A new release of the Climate Connectivity Taxonomy (CC Taxonomy), supported by the EU- funded FAIR2Adapt project, was announced on 7 October 2026 by TIB- Leibniz Information Centre for Science and Technology (via Dr. Sandra Niemeyer).

It addresses the fragmentation of climate change adaptation and disaster risk reduction knowledge, which is scattered across platforms and described with inconsistent terminology.

For example, an adaptation practitioner might refer to “adaptive capacity”, while a disaster risk specialist discusses “coping capacity” or “preparedness”. These related but non- interchangeable terms reflect different disciplines, values, timescales, and perspectives on risk.

Key Features of the CC Taxonomy

• It is an AI- and human -curated collection of terms related to climate change and disaster risk.
• Rather than imposing a single vocabulary, it maps connections between terms while preserving distinct meanings, enabling discovery of relevant knowledge across disciplinary boundaries.
• It draws from authoritative sources such as the IPCC Sixth Assessment Report (AR6) glossary and the United Nations Office for Disaster Risk Reduction (UNDRR) and International Science Council Hazard Information Profiles. Additional sources include items like the Myriad- EU Handbook and the Disaster Resilient Infrastructure Lexicon.
• AI- assisted tools continuously harvest content from platforms to identify new terms, which human experts then verify and add.
• Unique “scope notes” provide richer contextual information on how the same term is used differently by various actors or disciplines.
• An open- access API (version 1 released June 2025) allows other platforms and tools to import and align with the taxonomy. A “submit new concept” feature is forthcoming for user contributions.

The Climate Connectivity Hub

The taxonomy powers the Climate Connectivity Hub (freely accessible at https://connectivity-hub.weadapt.org/), an online search- and- discovery tool curated by the Stockholm Environment Institute (SEI). It aggregates knowledge from platforms including weADAPT, CORDIS, PreventionWeb, Climate-ADAPT, and the Resilience Platform.

Users can explore interactive “knowledge maps” linking keywords/concepts, articles, projects, and organizations. It also supports an interactive glossary on weADAPT (hovering over terms shows definitions). The Hub originated under the PLACARD project and has been further developed through MAIA, DIRECTED, and FAIR2Adapt.

Anne Fouilloux (FAIR2Adapt coordinator, LifeWatch ERIC) noted: “We don’t lack knowledge on climate adaptation. We struggle to connect it… The Climate Connectivity Taxonomy is a great example of how FAIR principles can help turn fragmented knowledge into knowledge that can be found, connected, and reused.”

Sukaina Bharwani (SEI) highlighted long- standing frustrations with platforms unable to interconnect, which inhibits shared learning, and emphasized that supporting interoperability helps build on existing knowledge rather than reinventing it.

About FAIR2Adapt

This Horizon Europe project (grant 101188256; started January 2025, three- year duration) aims to transform data into actionable knowledge for climate adaptation strategies using FAIR principles and EOSC alignment. Partners include LifeWatch ERIC, TIB, SEI, and others across Europe. One case study specifically focuses on enriching weADAPT and the Connectivity Hub.

In short, the taxonomy and Hub aim to reduce knowledge silos, accelerate learning and climate action by making existing work more discoverable and reusable, and foster better cross- community understanding of climate risk terminology.

The Climate Connectivity Taxonomy (CC Taxonomy) is an AI- and human- curated collection of terms (concepts and keywords) related to climate change adaptation, mitigation, and disaster risk. It is designed primarily as a bridge across fragmented knowledge rather than a rigid single hierarchy.

Core Design Philosophy

It does not force all terms into one unified vocabulary. Instead, it:

• Maps connections (broader, narrower, and related terms) between concepts.
• Preserves distinct disciplinary, cultural, and contextual meanings.
• Adds rich metadata so users can understand how and why the same term is used differently by different communities (e.g., “adaptive capacity” vs. “coping capacity”).

This supports FAIR principles (Findable, Accessible, Interoperable, Reusable) and powers the interactive knowledge maps in the Climate Connectivity Hub.

Structural Components of Each Term/Node

Each concept (keyword node) typically includes:

• Preferred term (main label).
• Definitions (drawn from authoritative sources).
• Alternative labels / synonyms.
• Broader terms and narrower terms (hierarchical relationships).
• Related terms (non- hierarchical connections).
• Scope notes, contextual background explaining origins, evolution, disciplinary differences, and usage nuances (these were expanded in later updates, especially for adaptation barriers and enablers, measures and actions, and outcomes and benefits).
• Links to tagged content (articles, projects, organizations) in the Hub.

In the Hub interface, terms appear as clickable orange nodes in dynamic network maps, connected to projects (purple), articles (blue), and organizations (green).

How It Is Built (Layered Structure)

The taxonomy is constructed in layers:

1. Seed Taxonomy (Foundational Base)
   • IPCC AR6 Glossary (climate mitigation, adaptation, policy processes, impacts, etc.).
   • UNDRR- ISC Hazard Information Profiles (302 hazards grouped into 8 clusters: meteorological and hydrological, geohazards, biological, technological, societal, etc.).
2. Integrated Existing Terminologies (sub- sets mapped in)
   Examples include the Myriad-EU Handbook of Multi- Hazard and Multi- Risk Definitions, Disaster Resilient Infrastructure (DRI) Lexicon, UNICEF Research, Study, Evaluation, Taxonomy, and others.
3. Thematic / Curated Additions
   Focused expansions addressing gaps, such as:
   • Adaptation outcomes and benefits.
   • Adaptation barriers and enablers.
   • Adaptation measures and actions.
   • Transboundary climate risks.
   • Capacity development and citizen engagement.
   • Climate finance terms and sector-specific options (e.g., agriculture).
4. Platform- Derived Tags
   • Existing tags from weADAPT, CORDIS, PreventionWeb, Climate- ADAPT, Resilience Platform, etc.
   • New candidate terms harvested by large language models (LLMs) from platform content, then manually reviewed and accepted/rejected by experts via an admin panel (prioritized by frequency or presence in robust sources).

Hierarchy and Relationships

• It begins with a relatively flat- to -moderately hierarchical structure (seeded from IPCC and UNDRR sources, which already include some parent and or child links).
• Version updates (e.g., v1.0 June 2025 → v1.1 August 2026) have added a more structured network of broader, narrower and related relationships.
• Future plans explicitly include introducing more hierarchy and relationships to evolve it toward a fuller ontology or knowledge graph.

Access and Formats

• Available via an open- access API (Version 1.0 released 13 June 2025; Version 1.1 on 27 August 2026).
• A SKOS- supported web tool and repository allows searching, filtering, and visualizing concepts.
• Continuously evolving: AI harvests new terms; experts verify; users can submit new concepts.

In short, the CC Taxonomy functions as a living, interconnected semantic network of climate and disaster risk concepts. It prioritizes contextual connections and interoperability over a single rigid classification tree, enabling discovery across platforms and disciplines while highlighting differences in how communities talk about climate risk.

Scaling knowledge interoperability for accelerated climate action through the Climate Connectivity Hub and Taxonomy

The paper addresses the urgency of the climate crisis by arguing that accelerating learning and implementation requires finding, using, and building on existing knowledge rather than reinventing it. The Climate Connectivity Hub and its underlying Climate Connectivity Taxonomy (CC Taxonomy) visualize and connect dispersed online climate information.

Together, they improve interoperability and discoverability of research while promoting a shared understanding of different knowledge domains and their applicability in policy, research, and practice.

Three key objectives:

1. Show that useful taxonomies can emerge from existing project results to support interoperability, discoverability, and identification of knowledge gaps.
2. Visualize the domain expertise of different organizations and increase connectivity between projects.
3. Demonstrate that a shared interpretation of language and terminology adds value to research, policy, and practice.

The study illustrates how taxonomies advance FAIR (Findable, Accessible, Interoperable, Reusable) knowledge for better platform management, more intuitive tool interfaces (e.g., interactive glossaries), and enhanced climate action by decision-makers, planners, researchers, and policymakers.

Next steps outlined:

• Expert verification and validation of the evolving taxonomy (accuracy, relevance, nuances across languages and technical terms).
• Adding more hierarchy and relationships to evolve it toward a richer ontology or knowledge graph.
• Identifying domain knowledge gaps via orphaned projects and expert consultation.

Key Context from the Paper

Climate knowledge is abundant but often siloed, too technical, or not usable for decision- making, leading to limited uptake, wasted resources, and risks like maladaptation (e.g., short- term flood measures that encouraged development in high-risk areas). Platforms lack common standards for describing content, and terminology varies across disciplines (adaptation vs. disaster risk reduction).

The authors distinguish taxonomies from related concepts (glossaries, thesauri, ontologies) and note the proliferation of recent climate- related taxonomies that often lack coherence. Collaborative tagging systems create further issues (synonyms, inconsistent terms, lack of hierarchy).

The CC Taxonomy was seeded with the IPCC AR6 glossary and UNDRR/ISC Hazard Information Profiles, then expanded via machine learning on sources like CORDIS and weADAPT, expert review of other knowledge structures, and hybrid (AI and human) curation. It does not force a single vocabulary but maps connections while preserving distinct meanings and adding scope notes and context.

The Climate Connectivity Hub aggregates content from platforms (weADAPT, CORDIS, PreventionWeb, Climate- ADAPT, etc.) and uses the taxonomy for interactive knowledge maps linking concepts, articles, projects, and organizations. Version 1 of the taxonomy (with open API) was released in June 2025.

This work builds on prior efforts (e.g., PLACARD roadmap, MAIA project) and aligns with FAIR principles to reduce silos and accelerate climate action.

The full paper is available open access at the link above (including methods, results on taxonomy mapping and visualization, discussion, and supplementary materials).

Journal information: Climatic Change, Volume 179, article number 48 (2026)

DOI: 10.1007/s10584-026-04139-y, Open access

Published: 24 February 2026

Provided: Leibniz Information Centre for Science and Technology

Authors: Sukaina Bharwani,
Kate Williamson &
Adam Wangrat 

Abstract

Accelerating learning and implementation is necessary to address the urgency of the climate crisis. This requires finding, using, and building on previous knowledge rather than replicating what already exists. The Climate Connectivity Hub and underlying Taxonomy seek to enable this by visualizing and connecting dispersed online climate information. Together, these tools increase the interoperability and discoverability of existing research and promote a shared understanding of different types and domains of knowledge and their applicability in policy, research and practice. To reduce climate knowledge silos and to scale up and accelerate climate action that builds on past experience, this paper has three key objectives: (1) to show that useful taxonomies can emerge from existing project results supporting interoperability, discoverability and the identification of knowledge gaps; (2) to visualize the domain expertise of different organizations and increase connectivity between projects; and, (3) to show that a shared interpretation of language and terminology can add value to research, policy and practice. This study illustrates how taxonomies can advance findable, accessible, interoperable, reusable (FAIR) knowledge in a robust yet dynamic way for: better platform knowledge management and interoperability; more intuitive user interfaces in tool development e.g. through interactive glossaries; and, enhanced climate action by decision makers, planners, researchers, and policy makers. Next steps will include (1) expert verification and validation of the evolving taxonomy, including assessing its accuracy, relevance and the nuances of interpretation in both technical terminology and diverse languages; (2) introducing more hierarchy and potential relationships to aid the taxonomy’s transition towards a more expressive ontology or knowledge graph; and, (3) identifying gaps in domain knowledge through orphaned projects and expert consultation.