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HAICu's Innovation Labs: Bridging Technology and Heritage through Collaborative Problem-Solving

Bridging Technology and Heritage through Collaborative Problem-Solving
Authors: de Gruijter, Michel; Klein, Rana; Romijn, Harry; Schulp, Anne; Broersma, Marcel; Larson, Martha; Ordelman, Roeland; +6 Authors

HAICu's Innovation Labs: Bridging Technology and Heritage through Collaborative Problem-Solving

Abstract

This poster introduces the Innovation Labs framework within the HAICu project, which connects AI and digital humanities researchers with cultural heritage institutions and societal stakeholders. The Labs begin from heritage-sector challenges rather than technological possibilities, embedding researchers in heritage environments to support interdisciplinary collaboration and sustainable research uptake. They provide structured co-creation spaces, integrate advanced AI with contextual knowledge of collections and user constraints, and enable iterative development using rich multimodal data and diverse user communities. Four thematic labs anchor the framework: ‘Deep Journalism Lab’, ‘Histories of Ordinary People Lab’, ‘Citizen Science for Natural History Lab’, and ‘Limitations of AI Lab’. Through collaborative activities and prototype testing, the Labs promote reliable, explainable, user-centred AI tools for heritage and society.

Country
Netherlands
Keywords

Artificial intelligence, interdisciplinarity, Innovation Labs, knowledge exchange, problem-solving, citizen science, living labs, cultural heritage, cultural heritage institutions, digital cultural heritage, collaboration

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green