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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 inc...

The ability to access and search metadata for marine science data is both a key requirement for answering fundamental principles of data management (making data Findable, Accessible, Interoperable and Reusable) and also in meeting domain-specific, community defined standards and legislative requirements placed on data publishers. This paper describes a modular data model to answer the functional requirements developed from these drivers and illustrates how this data model can be operationalised. The ability of this solution to meet the FAIR principles is then assessed.

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.

The ability to access and search metadata for marine science data is a key requirement for answering fundamental principles of data management (making data Findable, Accessible, Interoperable and Reusable) and also in meeting domain-specific, community defined standards and legislative requirements placed on data publishers. One of the foundations of effective data management is appropriate metadata cataloguing; the storing and publishing of descriptive metadata for end users to query online. However, with ocean observing systems constantly evolving and the number of autonomous platforms and sensors growing, the volume and variety of data is constantly increasing, therefore metadata catalogue volumes are also expanding. The ability for data catalogue infrastructures to scale with data growth is a necessity, without causing significant additional overhead, in terms of technical infrastructure and financial costs. To address some of these challenges, GitHub and Travis CI offers a potential solution for maintaining scalable data catalogues and hosting a variety of file types, all with minimal overhead costs.GitHub is a repository hosting platform for version control and collaboration, and can be used with documents, computer code, or many file formatsGitHub Pages is a static website hosting service designed to host web pages directly from a GitHub repositoryTravis CI is a hosted, distributed continuous integration service used to build and test projects hosted at GitHub GitHub supports the implementation of a data catalogue as it stores metadata records of different formats in an online repository which is openly accessible and version controlled. The base metadata of the data catalogue in the Marine Institute is ISO 19115/19139 based XML which is in compliance with the INSPIRE implementing rules for metadata. However, using Travis CI, hooks can be provided to build additional metadata records and formats from this base XML, which can also be hosted in the repository. These formats include:DataCite metadata schema - allowing a completed data description entry to be exported in support of the minting of Digital Object Identifiers (DOI) for published dataResource Description Framework (RDF) - as part of the semantic web and linked dataEcological Metadata Language (EML) - for Global Biodiversity Information Facility (GBIF) – which is used to share information about where and when species have been recordedSchema.org XML – which creates a structured data mark-up schema to increase search engine optimisation (SEO)HTML - the standard mark-up language for web pages which can be used to represent the XML as a web pages for end users to view the catalogue online As well as hosting the various file types, GitHub Pages can also render the generated HTML pages as static web pages. This allows users to view and search the catalogue online via a generated static website. The functionality GitHub has to host and version control metadata files, and render them as web pages, allows for an easier and more transparent generation of an online data catalogue while catering for scalability, hosting and security.

Integration of data management systems is a persistent problem in European projects that span multiple agencies. Months, if not years of projects are often expended on the integration of disparate database structures, data types, methodologies and outputs. Moreover, this work is usually confined to a single effort, meaning it is needlessly repeated on subsequent projects. The legacy effect of removing these barriers could therefore yield monetary and time savings for all involved, far beyond a single cross-jurisdictional project. The European Union’s INTERREG VA Programme has funded the COMPASS project to better manage marine protected areas (MPA) in peripheral areas. Involving five organisations, spread across two nations, the project has developed a cross-border network for marine monitoring. Three of those organisations are UK-based and bound for Brexit (the Agri-Food and Biosciences Institute, Marine Scotland Science and the Scottish Association of Marine Science). With that network under construction, significant efforts have been placed on harmonizing data management processes and procedures between the partners. A data management quality management framework (DM-QMF) was introduced to guide this harmonization and ensure adequate quality controls would be enforced. As lead partner on data management, the Irish Marine Institute (MI) initially shared guidelines for infrastructure, architecture and metadata. The implementation of those requirements were then left to the other four partners, with the MI acting as facilitator. This led to the following being generated for each process in the project:Data management plan: Information on how and what data were to be generated as well as where it would be stored. Flow diagrams: Diagrammatic overview of the flow of data through the project. Standard Operating Procedures: Detailed explanatory documents on the precise workings of a process.Data management processes were allowed to evolve naturally out of a need to adhere to this set standard. Organisations were able to work within their operational limitations, without being required to alter their existing procedures, but encouraged to learn from each other. Very quickly it was found that there were similarities in processes, where previously it was thought there were significant differences. This process of sharing data management information has created mutually benefiting synergies and enabled the convergence of procedures within the separate organisations. The downstream data management synergies that COMPASS has produced have already taken effect. Sister INTERREG VA projects, SeaMonitor and MarPAMM, have felt the benefits. The same data management systems cultivated as part of the COMPASS project are being reused, while the groundwork in creating strong cross boundary channels of communication and cooperation are saving significant amounts of time in project coordination.Through data management, personal and institutional relationships have been strengthened, both of which should persist beyond the project terminus in 2021, well into a post-Brexit Europe. The COMPASS project has been an exemplar of how close collaboration can persist and thrive in a changing political environment, in spite of the ongoing uncertainty surrounding Brexit.

Scales and otoliths (ear stones) from fish are routinely sampled for age estimation and stock management purposes. Growth records from scales and otoliths can be used to generate long-term time series data, and in combination with environmental data, can reveal species specific population responses to a changing climate. Additionally, scale and otolith microchemical data can be utilized to investigate fish habitat usage and migration patters. A common problem associated with biological collections, is that while sample intake grows, long-term digital and physical storage is rarely a priority. Material is often collected to meet short-term objectives and resources are seldom committed to maintaining and archiving collections. As a consequence, precious samples are frequently stored in many different and unsuitable locations, and may become lost or separated from associated metadata. The Marine Institute’s ecological research station in Newport, Ireland, holds a multi-decadal (1928-2020) collection of scales and otoliths from various fish species, gathered from many geographic locations. Here we present an open-source database and archiving system to consolidate and digitize this collection, and show how this case study infrastructure could be used for other biological sample collections. The system utilizes the FAIR (Findable Accessible Interoperable and Reusable) open data principals, and includes a physical repository, sample metadata catalogue, and image library.

The ability to access and search metadata for marine science data is a key requirement for answering fundamental principles of data management (making data Findable, Accessible, Interoperable and Reusable) and also in meeting domain-specific, community defined standards and legislative requirements placed on data publishers. Therefore, in the sphere of oceanographic data management, the need for a modular approach to data cataloguing which is designed to meet a number of requirements can be clearly seen. In this paper we describe a data cataloguing system developed at and in use at the Marine Institute, Ireland to meet the needs of legislative requirements including the European Spatial Data Infrastructure (INSPIRE) and the Marine Spatial Planning directive.The data catalogue described here makes use of a metadata model focussed on oceanographic-domain. It comprises a number of key classes which will be described in detail in the paper, but which include:Dataset - combine many different parameters, collected at multiple times and locations, using different instruments Dataset Collection - provides a link between a Dataset Collection Activity and a Dataset, as well as linking to the Device(s) used to sample the environment for a given range of parameters. An example of a Dataset Collection may be the Conductivity-Temperature-Depth profiles taken on a research vessel survey allowing the individual sensors to be connected to the activity and the calibration of those sensors to be connected with the associated measurements. Dataset Collection Activity - a specialised dataset to cover such activities as research vessel cruises; or the deployments of moored buoys at specific locations for given time periods Platform - an entity from which observations may be made, such as a research vessel or a satellite Programme - represents a formally recognized scientific effort receiving significant funding, requiring large scale coordination Device - aimed at providing enough metadata for a given instance of an instrument to provide a skeleton SensorML record Organisation - captures the details of research institutes, data holding centres, monitoring agencies, governmental and private organisations, that are in one way or another engaged in oceanographic and marine research activities, data & information management and/or data acquisition activities The data model makes extensive use of controlled vocabularies to ensure both consistency and interoperability in the content of attribute fields for the Classes outlined above.The data model has been implemented in a module for the Drupal open-source web content management system, and the paper will provide details of this application.

Scales and otoliths (ear stones) from fish are routinely sampled for age estimation and fisheries management purposes. Growth records from scales and otoliths can be used to generate long-term time series data, and in combination with environmental data, can reveal species specific population responses to a changing climate. Additionally, scale and otolith microchemical data can be utilized to investigate fish habitat usage. A common problem associated with biological collections, is that while sample intake grows, long-term physical storage is rarely a priority, and much of the sampling took place before the advent of open-access digital infrastructure. Material is often collected to meet short-term objectives and resources are seldom committed to maintaining and archiving collections. As a consequence, precious samples are frequently stored in many different and unsuitable locations, and may become lost or separated from associated metadata. The Marine Institute's ecological research station in in Newport, Co. Mayo, Ireland, holds a multi-decadal (1928–2020) collection of scales and otoliths from various fish species, gathered from many geographic locations. Here we present an open-source database model and archiving system to consolidate and digitize this collection, and show how this case study infrastructure could be used for other biological sample collections. The system utilizes the FAIR (Findable Accessible Interoperable and Reusable) open-data principles, and includes a physical repository, sample metadata catalogue, and image library.

The oceans play a key role in global issues such as climate change, food security, and human health. Given their vast dimensions and internal complexity, efficient monitoring and predicting of the planet’s ocean must be a collaborative effort of both regional and global scale. A first and foremost requirement for such collaborative ocean observing is the need to follow well-defined and reproducible methods across activities: from strategies for structuring observing systems, sensor deployment and usage, and the generation of data and information products, to ethical and governance aspects when executing ocean observing. To meet the urgent, planet-wide challenges we face, methods across all aspects of ocean observing should be broadly adopted by the ocean community and, where appropriate, should evolve into “Ocean Best Practices.” While many groups have created best practices, they are scattered across the Web or buried in local repositories and many have yet to be digitized. To reduce this fragmentation, we introduce a new open access, permanent, digital repository of best practices documentation (oceanbestpractices.org) that is part of the Ocean Best Practices System (OBPS). The new OBPS provides an opportunity space for the centralized and coordinated improvement of ocean observing methods. The OBPS repository employs user-friendly software to significantly improve discovery and access to methods. The software includes advanced semantic technologies for search capabilities to enhance repository operations. In addition to the repository, the OBPS also includes a peer reviewed journal research topic, a forum for community discussion and a training activity for use of best practices. Together, these components serve to realize a core objective of the OBPS, which is to enable the ocean community to create superior methods for every activity in ocean observing from research to operations to applications that are agreed upon and broadly adopted across communities. Using selected ocean observing examples, we show how the OBPS supports this objective. This paper lays out a future vision of ocean best practices and how OBPS will contribute to improving ocean observing in the decade to come.

Producing new generation of digital public services from open data is of major interest to policymakers, practitioners and academia in the digital government community. Recent efforts in the area of Linked Statistical Data suggest that the associated multidimensional data cubes are excellent resources that could underpin data-driven digital public services. We describe in this paper a set of tools and approach to exploiting linked statistical data produced from the integration of streams of open marine datasets for developing digital services to support Marine Rescue Operations. We also highlight the opportunities enabled through co-creation activities as well as the benefit and challenges for scaling and sustaining the initiative.

In August 2015, a new seafloor observatory was deployed in Galway Bay, Ireland. The sensors on the observatory platform are connected by fibre-optic cable to a shore station, where a broadband connection allows data transfer to the Marine Institute's data centre. This setup involved the development of a new data acquisition system which takes advantage of open source streaming data solutions developed in response to the Big Data paradigm, in particular the Velocity aspect. This activity merges concepts from the arenas of both Big Data and Internet of Things where data standardisation is not normally considered. This paper considers the architecture implemented to stream marine data from instrument to end user and offers suggestions on how to standardise these data streams.

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.

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.

Within the field of ocean science there is a long history of using controlled vocabularies and other Semantic Web techniques to provide a common and easily exchanged description of datasets. As an activity within the European Union, United States, Australian-funded project "Ocean Data Interoperability Platform", a workshop took place in June 2014 at Rensselaer Polytechnic Institute to further the use of these Semantic Web techniques with the aim of producing a set Linked Data publication patterns which describe many parts of a marine science dataset. During the workshop, a Semantic Web development methodology was followed which promoted the use of a team with mixed skills (computer, data and marine science experts) to rapidly prototype a model ontology which could be iterated in the future. In this paper we outline the methodology employed in the workshop, and examine both the technical and sociological outcomes of a workshop of this kind.

The NERC Science Information Strategy Data Citation and Publication project aims to develop and formalise a method for formally citing and publishing the datasets stored in its environmental data centres. It is believed that this will act as an incentive for scientists, who often invest a great deal of effort in creating datasets, to submit their data to a suitable data repository where it can properly be archived and curated. Data citation and publication will also provide a mechanism for data producers to receive credit for their work, thereby encouraging them to share their data more freely., Previously curated at: http://cedadocs.ceda.ac.uk/909/ The publish date on this item was its original published date. This work was funded by: NERC. This item was not refereed before the publication Associated projects: NERC SIS Data Citation and Publication project Main files in this record: IJDC_NERC_datacitation_paper.pdf Item originally deposited with Centre for Environmental Data Analysis (CEDA) document repository by Dr Sarah Callaghan. Transferred to CEDA document repository community on Zenodo on 2022-11-24

12 pages, 3 figures.-- The event model and ontology used within this work is named ef_EARS.owl and can be found at this web address: http://colla.ogs.trieste.it/download/esin, © 2014, Springer-Verlag Berlin Heidelberg. To use data proficiently and efficiently, scientists require comprehensive metadata. This is very difficult to reconstruct conceptually, positionally and temporally far from the time and place of data acquisition. The European Commission funded Eurofleets project, whose mission is to build an integrated European oceanographic research vessel fleet, is developing a system that aims to address this issue by capturing metadata in a uniform way at time of observation. As this is a European-wide initiative, the problems associated with the desired level of integration are also broad. Having so many partners, different paradigms, schools, practices and vocabularies must be taken into consideration. Assuming that this divergence is natural and even somehow positive in the perspective of adapting to a changing environment, we detail how bridging can take place using a systemic approach. In the Eurofleets experience, this relied on the definition of a boundary object: that is an artifact that can be used by each of the diverging communities, since it embeds the core, shared conceptual entities. The structure of the boundary object is based on an event model, its ontology and the controlled vocabularies linked to it. All conceptual entities, and indeed the structure of the boundary object itself, resulted from wide discussions among the divergent communities. These discussions, allowed the extension of meaning from a semantic perspective to the pragmatic scope, where theoretical and cultural matters can also be considered, so that, eventually, the knowledge represented by the boundary object is more likely to be understood across the divergent communities. To exploit the possibilities offered by the boundary object, specific software has been developed that, using the event model and ontology, allows easier deployment across the project partners of a system intended to address the heterogeneity of the research vessel fleet. In this paper we describe in detail the underlying ontology, This work was funded by the European Commission as part of the Seventh Framework Programme (FP7), EUROFLEETS

Where a virtual representation of the Earth must contain data values observed within the physical Earth system, data models are required that allow the integration of data across the silos of various Earth and environmental sciences domains. Creating a mapping between the well-defined terminologies of these silos is a stubborn problem. This paper presents a generalised ontology for use within Web 3.0 services, which builds on European Commission spatial data infrastructure models. The presented ontology acknowledges that there are many complexities to the description of environmental properties which can be observed within the physical Earth system. The ontology is shown to be flexible and robust enough to describe concepts drawn from a range of Earth science disciplines, including ecology, geochemistry, hydrology and oceanography. This paper also demonstrates the alignment and compatibility of the ontology with existing systems and shows applications in which the ontology may be deployed.

Ian McHarg's “The Theory of Creative Fitting” describes the collaborative integration of data into knowledge products for use in ecological architecture developments. In McHarg's system, the provenance of data layers and trust in their creators are vital to the creation of knowledge, ideas recently described as being “urgent and relevant.” This chapter begins with these ideas and explores provenance propagation and data publication. Provenance propagation has been a topic under discussion by the World Wide Web Consortium, while data publication has been a focus of the global marine science community. From these projects, the issue of uniquely identifying individuals in a distributed, collaborative network has emerged. Possible implications of this problem are discussed, as are technical solutions to the problem. The principles described within this chapter are illustrated by examples of uncertainty propagation in chained Web Processing Service networks and data publication activities at the British Oceanographic Data Centre.

This chapter focuses on improved access to marine science data, enabling researchers to generate new information and knowledge products. The history of controlled vocabulary developments in marine sciences, from paper publications to the Semantic Web, is explored in detail. This history is being furthered through the publication of Linked Open Data, meaning: the publication of clearly identifiable entities; a simple, universal mechanism for retrieving resources; a generic graph-based data model; and publishing explicit relationships to other resources. Progress towards Linked Open Data for marine science is reported in this chapter. As shown by the Data-Information-Knowledge ecosystem, the approach of “small pieces of data loosely joined” provides presentation and organisation to data, which creates information. The use of query endpoints to integrate this information from multiple locations into a knowledge base, which required active collaboration between cooperative partners to truly generate new knowledge and to address emerging science questions, is described.

The open service network for marine environmental data (NETMAR) project uses semantic web technologies in its pilot system which aims to allow users to search, download and integrate satellite, in situ and model data from open ocean and coastal areas. The semantic web is an extension of the fundamental ideas of the World Wide Web, building a web of data through annotation of metadata and data with hyperlinked resources. Within the framework of the NETMAR project, an interconnected semantic web resource was developed to aid in data and web service discovery and to validate Open Geospatial Consortium Web Processing Service orchestration. A second semantic resource was developed to support interoperability of coastal web atlases across jurisdictional boundaries. This paper outlines the approach taken to producing the resource registry used within the NETMAR project and demonstrates the use of these semantic resources to support user interactions with systems. Such interconnected semantic resources allow the increased ability to share and disseminate data through the facilitation of interoperability between data providers. The formal representation of geospatial knowledge to advance geospatial interoperability is a growing research area. Tools and methods such as those outlined in this paper have the potential to support these efforts.

Part 2: Information Systems, Information Modelling and Semantics; International audience; netCDF is a well-known and widely used format to exchange array-oriented scientific data such as grids and time-series. We describe a new convention for encoding netCDF based on Linked Data principles called netCDF-LD. netCDF-LD allows metadata elements, given as string values in current netCDF files, to be given as Linked Data objects. netCDF-LD allows precise semantics to be used for elements and expands the type options beyond lists of controlled terms. Using Uniform Resource Identifiers (URIs) for elements allows them to refer to other Linked Data resources for their type and descriptions. This enables improved data discovery through a generic mechanism for element type identification and adds element type expandability to new Linked Data resources as they become available. By following patterns already established for extending existing formats, netCDF-LD applications can take advantage of existing software for processing Linked Data and supporting more effective data discovery and integration across systems.

Linking published scientific results with the data on which they are based has been a growing trend. In some disciplines, such as molecular biology, journals require submission of data to a recognized data center as a condition for publication of the associated article. Data centers, government agencies, and journals have been seeking new ways to link publications and data. The push for transparency of science is also moving most fields of science in this direction. The benefits of publishing data and standardizing their provenance have been documented in several locations [European Union, 2010; Ball and Duke, 2012].

International audience; 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.; Los datos obtenidos por las infraestructuras de oceanografía operacional suponen una posibilidad de análisis significativo de la pesca en cuanto al progreso en la aplicación del Código de Conducta para una Pesca Responsable de la FAO, de 1995. Los productos de datos disponibles para la pesca y la acuicultura satisfacen las necesidades de investigación, para así garantizar la capacidad de cubrir las necesidades de resolución temporal, límites de tiempo de respuesta, frecuencia de notificación, y formatos de interoperabilidad. La existencia de esta legislación y los costes de su ejecución hacen que las actuales infraestructuras de datos se empleen en circunstancias relativamente precarias. Este capítulo presenta una panorámica, que no es exhaustiva pero es reveladora, de lo que se ha logrado sobre datos usados en oceanografía operacional para atender las necesidades de los especialistas en pesca y acuicultura.; Les données requises dans le cadre des infrastructures de l'océanographie opérationnelle désignent la possibilité d'une analyse significative de la pêche pour suivre les progrès accomplis dans la mise en oeuvre du Code de conduite pour une pêche responsable de la FAO, adopté en 1995. Les produits de données de modélisation basés sur la télédétection pour le secteur de la pêche et de l'aquaculture prennent en compte les nécessités de la recherche scientifique, afin d'assurer une capacité de répondre aux exigences d'une meilleure résolution temporelle, des délais fixés pour la réponse, de périodicité des rapports, et de l'interopérabilité des formats. L'existence de cette législation ainsi que des dépens découlant de l'exécution de ses obligations résultent en un usage des infrastructures de données actuelles dans des conditions relativement précaires. Ce chapitre fournit une vue d'ensemble, qu'il faut souligner n'est pas exhaustive mais démonstrative, en vue des résultats obtenus pour chaque indicateur selon la source de données utilisée dans le domaine de l'océanographie opérationnelle pour répondre aux besoins des scientifiques spécialisés dans la pêche et l'aquaculture.