transdisciplinarity becomes manifest in the systematic integration of classical curiosity-driven research (disciplinary and interdisciplinary), goal-oriented strategic research (impact assessment of different options), and process-related catalytic research (deliberative integration of knowledge, values, interests, and preferences). The defining characteristics of transdisciplinarity, namely, the systematic perspective, the orientation on concrete problems, and the inclusion of non-scientific knowledge, are inherent to this kind of research process. To meet these characteristics requires an organic synthesis of the three research concepts described in this chapter. The curiosity-driven concept brings in systematic insights to make policy options effective. The goal-oriented concept develops strategies to achieve the desired objectives or to address problems that need public attention constructively. The catalytic concept prepares the institutional architecture and communicative design necessary to successfully conduct a deliberative discourse between and among the various knowledge carriers and users of knowledge.

The synthesis of these three concepts into an integrative approach of building bridges between knowledge and collective action corresponds to the transdisciplinary mission of science. Transdisciplinary approaches integrate process-related, factual, and strategy-related knowledge and ideally lead to a problem resolution that is factually convincing, argumentatively consistent, morally substantiated, and, in principle, acceptable to all.

Core Messages

  • Wicked problems and complex issues require a new cooperative model between science, policymakers, and societal actors to provide robust knowledge for effective transformations of society (i.e., sustainability).

  • The concept of transdisciplinary science is aimed at a jointly supported, integration-oriented merging of different forms of knowledge that are needed for the analysis of wicked problems and/or for creating solution spaces for addressing these problems.

  • The concept introduced in this paper consists of the integration of three research components: (i) curiosity-driven research, directed towards improved understanding of complex phenomena; (ii) goal-oriented research, directed towards designing strategies and assessing their societal impacts for achieving pre-defined political objectives (such as energy transition); and (iii) catalytic research, directed towards designing and evaluating processes, formats, and techniques that facilitate desired transformations using deliberative discourse.

  • The integration of the three components mentioned above into a process of interaction between experts, policymakers, social actors, and affected citizens can produce robust knowledge, democratically legitimized orientation, and process know-how for implementation.