Ocean observatories and social computing: Potential and progress
Notice bibliographique
Résumé
In December 2009, after years of planning, preparations and extensive infrastructure deployment, the world's first regional-scale underwater ocean observatory was open for business. NEPTUNE Canada opened its instrument network and data archive to free and open access by anyone willing to register for an account. Thus, we have embarked on a journey to transform our observatory into an online platform for collaborative, multidisciplinary e-science. Four main areas of Internet-mediated activity characterize e-science: data provision, analysis & visualization, collaboration and publication. Data provision entails making our large and ever expanding data archive accessible and searchable through the Web. To support online analysis & visualization, tools must be developed, which allow scientists to display and manipulate a wide variety of data products derived from measurements gathered by the various instruments attached to the observatory. Virtual collaboration can be fostered by making it easy for groups of geographically or institutionally separated researchers to design experiments, control instruments, share analyses and discuss conclusions within a shared web-based workspace. Publication and dissemination of research findings can be supported by tools that help researchers manage and contribute to both informal outreach (e.g. blogs) and the iterative review and revision cycles required for formal manuscript authoring. E-science promises some tantalizing advantages over traditional approaches. By providing through-the-web access to a large multivariate data archive, researchers are freed from the burdens of data storage and management. Additionally, the archive can simultaneously serve multiple users at multiple institutions in widely separated locations. Community-driven development of analysis routines allows users to visualize the data using both existing and custom-created code. E-science also encourages higher levels of collaboration, allowing researchers to form virtual teams able to tackle complex problems, where expertise in a variety of disciplines is required. Finally, by opening new avenues for interaction between researchers and students or members of the general public, e-science can influence both the questions scientists choose to address and the scope of their investigations. Transforming the promise of e-science into reality, however, is fraught with both technical and organizational challenges. The sheer volume of data records (50+ Tb/year) and observation density pose significant challenges for observatory and researcher alike, requiring new data mining approaches to be developed. Evolving and sometimes competing data format standards must be grappled with. Questions of data reliability and security must be answered. New protocols for protecting intellectual property within an open data environment must be defined. Ground rules for providing equitable access to finite shared resources (eg. underwater camera control time) must be defined. Cultural, institutional and motivational barriers to distributed decision-making and virtual team coordination must be overcome. NEPTUNE Canada is working to address the many challenges of e-science through a wide range of possible solutions. To help researchers make more optimal use of our large and growing data archives, we are developing a facility that allows users to upload and run custom data analysis routines on NEPTUNE Canada servers. Code authors will be able to retain privacy of over their routines, or if desired, publish their code for sharing and possible additional development with the larger user community. NEPTUNE Canada is developing other tools in the form of web and mobile applications for data search and subscription, event detection, interactive data plotting and real-time collaborative multi-user device control. Other custom tools will give users the ability to search, browse and annotate streaming media, then integrate and compile playlists from multiple sources to produce custom movies. Finally, the "glue" for an effective e-science working environment is under development in the form of web-based facilities to support and encourage project team coordination, communications, collaboration and electronic publication.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».