Lessons Learned From the EnviroGRIDS Project on the Black Sea Catchment

Sunday, 15 February 2015: 8:30 AM-11:30 AM
Room LL20C (San Jose Convention Center)
Anthony Lehmann, University of Geneva, Carouge, Switzerland
The enviroGRIDS project is focusing on the Black Sea catchment by modeling its hydrology in order to predict future water resource vulnerabilities. The datasets produced by the project are made available through a Grid-enabled Spatial Data Infrastructure (SDI). Several components of the Black Sea catchment Observation System are linked to Grid computing infrastructures.

Currently, hydrological, meteorological and agricultural data remain difficult to find, access, and integrate because of various incompatibilities in data formats, models and quality, missing documentation (metadata), data fragmentation and replication, non-existing or inappropriate data policies, and isolation of operating systems. International initiatives catalyze data sharing by promoting interoperability standards to maximize the reuse of data. Improvements require the endorsement of some commonly agreed standards and documenting data with adequate metadata.

International initiatives such as Global Earth Observation System of Systems (GEOSS) and the European framework INSPIRE, promote the interoperability to maximize the reuse of geospatial data. The System of Systems framework supported by a brokering approach interconnects different systems and provides a real multi-disciplinary framework. SDI concepts, methods and technologies certainly represent an important step toward removing barriers to data availability, accessibility, integration, and modeling.

More recent data standards are enhancing interoperability between scientific disciplines, while distributed computing infrastructures can handle complex and large datasets and models, and Web Processing Services bring the flexibility to develop and execute simple to complex workflows over the Internet.

With all these technological improvements, large steps are being made to improve the science-policy interface. The most difficult step however remains to bring scientists and decision-makers around the same table to build their project together with an adaptive strategy. One way forward is through building interdisciplinary projects where several forms of knowledge (scientific, economic, social) are processed, compared and integrated to provide a holistic context within which important decisions may be informed and negotiated.