Evidence map›Paper›PMID 40937072›Full record

ArticleOpen research Europe2024

Mapping leadership and communities in EU-funded research through network analysis.

Fabio Morea, Alberto Soraci, Domenico De Stefano

Abstract read
In one paragraph

Article in Open research Europe, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Fabio MoreaArea Science Park, Trieste, Friuli-Venezia Giulia, Italy.ORCID https://orcid.org/0000-0002-2034-2951
Alberto SoraciArea Science Park, Trieste, Friuli-Venezia Giulia, Italy.
Domenico De StefanoUniversita degli Studi di Trieste, Trieste, Friuli-Venezia Giulia, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Horizon 2020 and Horizon Europe are flagship programs of the European Union aimed at supporting research and innovation, fostering collaboration among companies, academic institutions, and research organizations. Comprehensive data on projects, objectives, participants, funding details, and results of Horizon projects is available through the open access portal CORDIS (Community Research and Development Information Service). This paper introduces a novel methodology for utilizing CORDIS data to reveal collaborations, leadership roles, and their evolution over time. Methods: The methodology is based on network analysis. Data is downloaded from the CORDIS portal, enriched, segmented by year and transformed into weighted networks representing collaborations between organizations. Centrality measures are used to assess the influence of individual organizations, while community detection algorithms are used to identify stable collaborations. Temporal analysis tracks the evolution of these roles and communities over time. To ensure robust and reliable results, the methodology addresses challenges such as input-ordering bias and result variability, while the exploration of the solution space enhances the accuracy of identified collaboration patterns. Results: To illustrate the approach, the methodology is applied to a specific case: analyse the evolution of collaborations in hydrogen valleys, in the broader frame of "hydrogen energy" research and innovation projects funded by Horizon programmes. Conclusions: The proposed methodology effectively identifies influential organizations and tracks the stability of research collaborations. The insights gained are valuable for policy-makers and organizations seeking to foster innovation through sustained partnerships. This approach can be extended to other sectors, offering a framework for understanding the impact of EU research funding on collaboration and leadership dynamics.

Indexed as

Community DetectionHorizon 2020Horizon EuropeHydrogenHydrogen ValleyInnovationNetwork Analysis

Identifiers

PMID40937072
PMCPMC12421225

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.