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Enregistrement W2202522780

Global Research and Education Networks: Factors Influencing Network Deployment and Use

2011· article· en· W2202522780 sur OpenAlexaboutno aff
Carleen Maitland

Notice bibliographique

RevueSSRN Electronic Journal · 2011
Typearticle
Langueen
DomaineDecision Sciences
ThématiqueScientific Computing and Data Management
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSoftware deploymentGlobal networkThe InternetTelecommunicationsBroadbandInternet accessComputer scienceBusinessGeographyRegional scienceWorld Wide Web
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

A broad range of computational and network innovations, such as data mining and remote sensing, are becoming integrated into nearly all scientific disciplines. These developments have ushered in an era of global e-Science, characterized by internationally connected scientific communities with remote access to unique scientific equipment and scarce phenomena, and who in some cases form virtual scientific organizations.The networks for global e-science often push the envelope of computational and network technology, as occurred decades ago with the development of the internet. For example, connecting just the astronomical research community to a new high resolution telescope in Chile requires a 10 GB/s link between the site and the U.S. data archive site to enable remote operation and global data access. This link is part of a global network connecting, among others, telescopes from as far south as Antarctica and South Africa to the northern reaches of Russia.The international deployment of broadband infrastructure for e-science raises a variety of challenges. First, it requires the interconnection of national and regional academic research networks, even as these networks themselves are evolving. Second, the interconnection generates a need for joint planning to develop a coherent strategy for what is largely a decentralized global infrastructure. Third, joint planning in turn requires coordination between diverse international public and private entities. Fourth, global e-science requires integration of low income countries with limited network bandwidth.To better understand the international and inter-organizational factors influencing deployment of global academic research networks, this study examines several U.S. based projects. In particular, the research provides insight into important questions, including: 1. Through which mechanisms are international academic network investments carried out? 2. What factors determine the nature of public-private partnerships in these projects? 3. What factors influence the types of access these projects facilitate? 4. What factors influence the outcomes of these deployments?Given the likely influence of national institutional and organizational endowments, the research examines three projects, chosen for their international diversity. The first, the Global Ring Network for Advanced Applications Development (GLORIAD) Project, facilitates network connections primarily in the northern hemisphere and includes partners in the U.S., Russia, China, Korea, Canada, the Netherlands, India, Egypt, Singapore and the Nordic Countries. The second, America’s Lightpaths, ties together the major research networks of the U.S., Brazil, Canada, Chile and Mexico. The third project, Translight, connects U.S. networks with the South Pacific through Hawaii.While these projects vary in terms of their goals, scope and stages of development, they were all partially funded through the U.S. National Science Foundation’s Program on International Research Network Connections and in particular its ‘production network connections and services’ (ProNet) track. This common source of funding enhances their comparability by requiring the projects meet a common set of program goals and requirements . These goals include connecting the largest communities of interest with the broadest range of services, leveraging existing infrastructure, integrating into the existing global network, and promoting a rational global network architecture. The program requirements include a 5 year duration, an explicit services and systems design, plans for operations, monitoring, quality assurance and security, as well as specification for the use of international links, including use policies.The data for this research is collected through publicly available documents and interviews with project managers as well as their domestic and international partners. The findings will 1) provide insight into international academic network services, 2) shed light on the institutional and organizational factors influencing international academic networking, and 3) highlight the role of international public-private partnerships for academic networks in the global network innovation ecosystem.

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 machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,048
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,013
Score d'incertitude au seuil0,029

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,048
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,004
Études des sciences et des technologies0,0020,001
Communication savante0,0040,005
Science ouverte0,0010,003
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0080,001

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.

Tête enseignante Opus0,170
Tête enseignante GPT0,397
Écart entre enseignants0,228 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2011
Routes d'admission1
Résumé présentoui

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