{"title":"Dissemination effect of data papers on scientific datasets","authors":"Hong Jiao, Yuhong Qiu, Xiaowei Ma, Bo Yang","doi":"10.1002/asi.24843","DOIUrl":null,"url":null,"abstract":"<p>Open data as an integral part of the open science movement enhances the openness and sharing of scientific datasets. Nevertheless, the normative utilization of data journals, data papers, scientific datasets, and data citations necessitates further research. This study aims to investigate the citation practices associated with data papers and to explore the role of data papers in disseminating scientific datasets. Dataset accession numbers from NCBI databases were employed to analyze the prevalence of data citations for data papers from PubMed Central. A dataset citation practice identification rule was subsequently established. The findings indicate a consistent growth in the number of biomedical data journals published in recent years, with data papers gaining attention and recognition as both publications and data sources. Although the use of data papers as citation sources for data remains relatively rare, there has been a steady increase in data paper citations for data utilization through formal data citations. Furthermore, the increasing proportion of datasets reported in data papers that are employed for analytical purposes highlights the distinct value of data papers in facilitating the dissemination and reuse of datasets to support novel research.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"75 2","pages":"115-131"},"PeriodicalIF":2.8000,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Association for Information Science and Technology","FirstCategoryId":"91","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/asi.24843","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Open data as an integral part of the open science movement enhances the openness and sharing of scientific datasets. Nevertheless, the normative utilization of data journals, data papers, scientific datasets, and data citations necessitates further research. This study aims to investigate the citation practices associated with data papers and to explore the role of data papers in disseminating scientific datasets. Dataset accession numbers from NCBI databases were employed to analyze the prevalence of data citations for data papers from PubMed Central. A dataset citation practice identification rule was subsequently established. The findings indicate a consistent growth in the number of biomedical data journals published in recent years, with data papers gaining attention and recognition as both publications and data sources. Although the use of data papers as citation sources for data remains relatively rare, there has been a steady increase in data paper citations for data utilization through formal data citations. Furthermore, the increasing proportion of datasets reported in data papers that are employed for analytical purposes highlights the distinct value of data papers in facilitating the dissemination and reuse of datasets to support novel research.
期刊介绍:
The Journal of the Association for Information Science and Technology (JASIST) is a leading international forum for peer-reviewed research in information science. For more than half a century, JASIST has provided intellectual leadership by publishing original research that focuses on the production, discovery, recording, storage, representation, retrieval, presentation, manipulation, dissemination, use, and evaluation of information and on the tools and techniques associated with these processes.
The Journal welcomes rigorous work of an empirical, experimental, ethnographic, conceptual, historical, socio-technical, policy-analytic, or critical-theoretical nature. JASIST also commissions in-depth review articles (“Advances in Information Science”) and reviews of print and other media.