Steps Towards an Infrastructure for Scholarly Synthesis
<|reference_start|>Steps Towards an Infrastructure for Scholarly Synthesis: Sharing, reusing, and synthesizing knowledge is central to the research process, both individually, and with others. These core functions are not supported by our formal scholarly publishing infrastructure: instead of the smooth functioning of functional infrastructure, researchers resort to laborious "hacks" and workarounds to "mine" publications for what they need, and struggle to efficiently share the resulting information with others. Information scientists have proposed an alternative infrastructure based on the more appropriately granular model of a discourse graph of claims, and evidence, along with key rhetorical relationships between them. However, despite significant technical progress on standards and platforms, the predominant infrastructure remains steadfastly document-based. Drawing from infrastructure studies, we locate the current infrastructural bottlenecks in the lack of local systems that integrate discourse-centric models to augment synthesis work, from which an infrastructure for synthesis can be grown. Through 3 years of research through design and field deployment in a distributed community of hypertext notebook users, we elaborate a design vision of what can and should be built in order to grow a discourse-centric synthesis infrastructure: a thriving "installed base" of researchers authoring local, shareable discourse graphs to improve synthesis work, enhance primary research and research training, and augment collaborative research. We discuss how this design vision -- and our empirical work -- contributes steps towards a new infrastructure for synthesis, and increases HCI's capacity to advance collective intelligence and solve infrastructure-level problems.<|reference_end|>
@article{chan2024steps,
    title={Steps Towards an Infrastructure for Scholarly Synthesis},
    author={Joel Chan, Matthew Akamatsu, David Vargas, Lukas Kawerau, Michael
  Gartner},
    journal={arXiv preprint arXiv:2407.20666},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.20666},
    primaryClass={cs.HC}
}