Knowledge infrastructures are defined as robust networks of people, artifacts, and institutions that generate, share and maintain specific knowledge. Yet, many domains are fragmented and far from robustly networked, such as science communication or aerospace engineering. While FAIR (Findable, Accessible, Interoperable, Reusable) data management tools exist, their adoption in these domains is limited. Several challenges inhibit this adoption, from complex heterogeneous data formats to lack of structured support to outright incentives against collaboration or legal barriers. This doctoral work outlines how to foster underdeveloped knowledge infrastructures with the use-cases of science communication and aerospace engineering. By analyzing these problems and identifying available solutions, tool-supported workflows towards collaborative infrastructure can be implemented and evaluated. These include human-in-the-loop artificial intelligence (AI)-supported workflows for information extraction and processing, wiki- and knowledge-graph-based digital libraries, and stakeholder-requirement-driven interfaces. While these developed tools for workflow automation and knowledge representation show promise, significant challenges remain. Future work will have to go beyond technical problem-solving and address the societal and legal barriers to unlock the particular domains. Beyond that, advocates of emerging knowledge infrastructures in any domain are welcome to apply the findings of this work to foster the networking of available knowledge.

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