An identification and a prioritisation of geographic and temporal data gaps of Mediterranean marine databases

摘要

Getting an overall view of primary data available from existing Earth Observation Systems and networks databases for the Mediterranean Sea, the main objective of this paper is to identify temporal and geographic data gaps and to elaborate a new method for providing a prioritisation of missing data useful for end-users that have to pinpoint strategies and models to fill these gaps. Existing data sources have been identified from the analysis of the main projects and information systems available. A new method to perform the data gap analysis has been developed and applied to the whole Mediterranean basin as case study area, identifying and prioritise geographical and temporal data gaps considering and integrating the biological, geological, chemical and physical branches of the total environment. The obtained results highlighted both the main geographical data gaps subdividing the whole Mediterranean Sea into 23 sub-basins and the temporal data gaps considering data gathered since 1990. Particular attention has been directed to the suitability of data in terms of completeness, accessibility and aggregation, since data and information are often aggregated and could not be used for research needs. The elaborated inventory of existing data source includes a database of 477 data rows originated from 122 data platforms analysed, able to specify for each dataset the related data typologies and its accessibility. The obtained results indicate that 76% of the data comes from ongoing platforms, while the remaining 25% are related to platforms with non-operational monitoring systems. Since the large amount of analysed records includes data gathered in inhomogeneous ways, the prioritisation values obtained for each identified data gap simplify the data comparison and analysis. Lastly, the data gaps inventory contains geographic and temporal information for any missing parameter at the whole basin scale, as well as the spatial resolution of each available data. (C) 2019 Elsevier B.V. All rights reserved.