The data management system for the VENUS and NEPTUNE cabled observatories
Notice bibliographique
Résumé
The VENUS (http://venus.uvic.ca/) and NEPTUNE Canada (http://neptunecanada.ca/) cabled ocean observatories have been envisioned from their inception as underwater extensions of the Internet. Having sensors connected to a network opens up tremendous opportunities, from realtime access to sensor measurements to the interactive control of remote assets. Moreover, with a software system in control, data from all sensors can be managed, archived and made available to the wider community. Finally, a data management system can also offer features that are unique to centrally managed instrumentation: thanks to communication standards, autonomous event detection and reaction becomes a very powerful possibility. This talk will summarize the salient features of DMAS (Data Management and Archiving System) that have been implemented over the past four years as well as the planned features to be delivered soon. DMAS consists of two main components: the Data Acquisition Framework (DAF) takes care of the interaction with instruments in terms of control, monitoring as well as data acquisition and storage. The framework also contains operation control tools. The user interaction features include data search and retrieval, data distribution. Current developments in the Web 2.0 area will provide a complete research environment where users will have the ability to work and interact on-line with colleagues, process and visualize data, establish observation schedules and pre-program autonomous, event detection and reaction. We call this environment "Oceans 2.0". The architecture of DMAS is focused on limiting the amount of data loss and maximizing up time. It is a service oriented architecture, making use of some of the more advanced tools available. The code is written in Java and makes use of an enterprise service bus and of the publish-and-subscribe paradigm. The paper also describes the management approaches that were adopted to build DMAS. Good code quality, the continuous support of VENUS and the need for flexibility in dealing with rapidly changing requirements were the drivers behind the adoption of in-house development, the Agile development methodology and the creation of three teams. The development team deals with requirement collection, analysis, design, coding and unit testing; the QA/QC team performs software tests and regression in a production-like environment. The systems/operations team focuses on the hardware and system software preparation and support, receives and installs new code releases after QA approval and monitors systems operations. We are vying to perform new code releases twice a month. The method has worked well during the four years of the system development phase and has allowed for a constant support of VENUS. DMAS will be completed well under budget.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,032 | 0,029 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».