The I-ADOPT Interoperability Framework: a proposal for FAIRer observable property descriptions

Global environmental challenges like climate change, pollution, and biodiversity loss are complex. To understand environmental patterns and processes and address these challenges, scientists require the observations of natural phenomena at various temporal and spatial scales and across many domains. The research infrastructures and scientific communities involved in these activities are often following their own data management practices which inevitably leads to a high degree of variability and incompatibility of approaches. Consequently, a variety of metadata standards and vocabularies have been proposed to describe observations and are actively used in different communities. However, this diversity in approaches now causes severe issues regarding the interoperability across datasets and hampers their exploitation as a common data source.

Projects like ENVRI-FAIR, FAIRsFAIR, FAIRplus are addressing this difficulty by working on the full integration of services across research infrastructures based on FAIR Guiding Principles supporting the EOSC vision towards an open research culture. Beyond these projects, we need collaboration and community consensus across domains to build a common framework for representing observable properties. The Research Data Alliance InteroperAble Descriptions of Observable Property Terminology Working Group (RDA I-ADOPT WG) was formed in October 2019 to address this need. Its membership covers an international representation of terminology users and terminology providers, including terminology developers, scientists, and data centre managers. The group’s overall objective is to deliver a common interoperability framework for observable property variables within its 18-month work plan. Starting with the collection of user stories from research scientists, terminology managers, and data managers or aggregators, we drafted a set of technical and content-related requirements. A survey of terminology resources and annotation practices provided us with information about almost one hundred terminologies, a subset of which was then analysed to identify existing conceptualisation practices, commonalities, gaps, and overlaps. This was then used to derive a conceptual framework to support their alignment. 

In this presentation, we will introduce the I-ADOPT Interoperability Framework highlighting its semantic components. These represent the building blocks for specific ontology design patterns addressing different use cases and varying degrees of complexity in describing observed properties. We will demonstrate the proposed design patterns using a number of essential climate and essential biodiversity variables. We will also show examples of how the I-ADOPT framework will support interoperability between existing representations. This work will provide the semantic foundation for the development of more user-friendly data annotation tools capable of suggesting appropriate FAIR terminologies for observable properties.