Aggregated and Validated Datasets for the European Seas: The Contribution of EMODnet Chemistry

• Published in: Frontiers in Marine Science 2020-12, Vol.7 (583657)
• Main Authors: Giorgetti, Alessandra, Lipizer, Marina, Molina Jack, Maria Eugenia, Holdsworth, Neil, Jensen, Hans Mose, Buga, Luminita, Sarbu, George, Iona, Athanasia, Gatti, Julie, Larsen, Martin, Fyrberg, Lotta, Østrem, Ann Kristin, Schlitzer, Reiner
• Format: Article
• Language: English
• Subjects: acidity; Aggregation; Antifoulants; Archives & records; biota; Chemical oceanography; Chemistry; Chlorophyll; Chlorophylls; Contaminants; Data collection; Data management; Datasets; Eutrophication; Heavy metals; Historical account; History; Hydrocarbons; Identification; Information centres; Interoperability; Litter; Litters (births); Marine debris; Marine pollution; Metadata; Metals; Nutrients; Ocean floor; Oceanic analysis; oxygen; Pesticides; Procedures; Quality control; Quality standards; Sciences of the Universe; Security services; sediment; Semantics; Software; Statistical methods; Visualization; Vocabularies & taxonomies
• ISSN: 2296-7745; 2296-7745
• DOI: 10.3389/fmars.2020.583657

The objective of EMODnet Chemistry is to provide easy and open access to marine chemistry data sets and data products related to three main categories: eutrophication (e.g., nutrients, oxygen and chlorophyll), contaminants (e.g., hydrocarbons, pesticides, heavy metals, antifoulants) and marine litter (e.g., beach litter, seafloor litter and floating micro-litter). Historical data are often deprived of any detailed information on analytical procedures, calibrations and confidence intervals; conversely, large efforts are currently carried out in the framework of European data management initiatives to properly collect and archive this kind of relevant metadata. In order to obtain data aggregation per sea region from the heterogeneous datasets originating from multiple institutions, an automatic Robot Harvester, properly configured with predefined criteria of geographical and temporal coverage and parameters, was adopted to retrieve specific data sets from distributed data centers. Regional quality control follows procedures compiled in discussion with the wider international community (e.g., IOC/IODE, ICES and JCOMM, SeaDataNet Data Quality Control Procedures) and involves: metadata format correctness and completeness check, data format checks, identification of negative and zero values, identification of wrong measurement units and “broad range” check which consists in the comparison with minimum and maximum regional values derived from previous statistics (SeaDataNet, 2010; Barth et al., 2015; Buga et al., 2019).