Implementing Marine XML for Observed CTD Data in a Marine Data Exchange Platform

In order to archive, quality control and disseminate a large variety of marine data in a marine data exchange platfonn, a marine XML has been developed to encapsulate marine data, which provides an efficient means to store, transfer and display marine data. This paper first presents the details of the main marine XML elements and then gives an example showing how to transform CTD-observed data into Marine XML format, which illustrates the XML encapsulation process of marine observed data.

GPU Accelerated Marine Data Visualization Method

The study of marine data visualization is of great value. Marine data, due to its large scale, random variation and multiresolution in nature, are hard to be visualized and analyzed. Nowadays, constructing an ocean model and visualizing model results have become some of the most important research topics of ‘Digital Ocean'. In this paper, a spherical ray casting method is developed to improve the traditional ray-casting algorithm and to make efficient use of GPUs. Aiming at the ocean current data, a 3D view-dependent line integral convolution method is used, in which the spatial frequency is adapted according to the distance from a camera. The study is based on a 3D virtual reality and visualization engine, namely the VV-Ocean. Some interactive operations are also provided to highlight the interesting structures and the characteristics of volumetric data. Finally, the marine data gathered in the East China Sea are displayed and analyzed. The results show that the method meets the requirements of real-time and interactive rendering.

Web-based spatiotemporal visualization of marine environment data

With long-term marine surveys and research,and especially with the development of new marine environment monitoring technologies,prodigious amounts of complex marine environmental data are generated,and continuously increase rapidly.Features of these data include massive volume,widespread distribution,multiple-sources,heterogeneous,multi-dimensional and dynamic in structure and time.The present study recommends an integrative visualization solution for these data,to enhance the visual display of data and data archives,and to develop a joint use of these data distributed among different organizations or communities.This study also analyses the web services technologies and defines the concept of the marine information gird,then focuses on the spatiotemporal visualization method and proposes a process-oriented spatiotemporal visualization method.We discuss how marine environmental data can be organized based on the spatiotemporal visualization method,and how organized data are represented for use with web services and stored in a reusable fashion.In addition,we provide an original visualization architecture that is integrative and based on the explored technologies.In the end,we propose a prototype system of marine environmental data of the South China Sea for visualizations of Argo floats,sea surface temperature fields,sea current fields,salinity,in-situ investigation data,and ocean stations.An integration visualization architecture is illustrated on the prototype system,which highlights the process-oriented temporal visualization method and demonstrates the benefit of the architecture and the methods described in this study.

SeaDataNet-Pan-European infrastructure for marine and ocean data management:unified access to distributed data sets

Data availability is of vital importance for marine and oceanographic research but most of the European data are fragmented,not always validated and not easily accessible.In the countries bordering the European seas,more than 1000 scientific laboratories from governmental organisations and private industry collect data using various sensors on board of research vessels,submarines,fixed and drifting platforms,aeroplanes and satellites to measure physical,geophysical,geological,biological and chemical parameters,biological species and others.SeaDataNet is an Integrated Research Infrastructure Initiative(I3)(2006-2011)in the EU FP6 framework programme.It is developing an efficient distributed Pan-European marine data management infrastructure for managing these large and diverse data sets.It is interconnecting the existing professional data centres of 35 countries,active in data collection and providing integrated databases of standardised quality on-line.This article describes the architecture and the features of the SeaDataNet infrastructure.In particular it describes the way interoperability is achieved between all the contributing data centres.Finally it highlights the on-going developments and challenges.

Lessons from a Marine Spatial Planning data management process for Ireland

This paper presents a framework containing ten components to deliver a data management process for the storage and management of data used for Marine Spatial Planning(MSP)in Ireland.The work includes a data process flow and a recommended solution architecture.The architecture includes a central data catalogue and a spatial storage system.The components of the process are presented to maximise the reuse potential of any dataset within an MSP context.The terms‘Suitability’and‘Readiness’in the MSP context are offered as both formal and considered assessments of data,as is the applicability of a data stewardship maturity matrix.How data contained in such a storage system can be published externally to potential consumers of these data is also explored.The process presents a means of managing data and metadata to ensure data lineage is optimised by carrying information about the origin of and the processing applied to the data;to evaluate the quality and relevance of geospatial datasets for use in MSP decisions in Ireland.The process was piloted in the National Marine Planning Framework for Ireland in the development of draft map products;feedback from the public consultation is ongoing and not presented.

STGI:a spatio-temporal grid index model for marine big data

Marine big data are characterized by a large amount and complex structures,which bring great challenges to data management and retrieval.Based on the GeoSOT Grid Code and the composite index structure of the MongoDB database,this paper proposes a spatio-temporal grid index model(STGI)for efficient optimized query of marine big data.A spatio-temporal secondary index is created on the spatial code and time code columns to build a composite index in the MongoDB database used for the storage of massive marine data.Multiple comparative experiments demonstrate that the retrieval efficiency adopting the STGI approach is increased by more than two to three times compared with other index models.Through theoretical analysis and experimental verification,the conclusion could be achieved that the STGI model is quite suitable for retrieving large-scale spatial data with low time frequency,such as marine big data.

A Marine Remote Sensing Spatial Database Engine for Web Publishing

To meet the requirements of efficient management and web publishing for marine remote sensing data, a spatial database engine, named MRSSDE, is designed independently. The logical model, physical model, and optimization method of MRSSDE are discussed in detail. Compared to the ArcSDE, which is the leading product of Spatial Database Engine, the MRSSDE proved to be more effective.

Developing big ocean system in support of Sustainable Development Goals:challenges and countermeasures

The ocean is a critical part of the global ecosystem.The marine ecosystem balance is crucial for human survival and sustainable development.However,due to the impacts of global climate change and human activities,the ocean is rapidly changing,which poses an enormous threat to human health and the econ-omy.“Conserve and sustainably use the oceans,seas and marine resources”is one of the 17 Sustainable Development Goals(SDGs).Therefore,it is urgent to construct a transformative marine scientific solution to promote sustainable development.Marine data is the basis of ocean cognition and governance.Marine science has ush-ered in the era of big data with continuous advances in modern marine data acquisition.While big data provides a large amount of data for SDG research,it simultaneously brings unprecedented challenges.This study introduces an overall framework of a system for solving the current problems faced by marine data serving SDGs from the perspective of marine data management and application.Also,it articulates how the system helps the SDGs through two application cases of managing fragmented marine data and developing global climate change data products.