Oceanographic Data Management

In this chapter the authors look at technological issues within and the influence of technological developments outside oceanography on two very different, but interrelated, facets of ocean data: the labelling of parameters and the autonomous collection of oceanographic data. In particular, consideration is given to the influence of standards developed within computer science, such as Sensor Web Enablement (SWE), Resource Description Framework (RDF) and the Simple Knowledge Organisation System (SKOS). It is shown that the development of autonomy in oceanographic data collection is highly dependent on semantically sound data and metadata with presentation of related issues such as unambiguous data citation, resolution of systematic biases and integration of data from complementary but independently governed oceanographic observation programmes.

Building a 4D Voxel-Based Decision Support System for a Sustainable Management of Marine Geological Resources

For sustainable management of marine geological resources, a geological knowledge base is being built for the Belgian and southern Netherlands part of the North Sea. Voxel models of the subsurface are used for predictions on sand and gravel quantities and qualities, to ensure long-term resource use. The voxels are filled with geological data from boreholes and seismic lines, but other information can be added also. The geology provides boundary conditions needed to run environmental impact models that calculate resource depletion and regeneration under various scenarios of aggregate extraction. Such analyses are important in monitoring progress towards good environmental status, as outlined in the Marine Strategy Framework Directive. By including uncertainty, data products can be generated with confidence limits, which is critical for assessing the significance of changes in the habitat or in any other resource-relevant parameter. All of the information is integrated into a cross-domain, multi-criteria decision support system optimised for user-friendliness and online visualisation.

Data and Operational Oceanography

Data obtained within the operational oceanography infrastructures denote a possibility of significant analysis of fisheries in the progress of the implementation of the 1995 FAO Code for Responsible Fisheries. Data products for fisheries and aquaculture cater for research needs, thereby ensuring a capacity to meet temporal resolution, time frame, reporting frequency and interoperability formats requirements. The existence of this legislation and the costs of its enforcement make that the present data infrastructures are employed under relatively precarious circumstances. This chapter provides with an overview, not exhaustive but demonstrative, of what has been achieved for data within operational oceanography addressing the needs of fisheries and aquaculture scientists.

Semantic Search Engine for Data Management and Sustainable Development

This chapter presents a computer platform supporting a Marine Information and Knowledge System based on a repository that gathers, classify and structures marine scientific literature and data, guaranteeing their accessibility by means of standard protocols. This requires the access to quality controlled data and to information that is provided in grey literature and/or in relevant scientific literature. There exist efforts to develop search engines to find author's contributions to scientific literature or publications. This implies the use of persistent identifiers. However very few efforts are dedicated to link publications to data that was used, or cited in them or that can be of importance for the published studies. Full-text technologies are often unsuccessful since they assume the presence of specific keywords in the text; to fix this problem, it is suggested to use different semantic technologies for retrieving the text and data and thus getting much more complying results.

Linked Ocean Data 2.0

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.

Balancing Formalization and Representation in Cross-Domain Data Management for Sustainable Development

Sustainable development is grounded in complex systems where phenomena and processes are so interrelated and intermingled that they can only be studied in a multiple disciplinary manner. Limitiations in understanding such systems can be identified that are either epistemic and cognitive or socio-economic. Both cases are problematic for collaborative and multidisciplinary studies in sustainable development. This chapter explores these difficulties with a particular focus on data management, an activity that is at the same time very important and very sensitive to such problems. To allow users to find their way through data and information spaces, solutions are proposed that take advantage of either the formalization of knowledge; or of representations, such as schemas, mind maps or graphs. Through a careful balance of these two pathways this chapter demonstrates that it is possible to mitigate the difficulties mentioned above and allow a community to work together at profit.

Repositioning Data Management Near Data Acquisition

This chapter intends to propose a solution to the progressive paradigmatic drift that emerges when data is part of a workflow where processes and contexts are not accessible. In this case end users can have difficulties in identifying possible anomalies, or events that might be very important for the dataset and its interpretation. Since sustainable development is based on cross-disciplinary studies, this can revert in misunderstanding and difficulties to work collaboratively. To address this issue it is proposed to fill the gap between the data and its acquisition through a logging system named EARS that records underway data such as for example: meteo or swell, and events such as: anomalies or acquisition milestones. Once all these information are stored, they can be linked to the data through an OGC compliant metadata model and gathered as summaries as required by several data management initiatives.

Developing a Common Global Framework for Marine Data Management

The paradigm shift in marine research moving from the traditional discipline based methodology to a multidisciplinary, ecosystem level approach is being driven by changes in both the policies for the management and exploitation of the ocean, and the scientific method itself. The availability of large volumes of good quality data is fundamental to this increasingly holistic approach to ocean research but there are significant barriers to its re-use. The Ocean Data Interoperability Platform (ODIP) project has been funded in parallel by the European Commission, National Science Foundation in the USA and the Australian Government to promote the development of a common framework for marine data management that leverages the existing marine e-infrastructures which have been created in response to the need for greater sharing of marine data at a regional level.

Analysis of Ocean in Situ Observations and Web-Based Visualization

The sparsity of observations poses a challenge common to various ocean disciplines. Even for physical parameters where the spatial and temporal coverage is higher, current observational networks undersample a broad spectrum of scales. This situation is generally more severe for chemical and biological parameters because such sensors are less widely deployed. The present chapter describes the analysis tool DIVA (Data-Interpolating Variational Analysis) which is designed to generate gridded fields from in situ observations. DIVA has been applied to various physical (temperature and salinity), chemical (concentration of nitrate, nitrite and phosphate) and biological parameters (abundance of a species). The chapter also shows the technologies used to visualize the gridded fields. Visualization of analyses from in situ observations provide a unique set of challenges since the accuracy of the analysed field is not spatially uniform as it strongly depends on the location of the observations. In addition, an adequate treatment of the depth and time dimensions is essential.

Interoperability in Marine Sensor Networks through SWE Services

The rapid growth and development in different fields related to sensors has, together with the huge increase of devices due to the decrease of device costs, led to a shift from traditional monitoring, where the data collected is not subject to any management actions, to sensor/processing networks, where in the life cycle more stages are devoted to make the data accessible. Data integration is the first step in advanced environmental monitoring, but assuring that heterogeneous systems can interoperate is still a challenge. The Sensor Web Enablement (SWE) initiative defines a framework to address this issue, offering a set of standard models and interfaces to improve sensor interoperability and to face quality issues in the reliability of sensors. The need for seamless access to observations from marine sensors has been the focus of several research projects. This chapter presents the actions taken in the development of the Spatial Data Infrastructure for project RITMARE to ease the adoption of SWE within the Italian marine community overcoming the main constraints in SWE adoption.