[WEBINAR] Pier Luigi Buttigieg on publishing F.A.I.R data for agriculture development
Channel: CGIAR Platform for Big Data in Agriculture
Date: 2018-12-06

A semantic layer for the Sustainable Development Goals: Linking data, information, and knowledge in support of socio-ecological development

This talk was given for the International Data Week 2018, Botswana, in the CoData session on ‘Semantics for publishing FAIR data in Agriculture for Development ‘
In this video, Pier Luigi  Buttigieg , Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, introduces the Sustainable Development Goals Interface Ontology (SDGIO) – a human- and machine-readable representation of knowledge about the SDGs, their targets, and their indicators. 

The Sustainable Development Goals (SDGs) are far reaching, prompting action from myriad elements in socio-ecological systems across the planet. Official and unofficial collections and streams of data are emerging which are of great relevance to the SDG process, but their exact relationship to the SDGs, their targets, and their indicators is often hard to assess efficiently and at scale. Further, the data, information, and knowledge needed to fully understand how the SDGs are being achieved are inherently complex, often patchy, and subject to change. This complexity is compounded by variation introduced by national and sub-national contextualisation of SDG-relevant data. Handling information across these contexts requires the intervention of local knowledge, encoded in such a way that it can be used by informatics solutions and interfaced with global understandings.
 
This resource offers those working with SDG data a stable and logically coherent semantic reference to concretely assert what their data is about. SDGIO is an open resource maintained by a working group coordinated by UN Environment, expressed in the Web Ontology Language (OWL), and aligned to the best practices of the Open Biological and Biomedical Ontologies (OBO) Foundry and Library and the FAIR principles. 

The ontology is linked to and reuses a growing collection of community ontologies which are used in fields including ecology, environmental science, epidemiology, agronomy, and food informatics. 

These resources express and logically interlink both global and local understandings and standards in a way that is computationally accessible, queryable, and aligned to semantic web conventions. Software developers can leverage this content to work with data in novel ways, aligned to the knowledge captured from experts from multiple disciplines. To ensure inclusivity and representativeness, SDGIO and its associated ontologies can be extended by all and we welcome co-editors to drive future development.


We describe how SDGIO may be used as a map of knowledge and aid the community in the identification of gaps, inconsistencies, and opportunities to generate multipurpose data which is simultaneously relevant to several targets and indicators. Contributors may extend this map into regions with sparse data, marking them as targets for collaborative action. In this mode, SDGIO provides a knowledge-level tool to help the SDG data community rally their efforts to create a well-coordinated datascape for sustainable development. In sum, SDGIO provides a stable, operational, and extensible semantic solution to bolster efforts to interoperably link distributed data stores from the local to the global level. 


About the presenter, Pier Luigi:

My work focuses on the combination of semantics, bioinformatics, and data analysis in aid of meaningfully mobilising ecological data and detecting structure in this complex and plastic context. I apply omics-focused bioinformatics and multivariate statistics (see http://mb3is.megx.net/gustame) to the diverse data sets derived from microbial ecology investigations. I also develop resources to assist microbial ecologists in learning and effectively using these techniques. Concurrently, I research environmental semantics and lead the Environment Ontology (ENVO; www.environmentontology.org) in support of semantically consistent data standardisation across and beyond the life sciences. I am also co-leading the Sustainable Development Goals Interface Ontology (SDGIO; https://github.com/SDG-InterfaceOntology/sdgio) to better link scientific output to societal goals. My past training in biochemistry, cell biology, and marine microbiology grounds my current in silico work in biological knowledge.