SOURCE-LINKED INTELLIGENCE

Fragmented data, LOst voices and The potential Silences of the digitised Archive: The case of early modern Maritime disability.

CORDIS · observation · Publication date unknown

of algorithmic or terminological biases and our under-theorised use of computational methods. Transformative studies of race and gender have shown how we can begin to undo this bias, e.g. redesigning machine learning tools to capture people rendered nameless by the violence of the colonial archive. FLOTSAM’s core aim is to further integrate methods for recovering hidden histories with the digital methods and interoperable systems transforming the humanities and cultural heritage, balancing and raising our awareness of power inequalities and marginalisation in our use of digital technologies. It uses eighteenth-century seafaring disability, impairment and difference to: 1) interrogate the roots and action of intersecting biases –global mobility, gender, class, work and abled-ness– inscribed in the original records and imposed externally by digital tools for data organisation, retrieval and analysis, alongside, 2) developing a method to ethically model historical knowledge as interoperable data without imposing pre-existing or new problematic systems of categorisation on marginalised p

Read original source ↗ Open in workspace

recordType

award

status

SIGNED

region

EU

value

236340

unit

EUR