The NERC Vocabulary Server (NVS) is a global resource used to manage controlled vocabularies and semantic relationships between concepts. Both speakers are involved in collaborations dedicated to developing FAIR data and services. Their combined interests and expertise include standardization, semantic interoperability, Linked Data, ontologies, and the Semantic Web.


Drs Gwen Moncoiffe and Alexandra Kokkinaki lead the NERC Vocabulary Server (NVS) at the National Oceanography Centre - British Oceanographic Data Centre (NOC-BODC). 

Gwen has a 20+-year career in scientific data management at BODC. She is currently co-chair of the Research Data Alliance (RDA) Working Group InteroperAble Descriptions of Observable Property Terminologies (I-ADOPT) developing a semantic framework and best practices to support semantic interoperability within and across domain boundaries.

Alexandra has worked on standardisation and interoperability in the medical domain and is technical lead of the NVS and co-chair of the RDA Vocabulary Semantic Services Interest Group (VSSIG) that addresses various aspects of making semantic resources Findable, Accessible, Interoperable and Reusable (FAIR).

This event is part of the 'data management and analytical tools for environmental science' webinar series

The NERC Constructing a Digital Environment programme runs an active webinar activity. Held every three weeks, these aim to develop the digitally enabled environment to benefit scientists, policymakers, businesses, communities and individuals. The webinars are arranged into ‘series’, drawing together presentations following similar themes. 

The fourth webinar series, led by the NERC Environmental Data Service (NERC EDS) focusses on research data management and the analytical tools available to support researchers in the environmental sciences. This series showcases the services provided by the EDS and illustrates how it supports the open data agenda. The series will describe how tools developed by the EDS enable interoperability, support large-scale data analysis and facilitate multi- and trans-disciplinary research.