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| Koulouzis, Spiros; Martin, Paul; Zhou, Huan; Hu, Yang; Wang, Junchao; Carval, Thierry; Grenier, Baptiste; Heikkinen, Jani; De Laat, Cees; Zhao, Zhiming. |
| The increasing volume of data being produced, curated, and made available by research infrastructures in the environmental science domain require services that are able to optimize the delivery and staging of data for researchers and other users of scientific data. Specialized data services for managing data life cycle, for creating and delivering data products, and for customized data processing and analysis all play a crucial role in how these research infrastructures serve their communities, and many of these activities are time-critical-needing to be carried out frequently within specific time windows. We describe our experiences identifying the time-critical requirements of environmental scientists making use of computational research support... |
| Tipo: Text |
Palavras-chave: Dynamic Real-Time Infrastructure Planner; E-infrastructure; Research infrastructure; Time-critical services; Virtual research environment. |
| Ano: 2020 |
URL: https://archimer.ifremer.fr/doc/00643/75557/76479.pdf |
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| Quimbert, Erwann; Jeffery, Keith; Martens, Claudia; Martin, Paul; Zhao, Zhiming. |
| After a brief reminder on general concepts used in data cataloguing activities, this chapter provides information concerning the architecture and design recommendations for the implementation of catalogue systems for the ENVRIplus community. The main objective of this catalogue is to offer a unified discovery service allowing cross-disciplinary search and access to data collections coming from Research Infrastructures (RIs). This catalogue focuses on metadata with a coarse level of granularity. It was decided to offer metadata representing different types of dataset series. Only metadata for so-called flagship products (as defined by each community) are covered by the scope of this catalogue. The data collections remain within each RI. For RIs, the aim is... |
| Tipo: Text |
Palavras-chave: Catalogue; Metadata; Data; Interoperability; Standard; ISO; OGC; Format; Schema. |
| Ano: 2020 |
URL: https://archimer.ifremer.fr/doc/00642/75455/76273.pdf |
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| Tanhua, Toste; Pouliquen, Sylvie; Hausman, Jessica; O’brien, Kevin; Bricher, Pip; De Bruin, Taco; Buck, Justin J. H.; Burger, Eugene F.; Carval, Thierry; Casey, Kenneth S.; Diggs, Steve; Giorgetti, Alessandra; Glaves, Helen; Harscoat, Valerie; Kinkade, Danie; Muelbert, Jose H.; Novellino, Antonio; Pfeil, Benjamin; Pulsifer, Peter L.; Van De Putte, Anton; Robinson, Erin; Schaap, Dick; Smirnov, Alexander; Smith, Neville; Snowden, Derrick; Spears, Tobias; Stall, Shelley; Tacoma, Marten; Thijsse, Peter; Tronstad, Stein; Vandenberghe, Thomas; Wengren, Micah; Wyborn, Lesley; Zhao, Zhiming. |
| Well-founded data management systems are of vital importance for ocean observing systems as they ensure that essential data are not only collected but also retained and made accessible for analysis and application by current and future users. Effective data management requires collaboration across activities including observations, metadata and data assembly, quality assurance and control (QA/QC), and data publication that enables local and interoperable discovery and access and secures archiving that guarantees long-term preservation. To achieve this, data should be findable, accessible, interoperable, and reusable (FAIR). Here, we outline how these principles apply to ocean data and illustrate them with a few examples. In recent decades, ocean data... |
| Tipo: Text |
Palavras-chave: FAIR; Ocean; Data management; Data services; Ocean observing; Standardization; Interoperability. |
| Ano: 2019 |
URL: https://archimer.ifremer.fr/doc/00509/62068/66248.pdf |
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| Koulouzis, Spiros; Carval, Thierry; Heikkinen, Jani; Pursula, Antti; Zhao, Zhiming. |
| To perform data-centric research in environmental and earth sciences, researchers need effectively query, select and access data products from different research infrastructures. When providing observation data continuously, infrastructure is expected to create and deliver customised data products, e.g. for specific geo-regions, time durations or observation parameters, to enhance its ability to serve the research communities. Such kind of services often have time-critical requirements; some tasks need to be carried out within specific time windows when the data products are needed for real-time modelling or simulation frameworks. |
| Tipo: Text |
Palavras-chave: Research infrastructure; Data subscription; Cloud computing. |
| Ano: 2020 |
URL: https://archimer.ifremer.fr/doc/00644/75656/76527.pdf |
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