Cardiff University lead new paper on ten principles to improve EBV informatics
14 January 2019
A new paper published in the journal Ecological Informatics outlines an interoperability framework for Essential Biodiversity Variable (EBV) data products.
Since 2013 a key question has been how to prepare data products for EBVs on a global scale. It has also remained unclear what is needed to build transparent and easily accessible EBV data products for any geographical area, over any required time period, for any species, assemblage, ecosystem, or biome of interest and with data that may be held by any (or across multiple) data repositories
A key step to answer those questions includes the improvement of cooperation and interoperability among multiple stakeholders. The new publication suggests ten areas where data and informatics interoperability among infrastructures can be improved in support of EBVs. The ten areas cover data management planning, data structure, metadata, services, data quality, scientific workflows, provenance ontologies/vocabularies, data preservation and accessibility.
For each area, a core interoperability principle is described and desired outcomes and goals are provided. The implementation guidelines are presented as the 'Bari Manifesto', named after the town in southern Italy where they were specified.
“The Bari Manifesto provides a strong basis for supporting EBVs and the success of a global EBV framework. The interoperability framework will also contribute towards a stronger infrastructural basis for biodiversity and ecological informatics more generally” says Alex Hardisty, lead author of the paper from Cardiff University.
The article also highlights specific actions to improve data interoperability. The recommendations are formulated separately for different stakeholders, including data standards bodies, research data infrastructures, pertinent research communities and funders.
W. Daniel Kissling, the scientific coordinator of the GLOBIS-B project said: “We hope that the Bari Manifesto will allow us to build scientific workflows for making reproducible and transparent EBV data products.”