Data Methodologies

The Data Methodologies Working Group is dedicated to enhancing data mapping, inter-operability and accessibility of data across research domains in planetary health, building on the experiences and needs of the cluster’s five projects.

Recognising the diverse data landscapes across these projects, the group is working to establish a unified framework that facilitates alignment in data practices through the sharing of metadata, best practices on FAIR data principles, data security and ethical standards, as well as links and unique identifiers to openly available data and code.

Main activities

• Common Data Management Plan (DMP): The cluster-wide DMP is now complete, providing clear guidance on data governance, sharing protocols, metadata standards, and alignment with FAIR principles. It serves as a foundational document for all data-related activities across the five projects.
• Ongoing Data Harmonisation: Projects are applying shared metadata standards and persistent identifiers to ensure interoperability. These efforts are aimed at facilitating cross-project analyses and improving the quality and comparability of results.
• Operational Data Mapping Instrument: The data mapping instrument is fully developed and currently being populated by each project. This tool enables the identification of data types, formats, and sources, improving visibility across the cluster and supporting harmonisation efforts.
• Capacity Building and Knowledge Sharing: The group is actively supporting teams through internal guidance, knowledge exchange sessions, and documentation on FAIR data practices, ethical data use, and open science.

Sub-group on Indicator Developments

The Sub-group on Indicator Development is creating a set of harmonised planetary health indicators to monitor and assess progress across cluster activities.

• Focus Indicator Development Areas
  • Defining core indicators across environmental, health, and social domains
  • Aligning methodologies for consistency and comparability
  • Linking indicators to underlying datasets through the data