/ PROJECT

Mapping Human Earth Systems

/ DATE

2024—2025

/ ROLE

Research, design, development, writing

/ TYPE

Thesis, participatory mapping, data viz

Exhibition installation image from Mapping Human Earth Systems

/ OVERVIEW

Mapping Human Earth Systems operationalises “truthful” visualisation through two live case studies and a reusable system: a certification-timeline map for organic farms and a participatory network map for Māori businesses. The work centres data sovereignty, fluid ontologies, and user authorship.

Thesis aim: design a framework that keeps provenance, consent, and context attached to data across collection, processing, and display.

/ TRUTH MODEL

Two complementary lenses guide representation.

Correspondence

Faithful alignment to verifiable facts for quantifiable layers: locations, dates, certification states.

Coherence

Internal consistency for qualitative layers: lived narratives, tikanga, sites of significance, community notes.

The UI exposes both: maps for facts, drawers for context, and narrative “story snapshots”.

/ GEODESIGN LOOP

Process follows an iterative loop from the thesis: RepresentationProcessEvaluationChangeImpactDecision. Each prototype cycles evidence → design → feedback with community stakeholders.

/ BARRIERS ADDRESSED

  • Cost: open-source stack replaces paid GIS where possible.
  • Skills: progressive disclosure, inline help, and raw table access.
  • Data gaps: participatory inputs plus visible provenance and status.
  • Trust: consent badges, TK Labels, and reversible sharing scopes.

/ CASE STUDY 1 — MAPPING TRUST IN ORGANICS

Organic certification provides a verifiable temporal pathway.

C0 Registration C1 Conversion C2 Conversion Certified Full
  • Interactive timeline: scrub years to see progression from C0→Certified.
  • Minimal basemap: spatial clarity over satellite noise.
  • Data table view: full record list with PII redacted.

Early Unreal Engine tests informed scope. Web mapping chosen for reach and performance.

/ CASE STUDY 2 — MĀORI WELLINGTON BUSINESSES

Network view with opt-in verification, sites of significance, and narrative overlays.

Verification tiers

  • Self-identified submitted by owner or community.
  • Community-verified corroborated by network.
  • Certified formal governance/ownership evidence.

Views

  • Geospatial clusters by suburb and ANZSIC.
  • Abstract “metro-style” relationship map for non-cartesian sense-making.
  • Sites of significance overlay with culturally aware icons.

/ PARTICIPATION, FLUID ONTOLOGIES, TK LABELS

  • Add marker (+): users submit businesses or places. Stored in a separate queue, visualised distinctly.
  • Fluid ontology: tags evolve with community use. No fixed taxonomy lock-in.
  • Consent badges on each record: Provenance: source Scope: public/community/private Revocation: enabled
  • TK Labels metadata: usage, attribution, and cultural protocol embedded in records.
  • Story snapshots: curate sequences of points and notes for teaching or advocacy.

/ SYSTEM & STACK

  • Data prep: Python/Pandas, GeoPandas.
  • Viz: Leaflet / React-Leaflet, custom vector tiles, D3-style clustering.
  • Design: Figma, Illustrator for UI and iconography.
  • Governance: provenance fields, consent states, TK Labels, audit log.

/ ONBOARDING

Landing explainer, guided tutorial, inline tips, and a data transparency panel linking sources, methods, and caveats.

/ OUTCOMES

  • Reusable mapping kit with consent and provenance baked in.
  • Two working prototypes: certification timeline map and Māori business network map.
  • Design patterns: layer chips with time windows, context drawers, uncertainty notation.

Optional to add later: user counts, submission volume, workshop notes, access stats.

/ REFERENCES

D’Ignazio, C., & Klein, L. Data Feminism.
Drucker, J. “Humanities Approaches to Graphical Display.”
Kukutai, T., & Taylor, J. Indigenous Data Sovereignty.
Tufte, E. The Visual Display of Quantitative Information.
Wilkins, D. “Sites of significance” guidance.

Full bibliography in thesis PDF.