No abstract

The Atlantic Meridional Transect (AMT) series of twenty-five cruises over the past twenty years has produced a rich depth-resolved biogeochemical in situ data resource consisting of a wealth of essential core variables. These multiple core datasets, key to the operation of AMT, such as temperature, salinity, oxygen and inorganic nutrients, are often only used as ancillary measurements for contextualising hypothesis-driven process studies. In this paper these core in situ variables, alongside data drawn from satellite Earth Observation (EO) and modelling, have been analysed to determine characteristic oceanic province variability encountered over the last twenty years on the AMT through the Atlantic Ocean. The EO and modelling analysis shows the variability of key environmental variables in each province, such as surface currents, the net heat flux and subsequent large scale biological responses, such as primary production. The in situ core dataset analysis allows the variability in features such as the tropical oxygen minimum zone to be quantified as well as showing clear differences between the provinces in nutrient stoichiometry. Such observations and relationships can be used within basin scale biogeochemical models to set realistic variability bounds.

The International Oceanographic Data and Information Exchange of UNESCO's Intergovernmental Oceanographic Commission (IOC-IODE) released a quality management framework for its National Oceanographic Data Centre (NODC) network in 2013. This document is intended, amongst other goals, to provide a means of assistance for NODCs to establish organisational data management quality management systems. The IOC-IODE's framework also promotes the accreditation of NODCs which have implemented a Data Management Quality Management Framework adhering to the guidelines laid out in the IOC-IODE's framework. In its submission for IOCE-IODE accreditation, Ireland's National Marine Data Centre (hosted by the Marine Institute) included a Data Management Quality Management model; a manual detailing this model and how it is implemented across the scientific and environmental data producing areas of the Marine Institute; and, at a more practical level, an implementation pack consisting of a number of templates to assist in the compilation of the documentation required by the model and the manual.

Within the theme of sustainable development, it is not desirable to either have data siloed in one location where it cannot be reused for purposes beyond which it was originally collected, or in a state where it cannot be integrated into a holistic view of the marine environment. As such, the links between datasets should be formally documented and exploited as best as possible. Given this, the use of Semantic Web technology and information modelling patterns are explored in this chapter with reference to the marine domain. Further, new strategies for adding semantic annotation to data in real-time are discussed and prototyped.