1.2BRecords in a climate and agrobiodiversity data architecture
COP 10Data-platform criteria presented to Prime Ministers at UNCCD COP 10
Skills usedAI governance, risk & regulatory complianceMachine learning, deep learning & MLOpsSolution & enterprise architectureData architecture, engineering & governanceSemantic engineering & knowledge managementInnovation & change managementTeam leadership & talent developmentCommunication & thought leadership
IndustriesScientific research & academiaPublic sector & international organisationsAgriculture, food & environmentMedia & publishing
All 11 contributions
- Led a team of data scientists and architects on a climate-change project, designing a large-scale data architecture managing 1.2 billion records to analyse agrobiodiversity.
- Implemented time-series analysis across 3,875 plant sensors in 12 countries for real-time monitoring of climate impact on agricultural systems.
- Designed multi-country sensor-data collection architectures, integrating real-time climate datasets from thousands of sensors into unified analytical systems.
- Authored technical documentation defining recommended criteria for national and international data platforms and enterprise data architecture for desertification datasets, presented to Prime Ministers of several countries at UNCCD COP 10. Evidence ↗
- Engineered REST/SOA services enabling cross-agency interoperability for scientific and environmental data platforms.
- Built semantic data-integration components harmonising agrobiodiversity datasets with global ontologies for multi-agency use.
- Established a corporate taxonomy and knowledge-management framework for UNCCD (Protégé, OWL), strengthening discoverability, semantic interoperability, information governance and institutional knowledge reuse.
- Designed and documented a UN institutional data-governance framework, including enterprise database analysis and entity-relationship modelling for multi-country, multi-agency data systems. Evidence ↗
- Directed the integration of research data from 1,260 institutes worldwide through GBIF, spanning 358 taxonomies and ontologies, for analytics, reporting and scientific insight.
- Applied time-series and dimensional modelling, including slowly changing dimensions, to real-time IoT and environmental sensor data.
- Coordinated communities of practice and regional offices to scale analytics capabilities, data literacy and collaboration, and supported the application of the Dublin Core (DCMI) taxonomy to publications.