Evidence map›Paper›PMID 41390533›Full record

ArticleScientific data2025

A Railway Network Dataset Incorporating Multi-Type Train Operation Records and Train Scheduling.

Jianqing Wu, Xukai Xiao, Yitao Zhou, Bo Du, Jun Shen, Yishan Chen, Bi Wang, Qiang Wu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2025. 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

8 authors.

Jianqing Wu *School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, Jiangxi Province, 341000, China.ORCID http://orcid.org/0000-0001-7198-4199
Xukai Xiao *School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, Jiangxi Province, 341000, China.
Yitao ZhouSchool of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, Jiangxi Province, 341000, China.
Bo DuDepartment of Management, Griffith University, Brisbane, QLD, 4111, Australia.
Jun ShenSchool of Computing and Information Technology, University of Wollongong, Wollongong, NSW, 2522, Australia. jshen@uow.edu.au.ORCID http://orcid.org/0000-0002-9403-7140
Yishan ChenSchool of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, Jiangxi Province, 341000, China.
Bi WangSchool of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, Jiangxi Province, 341000, China.
Qiang WuCollaborative Innovation Center for Western Ecological Safety, Lanzhou University, Lanzhou, China.

Funding

National Natural Science Foundation of China (National Science Foundation of China) 62466023
6 · The paper itself

Abstract

Train operation data contains valuable information with potential insights, yet the datasets released by railway companies are often unstandardized or incomplete, limiting their direct applicability in research. Publicly available railway network datasets that comprehensively integrate train operation records with scheduling information remain rare. To support research in large-scale complex networks, dynamic systems, and intelligent transportation systems, we present the Italian Railway Network Dataset. This dataset includes operational records of multiple types of trains, station locations, inter-station mileage, weather conditions, and scheduling data. By providing detailed and structured railway data, our dataset facilitates research in diverse areas such as spatio-temporal pattern mining, network topology analysis, and train delay propagation and distribution. Moreover, it offers valuable support for addressing operational challenges in the railway domain, including timetable optimization, system resilience assessment, and advanced scheduling strategies.

Identifiers

PMID41390533
PMCPMC12827336

What OpenQuestion holds

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LicenceCC BY
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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.