Kimihia te Matangaro

Rere ki uta, rere ki tai, tau mai te manu, pītakataka ki tō pae e

karearea

Tēnā koutou katoa,

Kimihia te Matangaro is a project that empowers Māori communities to reconnect uri with their whenua and whakapapa through automated linking of publicly accessible data. This video offers an overview of our web-based tools, our unique inference approach, and compelling stories that demonstrate the value of reconnection. Examples of impact include timely processing of successions, the reclamation of ancestral names for landblocks that catalyse new land use strategies, enhancing information access, and community engagement leading to more equitable decision-making. Whether you are an iwi, hapū, marae, trust, or Māori business entity, finding and reconnecting with your missing uri is key to increased economic, social, cultural prosperity and spiritual wellbeing.

If we could assist you in mapping your people’s journey back home, please contact our team at kimihia-te-matangaro@vuw.ac.nz

Our National Science Challenge - Science for Technological Innovation Spearhead (2016-2024) Te Tātari Raraunga was a unique three-way research collaboration between University of Auckland, Victoria University of Wellington, and Parininihi ki Waitōtara Incorporation that catalysed innovation through new data science modelling and analytics in the context of Mātauranga Māori with the kaupapa of reconnecting missing Māori whānau for a prosperous economic, cultural, and socially revitalised future.

Researchers from Te Herenga Waka - Victoria University of Wellington led by Co-PIs Marcus Frean and Sydney Shep worked with Māori Land Court, Births, Deaths and Marriages Historical, Land Information New Zealand (LINZ). and Cenotaph data, using machine learning and Bayesian record linkage to identify and validate the existence and location of specific names relating to whenua. Small-scale prototype apps were developed that drew on both analogue and digital maps as well as our linked data triplestore. Central to this mahi was the development of ‘Punakupu’, the first bilingual Māori-English ontology (classification and explanation of entities) that underpins the data structure, defining relationships between data points through a Te Ao Maōri lens. Throughout the project, the CARE principles of Indigenous Data Governance and issues around Māori Data Sovereignty were acknowledged, honoured, and put into practice.

Our research team focused on building capability amongst Māori researchers, summer scholars, postgraduate researchers and interns, Masters and PhD students. We were honoured to have worked with: Adrian Poa (Ngāti Maniapoto, Ngāti Porou), Rere-No-A-Rangi Pope (Ngā Ruahine, Te Ati Awa), Rhys Owen (Te Rarawa ki Hokianga - Ngāi Tūpoto and Ngāti Here), Marino Doyle (Ngā Rauru, Ngāti Ruanui), Daniel Kahu (Ngāti Kahungunu), Pikihuia Reihana (Ngapūhi - Ngāti Hine, Ngāti Kahungunu - Ngāti Kere, Rangitane ki Wairau, Ngai Tahu), Rowan Thom (Ngāti Rakaipaaka, Ngāti Kahungunu, Ngāi Tuhoe), Valerie Chan.


Related projects included the conceptualisation of a Māori Data Commons, and most recently, developing new advanced AI and te reo Māori attuned computer vision tools to unlock Mātauranga Māori in historic maps, enabling this taonga data to be a locus for new forms of knowledge sharing and storytelling.

Take a look at our award winning video and read more about the project here. Our co-authored article appeared in a special issue of the Journal of Data Mining and Digital Humanities entitled "HistioInformatics: Computational Approaches to History."


Image credit: Detail from Shane Hansen's, Taranaki Karearea, gifted to the project along with the waiata above, translated by Mitchell Ritai of PKW, which speaks of a bird that takes its flight across land and sea then off to its final resting place, there to remain. It is a metaphor for the journey that our spirits take once we pass away and leave this world. Since the project data is often referring to whānau that have already taken this flight, this kōrero helps us acknowledge those who have passed on and it ensures we appropriately care for the data we are working with.