The Global Centre for Risk and Innovation (GCRI)
Data about people, communities and places can serve the public good or cause harm. Privacy law, consent, data sovereignty, Indigenous data governance and trusted access arrangements decide who may use data, for what and under which safeguards. This page sets out how data rights and trust are built and lost, how governance is assessed, and what evidence serves the regulators, data stewards and communities involved.
GCRI · In development · service level R0
Data rights are the legal and ethical entitlements that individuals and communities hold over data about them. Privacy law, the CARE principles and trusted access arrangements decide who may use data, for what and with which safeguards, and misuse in one programme reduces willingness to share in others.
For data rights and trust, in GCRI's spatial-intelligence reading, the map opens on night lights, true-colour imagery and population density with true colour from NASA GIBS, framed on the contiguous United States; every other NASA layer, live feed and forecast waits in the layer list.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Connected activity, for this page
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
For data rights and trust, in GCRI's spatial-intelligence reading, the map opens on night lights, true-colour imagery and population density with true colour from NASA GIBS, framed on the contiguous United States; every other NASA layer, live feed and forecast waits in the layer list.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.
Layers and dates
The working screen behind this subject: its structure, terms and states. Names are placeholders and values illustrative.
Data rights and trust · Public data platform · Catalogue v5
| Flood extents | Open | Complete | Yes | Published |
| Health facility list | Open | Complete | Yes | Published |
| Mobility traces | Restricted | Partial | n/a | Rights review |
| Household survey | Restricted | Complete | Yes | Access by request |
Data access, licencing and privacy. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Data protection laws give people rights over their data and set lawful bases, purpose limits and safeguards for processing.
Data about groups, including Indigenous peoples, can affect them collectively. The CARE principles assert community authority over such data.
Secure research environments, safe outputs and accredited researchers let sensitive data be analysed without being released.
Misuse or a breach in one programme reduces willingness to share data in others, harming research and services that depend on participation.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Five Safes | A framework for safe data access covering safe projects, people, settings, data and outputs. |
| Statistical disclosure control | Methods that reduce the risk of identifying individuals in released outputs. |
| Lawful basis | The legal ground on which personal data may be processed under data protection law. |
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Countries with comprehensive data protection law | count | annual | UNCTAD data protection legislation tracker | OFFICIAL |
| Data protection complaints received | count | annual | Data protection authority reports | OFFICIAL |
| Projects using trusted research environments | count | annual | Environment operator reports | REPORTED |
| Outputs checked for disclosure before release | percent of outputs | annual | Output checking records | OBSERVED |
| Data sharing agreements with community governance | count | per assessment | Agreement registers | DECLARED |
| Public trust in data use | percent of respondents | per survey | Public attitude surveys | REPORTED |
The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.
Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| UNCTAD Data Protection and Privacy Legislation Worldwide | Status of data protection laws by country | Public, UNCTAD terms |
| Data protection authority annual reports | Complaints, breaches and enforcement | Public records, licence per authority |
| Global Indigenous Data Alliance CARE principles | Principles for Indigenous data governance | Public, GIDA terms |
| Five Safes framework documentation from statistical agencies | Framework for safe access to sensitive data | Public, terms per agency |
| Public attitude surveys on data use | Trust and acceptability of data sharing | Licence per survey |
Data and Compute prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Data protection authorities | Where to focus guidance and enforcement | Complaints and breach evidence |
| Data stewards in agencies and research bodies | How to provide safe access to sensitive data | Environment designs; disclosure protocols |
| Communities and Indigenous governing bodies | On what terms data about them may be used | Agreement templates; governance reviews |
Trust in data systems is slow to build and quick to lose. A single breach, an undisclosed reuse or a feeling that data was taken without fair return can close off sharing for years. Engineering cannot create trust on its own, but it can make trustworthy behaviour verifiable.
Unclear or incompatible licences block reuse even when holders are willing to share.
Technical measures that limit exposure make sharing possible where it otherwise would not be.
Communities whose data is used without say or benefit lose trust and may withdraw cooperation.
De-identification, differential privacy, secure enclaves, federated analysis and secure computation, grounded in cybersecurity and cryptography. Limits: each trades some utility or cost for protection, and de-identification can sometimes be reversed.
Recording who accessed what and why. Limits: logs only help if someone reviews them.
Controlled settings where approved researchers analyse sensitive data without removing it. Limits: cost and capacity.
Encoding terms so systems can respect them. Limits: legal interpretation still requires people.
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.