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Indigenous frameworks for data-intensive humanities: recalibrating the past through knowledge engineering and generative modelling.

Authors :
Sydney Shep
Marcus Frean
Rhys Owen
Rere-No-A-Rangi Pope
Pikihuia Reihana
Valerie Chan
Source :
Journal of Data Mining and Digital Humanities, Vol HistoInformatics, Iss HistoInformatics (2021)
Publication Year :
2021
Publisher :
Nicolas Turenne, 2021.

Abstract

Identifying, contacting and engaging missing shareholders constitutes an enormous challenge for Māori incorporations, iwi and hapū across Aotearoa New Zealand. Without accurate data or tools to har-monise existing fragmented or conflicting data sources, issues around land succession, opportunities for economic development, and maintenance of whānau relationships are all negatively impacted. This unique three-way research collaboration between Victoria University of Wellington (VUW), Parininihi ki Waitotara Incorporation (PKW), and University of Auckland funded by the National Science Challenge | Science for Technological Innovation catalyses innovation through new digital humanities-inflected data science modelling and analytics with the kaupapa of reconnecting missing Māori shareholders for a prosperous economic, cultural, and socially revitalised future. This paper provides an overview of VUW's culturally-embedded social network approach to the project, discusses the challenges of working within an indigenous worldview, and emphasises the importance of decolonising digital humanities.

Details

Language :
English
ISSN :
24165999
Volume :
HistoInformatics
Issue :
HistoInformatics
Database :
Directory of Open Access Journals
Journal :
Journal of Data Mining and Digital Humanities
Publication Type :
Academic Journal
Accession number :
edsdoj.0504d86854b64d06acff05dbf521eb41
Document Type :
article
Full Text :
https://doi.org/10.46298/jdmdh.6095