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Risk Academy, led by the Nexus Consortium · Course catalogue · Risk Science and Methods

Geospatial and Risk Data Science

Risk information standards and interoperability

Risk information standards and interoperability, taught twice over: as the working methods of the field and as its frontier since 2024, with labs on the Academy's tools, open data and the Nexus Standards.

Core course Frontier course

The discipline

01Core course · L2 Intermediate

Risk information standards and interoperability: foundations and practice

This area covers the standards that make risk information findable, citable and checkable across organisations: persistent identifiers, dataset and metadata profiles, naming rules, and how a standard is adopted and its conformance shown.

Level
L2 Intermediate
Study time
about 24 hours (planning estimate)
Status
In authoring
Prerequisites
An L1 course in the area, or an entry review

Why now

An open, formal format for elevation point clouds supports reproducible terrain and exposure analysis across tools. Open Geospatial Consortium, OGC Announces Publication of the LAZ 1.4 Community Standard, 3 September 2026

Learning outcomes

  1. Define UNI and the other key terms of the discipline and use them correctly in a written case
  2. Explain persistent identifiers and the UNI and versioning and corrections with a worked example and its source
  3. Apply the discipline's method to a documented case and explain each result with its source
  4. Analyse a named case against metadata profiles: STAC, DCAT and PROV-O, stating evidence, date and limits

Modules

  1. Persistent identifiers and the UNI
    • Persistent identifiers and the UNI
    • Versioning and corrections
    • Metadata profiles: STAC, DCAT and PROV-O
  2. Licence and provenance metadata
    • Licence and provenance metadata
    • Honesty and epistemic state fields
    • Naming and public identity rules
  3. Standards adoption and attestations
    • Standards adoption and attestations
    • Conformance checking and typed states
  4. Lab: the discipline's method
    • A reference is only as good as its resolution years later; a plain web address decays at a measurable rate while a persistent identifier with a registry and a resolver holds, and the share of a corpus that still resolves, times the share whose metadata and version history are complete, is the share a later reader can check.
    • Work the method through a documented case and explain each result
    • Read the method's sources and stated values

Labs with Academy tools

Nexus Standards

Teaches

  • NS-1 The UNI and the artefact catalogue
  • NS-3 The Global Risks Index (NXS-GRX) record UNIs (grammar, legacy crosswalk, allocation authority)
  • NS-3B NS-3B
  • NS-10 Policies and clauses (machine-readable obligations, enforcement in commons and command rooms)
  • NS-11 Verification and monitoring (evidence, attestations, zero-trust conformance observation)
  • NS-13 Standards development process (open proposals, debate, versioning, adoption)
  • NS-14 Conformance and crosswalk to external standards
  • NS-16 UNI application profile (how articles, documents, code, data, APIs and interfaces carry the UNI)

Relies on

  • NRS-A5 Built-in licensing and rights
  • NRS-C2 Risk assessment method
  • NRS-C8 Evidence, uncertainty and provenance
  • NRS-C9 Risk models, methods and validation

Assessment

  • 40%Lab recordWork the discipline's method through a documented case and explain each result with its source and date
  • 40%Case memoApply the discipline's methods to a named place or organisation, stating evidence and limits
  • 20%Key terms checkShort answers on the key terms, marked against the definitions

Delivery

  • Self-paced online, with the labs in the browser
  • Cohort study over six to eight weeks, with a weekly lab review
  • Co-delivered with a partner institution, inside its own courses

Partner on this course

  • Co-teach a module and bring a current case from your work
  • Host a cohort for your learners, with your own schedule and review
  • Contribute a lab: a dataset your institution publishes openly, or a model
  • Review the course content and its references before it opens
  • Translate the course and adapt its cases to your region

How institutions and experts take part

In the Academy LMS

Course on the learning platform
Intermediate, 4 topics
Cohort group
A community group for each cohort of learners
Achievement
Recorded on completion of the assessed work

References

  1. Open Geospatial Consortium, OGC Announces Publication of the LAZ 1.4 Community Standard, 3 September 2026
  2. Klein et al., Scholarly context not found: one in five articles suffers from reference rot, PLoS ONE, 2014
  3. Data Citation Synthesis Group, Joint Declaration of Data Citation Principles, FORCE11, 2014
  4. ISO 26324:2022 Information and documentation, Digital object identifier system, 2022
02Live map

Hazards and exposure in Italy

Flood water, active fires and surface heat beside population and night-time lights, over Italy.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 3

Hazards and exposure

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.

Hazards and exposure, framed on Italy.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · U.S. Geological SurveySources and licences

  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • NASA Fire Information for Resource Management System (FIRMS), VIIRS 375 m active fire product, NASA LANCE; vector tiles via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
  • VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • MODIS and VIIRS atmosphere products, NASA LANCE and LAADS DAAC; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
  • Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
  • © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
  • Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.
  • Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
  • Live: NASA EONET Events are indicative, not authority warnings.
  • Live: U.S. Geological Survey Events are indicative, not authority warnings.
  • NASA GIBS: We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
  • River discharge forecast, 30 days with range (GloFAS via Open-Meteo): Contains modified Copernicus Emergency Management Service information 2026; not a flood warning.
  • Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
  • Optional layers (10 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.

Layers and dates

  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
  • Active fires and thermal anomalies: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026
  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
  • Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
  • Aerosol optical depth, daily: VIIRS NOAA-20 Deep Blue AOD, NASA LANCE · 13 Oct 2026

03How learning runs

How learning runs, as a process you can run

Select a scenario and press Play: course, pathway, practice, faculty, cells and record.

04What is changing

Frontier course · L3 advanced, programme courses and standards

Risk information standards and interoperability: frontier methods

The methods, data, tools and studies that changed risk information standards and interoperability between 2024 and 2026, taught by reproducing them on open data.

Level
L3 Advanced
Study time
about 28 hours (planning estimate)
Status
Planned
Prerequisites
Risk information standards and interoperability: foundations and practice; Working knowledge of a scripting language (Python or R) for the labs

Why now

An open, formal format for elevation point clouds supports reproducible terrain and exposure analysis across tools. Open Geospatial Consortium, OGC Announces Publication of the LAZ 1.4 Community Standard, 3 September 2026

Learning outcomes

  1. Explain what changed in risk information standards and interoperability since 2024 and cite the studies, data or rules behind each change
  2. Reproduce OGC published LAZ 1.4 for lossless LiDAR compression on open data and state the uncertainty of the result
  3. Evaluate a 2024 to 2026 study: its question, data, method, limits and what it changes for practice
  4. Design an analysis that combines a frontier method with the faculty's instruments, and justify each choice

Modules

  1. OGC published LAZ 1.4 for lossless LiDAR compression
    • OGC published LAZ 1.4 as a Community Standard for lossless compression of LAS 1.4 point clouds, with chunked and layered storage for selective reading and the open LASzip library as reference implementation.
    • An open, formal format for elevation point clouds supports reproducible terrain and exposure analysis across tools.
    • Open Geospatial Consortium, 3 September 2026
  2. EU finalised a code on marking and labelling AI-generated content
    • The Code of Practice on Transparency of AI-generated Content, finalised on 10 June 2026 after three drafting rounds, helps providers and deployers meet AI Act duties to mark and label AI-generated content.
    • Machine-readable marking conventions affect how provenance of images and text can be checked across systems.
    • European Commission, 10 June 2026
  3. DataCite Metadata Schema 4.7 added new identifiers and relations
    • DataCite released schema 4.7, adding Poster and Presentation resource types, RAiD and SWHID identifier types, an Other relation type and a relationTypeInformation sub-property.
    • Software Heritage and project identifiers let risk datasets cite the exact code and projects behind them.
    • DataCite, 3 March 2026
  4. Reproduction lab
    • Extend the discipline's method with one frontier method and compare its results
    • State the uncertainty and the limits of the result
    • Peer review against a shared checklist

Labs with Academy tools

Nexus Standards

Teaches

  • NS-1 The UNI and the artefact catalogue
  • NS-3 NXS-GRX record UNIs (grammar, legacy crosswalk, allocation authority)
  • NS-3B NS-3B
  • NS-10 Policies and clauses (machine-readable obligations, enforcement in commons and command rooms)
  • NS-11 Verification and monitoring (evidence, attestations, zero-trust conformance observation)
  • NS-13 Standards development process (open proposals, debate, versioning, adoption)
  • NS-14 Conformance and crosswalk to external standards
  • NS-16 UNI application profile (how articles, documents, code, data, APIs and interfaces carry the UNI)

Relies on

  • NRS-A5 Built-in licensing and rights
  • NRS-C2 Risk assessment method
  • NRS-C8 Evidence, uncertainty and provenance
  • NRS-C9 Risk models, methods and validation

Assessment

  • 50%Method reproductionReproduce one frontier method on open data and state the uncertainty of the result
  • 30%Study reviewA critical review of a 2024 to 2026 study: question, data, method, limits, what it changes
  • 20%Peer reviewReview two other learners' reproductions against a shared checklist

Delivery

  • Self-paced online, with the labs in the browser
  • Cohort study over six to eight weeks, with a weekly lab review
  • Co-delivered with a partner institution, inside its own courses

Partner on this course

  • Co-teach a module and bring a current case from your work
  • Host a cohort for your learners, with your own schedule and review
  • Contribute a lab: a dataset your institution publishes openly, or a model
  • Review the course content and its references before it opens
  • Translate the course and adapt its cases to your region

How institutions and experts take part

In the Academy LMS

Course on the learning platform
Expert, 4 topics
Cohort group
A community group for each cohort of learners
Achievement
Recorded on completion of the assessed work

References

  1. Open Geospatial Consortium, OGC Announces Publication of the LAZ 1.4 Community Standard, 3 September 2026
  2. European Commission, Code of Practice on Transparency of AI-generated Content, 10 June 2026
  3. DataCite, DataCite Metadata Schema 4.7, 3 March 2026
  4. Klein et al., Scholarly context not found: one in five articles suffers from reference rot, PLoS ONE, 2014
  5. Data Citation Synthesis Group, Joint Declaration of Data Citation Principles, FORCE11, 2014
  6. ISO 26324:2022 Information and documentation, Digital object identifier system, 2022
05Take part

Take part in the work

Start from who you are.

06Questions

Questions, answers and key terms

Is the course free?
Yes. Every course and learning material of Risk Academy, led by the Nexus Consortium, is free to study, self-paced or with a cohort. Ordinary participation has no fee; paid work, internships and fellowships are separate arrangements.
What does completing a course give me?
A completion record: the course, its version, the date and what was assessed, private by default and shared by you. It stacks into discipline, department and programme achievements. A record states what was studied and assessed and does not certify competence; it is not a licence, a professional title or an employment status.
Where do the data and the places come from?
Every faculty teaches on a twin of a real place built from open data; each layer carries its provider, licence and date, and every result on the Academy states its source. Maps and figures are indicators for teaching, never an assessment of a place.
How do I take part beyond the course?
Form a competence cell of three to seven people, study a shared pathway, take a supervised assignment in the National Working Groups, or bring a cohort from your institution. For organisations.

Key terms

Term

UNI

The Nexus Standards identifier that names an artefact, record or page and resolves to its catalogue entry.

Term

Persistent identifier

An identifier that stays the same and resolvable even when the resource moves.

Term

Metadata profile

A set of rules on which metadata fields to use and how.

Term

PROV-O

The W3C provenance ontology for describing how data were produced.

ReportsContribute

Contribute evidence from this page.

Reports is the Consortium's quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

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