Evidence map›Paper›PMID 40890177›Full record

ArticleScientific data2025

Quantitative datasets of societal value, technology and policy for human-water system modelling.

Shuanglei Wu, Yongping Wei, Jing Wei, Yonglan Xiong, Sarina Huang, Ratri Werdiningtyas, Paulina Genova, Paul Hong, Lin Gan, Chendi Song

Abstract read
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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

10 authors.

Shuanglei WuSchool of Public Policy and Management, Guangxi University, Nanning, 530004, China.ORCID http://orcid.org/0000-0002-0587-9267
Yongping WeiSchool of the Environment, the University of Queensland, Brisbane, 4072, Australia. yongping.wei@uq.edu.au.
Jing WeiDepartment of Hydraulic Engineering, State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing, 100084, China.
Yonglan XiongNational Science Library (Chengdu), Chinese Academy of Science, Chengdu, 610213, China.
Sarina HuangRoom 1704, Building A, Fenglan GuoJi Mall, 32 Xizhimen Street North, Beijing, 100082, China.
Ratri WerdiningtyasUrban and Regional Planning Study Program, Faculty of Engineering, Universitas Sebelas Maret, Ir. Sutami 36 A Kentingan, Surakarta, 57126, Indonesia.
Paulina GenovaWSP Chile and Argentina, Santiago, 7650784, Chile.
Paul HongSchool of the Environment, the University of Queensland, Brisbane, 4072, Australia.
Lin GanSchool of the Environment, the University of Queensland, Brisbane, 4072, Australia.
Chendi SongSchool of the Environment, the University of Queensland, Brisbane, 4072, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Value, technology, and policy are three interactive societal factors affecting the willingness, capacity, and formal rules of human interactions with water. Existing human-water models generally neglect the dynamic and accumulated processes of these factors, failing to explain the societal causes of changes in water practices. Here we developed nine process-based quantitative datasets of Value-Technology-Policy regarding water. They contain 17,003 newspaper articles and 801 public submissions to reflect different water values, 1337 ancient technologies and 40,303 patents for water technologies, and 720 water policy documents at various spatial (national, regional, state, and river basin) and temporal (decades to hundreds of years) scales. A consistent, 4-step content analysis approach was adopted to identify, collect and manually code five key elements (processes) of value, technology and policy: the time ("when"), location ("where"), actor ("who"), theme ("what"), and perspective/tone ("what effects"). Inter-coder reliability tests were conducted to ensure the consistency and validity of the data. These datasets will contribute to more process-oriented understanding of societal factors for improved human-water system modelling in the Anthropocene.

Identifiers

PMID40890177
PMCPMC12402240

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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.