Evidence map›Paper›PMID 41464893›Full record

ArticleFoods (Basel, Switzerland)2025

ForestFoodKG: A Structured Dataset and Knowledge Graph for Forest Food Taxonomy and Nutrition.

Rongen Yan, Zhidan Chen, Shengqi Zhou, Guoxing Niu, Yan Li, Zehui Liu, Jun Wang, Xinwan Wu, Qi Luo, Yibin Zhou and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Foods (Basel, Switzerland), 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

15 authors.

Rongen YanSchool of Information Science and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, China.ORCID 0000-0002-5107-4339
Zhidan ChenSchool of Information Science and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, China.
Shengqi ZhouSchool of Landscape Architecture, Beijing Forestry University, Beijing 100083, China.
Guoxing NiuSchool of Information Science and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, China.
Yan LiSchool of Information Science and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, China.
Zehui LiuSchool of Economics & Management, Beijing Forestry University, Beijing 100083, China.
Jun WangCollege of Forestry, Beijing Forestry University, Beijing 100083, China.ORCID 0009-0004-7723-4523
Xinwan WuCollege of Forestry, Beijing Forestry University, Beijing 100083, China.
Qi LuoSchool of Information Science and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, China.
Yibin ZhouSchool of Landscape Architecture, Beijing Forestry University, Beijing 100083, China.
Yanting JinSchool of Information Science and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, China.
Keyan LiuSchool of Landscape Architecture, Beijing Forestry University, Beijing 100083, China.
Weilong YuanSchool of Landscape Architecture, Beijing Forestry University, Beijing 100083, China.
Jingyi XuSchool of Foreign Languages, Beijing Forestry University, Beijing 100083, China.
Fu XuSchool of Information Science and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Forest foods play a vital role in enhancing dietary diversity, human health, and the sustainable use of forest ecosystems. However, structured and machine-readable resources that systematically describe their taxonomic and nutritional attributes remain scarce. To fill this gap, we introduce ForestFoodKG, a comprehensive resource that integrates taxonomic hierarchy and nutritional composition of 1191 forest food items. The resource consists of two components-(i) the ForestFoodKG dataset, containing standardized taxonomic and nutritional records across seven biological levels, and (ii) the ForestFoodKG Knowledge Graph (ForestFoodKG-KG), which semantically links forest food entities using named entity recognition and relation extraction. The constructed graph comprises 4492 entities and 14,130 semantic relations, providing a structured foundation for intelligent querying, nutrition analytics, and ecological informatics. All data were manually verified and made publicly available in CSV format on GitHub. ForestFoodKG serves as the first structured knowledge base for forest foods, promoting data-driven research in nutrition science, sustainable forestry, and knowledge-based decision-making.

Indexed as

dataset constructionforest foodknowledge graphnutritional informationtaxonomy

Identifiers

PMID41464893
PMCPMC12731884

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.