Research on Chinese Science Journals Based on DOAJ

Through the study, we explore the development path of open access (OA) in Chinese Science journals based on DOAJ. This article examines the development of Open Access (OA) in Chinese Science journals on DOAJ, using a web-based survey of 86 journals. Data from the DOAJ platform and journal websites were collected and analyzed statistically with EXCEL. Findings indicate that the growth of Chinese Science journals is uneven, with a significant number of journals published in English. Most journals require authors to pay Article Processing Charges (APCs), and only 40.7% offer APC waiver policies. The predominant OA license is CC BY-NC-ND. About 69.77% of journals have a publishing cycle of under 20 weeks, and anonymous peer review is the most common method. Print remains the primary publication format, with few journals having long-term digital preservation or dedicated institutions in China for such preservation. Additionally, there is an imbalance in research themes. Recommendations include increasing the number of OA journals in Chinese Science disciplines and encouraging more Chinese journals to join the DOAJ, waving or reasonably charging APCs, adopting flexible Creative Common Licenses, implementing more rigorous peer review processes, reducing publishing cycles, internationalizing journal formats, and conducting further research on long-term digital preservation and expanding research themes.

Authors

Institutions

Publication Details

Journal
International journal of Asian social science research.
Published
2025-08-03
DOI
https://doi.org/10.70267//ijassr.250203.4858
Primary Topic
Forest, Soil, and Plant Ecology in China
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on Chinese Science Journals Based on DOAJ

Meiping Wang
International journal of Asian social science research.
Forest, Soil, and Plant Ecology in China
article

Research on Chinese Science Journals Based on DOAJ

Meiping Wang
article en

Abstract

Through the study, we explore the development path of open access (OA) in Chinese Science journals based on DOAJ. This article examines the development of Open Access (OA) in Chinese Science journals on DOAJ, using a web-based survey of 86 journals. Data from the DOAJ platform and journal websites were collected and analyzed statistically with EXCEL. Findings indicate that the growth of Chinese Science journals is uneven, with a significant number of journals published in English. Most journals require authors to pay Article Processing Charges (APCs), and only 40.7% offer APC waiver policies. The predominant OA license is CC BY-NC-ND. About 69.77% of journals have a publishing cycle of under 20 weeks, and anonymous peer review is the most common method. Print remains the primary publication format, with few journals having long-term digital preservation or dedicated institutions in China for such preservation. Additionally, there is an imbalance in research themes. Recommendations include increasing the number of OA journals in Chinese Science disciplines and encouraging more Chinese journals to join the DOAJ, waving or reasonably charging APCs, adopting flexible Creative Common Licenses, implementing more rigorous peer review processes, reducing publishing cycles, internationalizing journal formats, and conducting further research on long-term digital preservation and expanding research themes.

International journal of Asian social science research.Vol. 2(3)
Henan Agricultural University (CN)
Openalex Percentile: Top 79%
Forest, Soil, and Plant Ecology in China
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.