Evidence map›Paper›PMID 39955268›Full record

ArticleScientific data2025

The Water Health Open Knowledge Graph.

Anna Sofia Lippolis, Giorgia Lodi, Andrea Giovanni Nuzzolese

Abstract readDataset
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. Review
  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

3 authors.

Anna Sofia Lippolis *Institute of Cognitive Sciences and Technologies, CNR, Bologna and Rome, Italy. annasofia.lippolis2@unibo.it.ORCID http://orcid.org/0000-0002-0266-3452
Giorgia Lodi *Institute of Cognitive Sciences and Technologies, CNR, Bologna and Rome, Italy. giorgia.lodi@cnr.it.
Andrea Giovanni Nuzzolese *Institute of Cognitive Sciences and Technologies, CNR, Bologna and Rome, Italy. andrea.nuzzolese@cnr.it.

Funding

EC | Connecting Europe Facility (CEF) INEA/CEF/ICT/A2019/206
6 · The paper itself

Abstract

Global sustainability challenges have recently led to an increasing interest in the management of water and health resources. Thus, the availability of effective, meaningful and open data is crucial to address those issues in the broader context of the Sustainable Development Goals of clean water and sanitation as targeted by the United Nations. In this paper, we present the Water Health Open Knowledge Graph (WHOW-KG) along with its design methodology and analysis on impact. Developed in the context of the EU-funded WHOW (Water Health Open Knowledge) project, the WHOW-KG is a semantic knowledge graph that models data on water consumption, pollution, extreme weather events, infectious disease rates and drug distribution. Indeed, it aims at supporting a wide range of applications: from knowledge discovery to decision-making, making it a valuable resource for researchers, policymakers, and practitioners in the water and health domains. The WHOW-KG consists of a network of five ontologies and related linked open data, modelled according to those ontologies. As a fully distributed system, it is sustainable over time, can handle large datasets, and allows data providers full control, establishing it as a vital European asset in the fields of water consumption and pollution.

Indexed as

Water SupplyHumansSustainable Development

Identifiers

PMID39955268
PMCPMC11829977

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.