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| Foster, Scott D.; Vanhatalo, Jarno; Trenkel, Verena; Schulz, Torsti; Lawrence, Emma; Przeslawski, Rachel; Hosack, Geoffrey R.. |
| Data are currently being used, and reused, in ecological research at an unprecedented rate. To ensure appropriate reuse however, we need to ask the question: “Are aggregated databases currently providing the right information to enable effective and unbiased reuse?” We investigate this question, with a focus on designs that purposefully favour the selection of sampling locations (upweighting the probability of selection of some locations). These designs are common and examples are those designs that have uneven inclusion probabilities or are stratified. We perform a simulation experiment by creating datasets with progressively more uneven inclusion probabilities, and examine the resulting estimates of the average number of individuals per unit area... |
| Tipo: Text |
Palavras-chave: Bias; Survey Design; Database; Population Density Estimate; Model; Horvitz‐Thompson; FAIR; Reuse; Data; Inclusion Probability. |
| Ano: 2021 |
URL: https://archimer.ifremer.fr/doc/00691/80339/83422.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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| Schmidt, Sabine; Maudire, Gilbert; Nys, Cecile; Sudre, Joel; Harscoat, Valerie; Dibarboure, Gérald; Huynh, Frédéric. |
| The past few decades have seen a marked acceleration in the amount of marine observation data derived using both in situ and remote sensing measurements. For example, high-frequency monitoring of key physical-chemical parameters has become an essential tool for assessing natural and human-induced changes in coastal waters as well as their consequences on society. The number and variety of data acquisition techniques require efficient methods of improving data availability. The challenge is to make ocean data available via interoperable portals, which facilitate data sharing according to Findable, Accessible, Interoperable, and Reusable (FAIR) principles for producers and users. Ocean DAta Information and Services (ODATIS) aims to become a unique gateway to... |
| Tipo: Text |
Palavras-chave: Ocean; Data repository; Interoperability; FAIR; Data and service center. |
| Ano: 2020 |
URL: https://archimer.ifremer.fr/doc/00667/77872/80019.pdf |
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