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Record W2202522780

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

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

Bibliographic record

VenueSSRN Electronic Journal · 2011
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Computing and Data Management
Canadian institutionsnot available
Fundersnot available
KeywordsSoftware deploymentGlobal networkThe InternetTelecommunicationsBroadbandInternet accessComputer scienceBusinessGeographyRegional scienceWorld Wide Web
DOInot available

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.048
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.001
Scholarly communication0.0040.005
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.170
GPT teacher head0.397
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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