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Supporting sustainability transformation through research requires, in equal parts, knowledge about complex problems and knowledge that supports individual and collective action to change the system. Recasting the conditions, characteristics, and modes of research processes that address these needs leads to solution-oriented research in sustainability science. This is supported by systematically analyzing the system’s dynamics, envisioning the desired future target state, and by engaging and designing strategic pathways. In addition, learning and capacity building are important crosscutting processes for co-producing required knowledge. In research, we use sophisticated representations as mediators between theories and objects of interest, depicted as visualizations, models, and simulations. They simplify, idealize, and store large and dense amounts of information. Representations are already employed in the service of sustainability, e.g., in communication about climate change. Understanding them as tools to facilitate processes, dialogue, mutual learning, shared understanding, and communication can yield contributions to knowledge processes of analyzing, envisioning, and engaging, and has implications on the design of the sustainability solution. Therefore I ask, what role do representations and representational practices play in the generation of sustainability solutions in different knowledge processes? Four empirical case studies applying rough set analysis, multivariate statistics, systematic literature review, and expert interviews target this research question. The overall aim of this dissertation is to contribute to a stronger foundation and the role of representation in sustainability science. This includes: (i) to explore and conceptualize representations for the three knowledge processes along selected characteristics and mechanisms; (ii) to understand representational practices as tools and embedded into larger methodological frameworks; (iii) to understand the connection between representation and (mutual) learning in sustainability science. Results point toward crosscutting mechanisms of representations for knowledge processes and the need to build representational literacy to responsible design and participate in representational practices for sustainability.