Show me the image: a systematic analysis on how results are represented in publications from different fields of biomedical and biological research.

IF 1.1 4区 综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES Anais da Academia Brasileira de Ciencias Pub Date : 2025-03-17 eCollection Date: 2025-01-01 DOI:10.1590/0001-3765202520241023
Mariana P C Cibreiros, Marnie Hillary C Leão, Claudia Mermelstein, Manoel Luis Costa
{"title":"Show me the image: a systematic analysis on how results are represented in publications from different fields of biomedical and biological research.","authors":"Mariana P C Cibreiros, Marnie Hillary C Leão, Claudia Mermelstein, Manoel Luis Costa","doi":"10.1590/0001-3765202520241023","DOIUrl":null,"url":null,"abstract":"<p><p>Figures are essential to convey the main results of scientific articles. Different biomedical research fields have different methodologies and therefore different forms of data representation. To understand whether there are distinct patterns of data representation, we analyzed how results are displayed in scientific publications from six fields: Biochemistry and Cell Biology, Bioinformatics and Computational Biology, Clinical Sciences, Oncology and Carcinogenesis, Pharmacology and Pharmaceutical Sciences, and Zoology. Our results show that Graphics were the most frequent type of representation, followed by Schemes and diagrams. Microscopy was the third most used type of image in most fields, except in Pharmacology and Pharmaceutical Sciences, where Molecules and chemical reactions were the third most frequent. Interestingly, each research field has a characteristic pattern of image. We further classified the image types in primary or secondary data, according to the level of human interference in its construction. Each field has a particular proportion of primary and secondary images. We also analyzed the frequency of words and observed a remarkable vocabulary difference between fields. The most frequent word of each field nicely correlates with the unique type of figures used. Specific fields might gain more visibility for their data by using diverse approaches in image representation.</p>","PeriodicalId":7776,"journal":{"name":"Anais da Academia Brasileira de Ciencias","volume":"97 1","pages":"e20241023"},"PeriodicalIF":1.1000,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Anais da Academia Brasileira de Ciencias","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1590/0001-3765202520241023","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Figures are essential to convey the main results of scientific articles. Different biomedical research fields have different methodologies and therefore different forms of data representation. To understand whether there are distinct patterns of data representation, we analyzed how results are displayed in scientific publications from six fields: Biochemistry and Cell Biology, Bioinformatics and Computational Biology, Clinical Sciences, Oncology and Carcinogenesis, Pharmacology and Pharmaceutical Sciences, and Zoology. Our results show that Graphics were the most frequent type of representation, followed by Schemes and diagrams. Microscopy was the third most used type of image in most fields, except in Pharmacology and Pharmaceutical Sciences, where Molecules and chemical reactions were the third most frequent. Interestingly, each research field has a characteristic pattern of image. We further classified the image types in primary or secondary data, according to the level of human interference in its construction. Each field has a particular proportion of primary and secondary images. We also analyzed the frequency of words and observed a remarkable vocabulary difference between fields. The most frequent word of each field nicely correlates with the unique type of figures used. Specific fields might gain more visibility for their data by using diverse approaches in image representation.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
求助全文
约1分钟内获得全文 去求助
来源期刊
Anais da Academia Brasileira de Ciencias
Anais da Academia Brasileira de Ciencias 综合性期刊-综合性期刊
CiteScore
2.20
自引率
0.00%
发文量
347
审稿时长
1 months
期刊介绍: The Brazilian Academy of Sciences (BAS) publishes its journal, Annals of the Brazilian Academy of Sciences (AABC, in its Brazilianportuguese acronym ), every 3 months, being the oldest journal in Brazil with conkinuous distribukion, daking back to 1929. This scienkihic journal aims to publish the advances in scienkihic research from both Brazilian and foreigner scienkists, who work in the main research centers in the whole world, always looking for excellence. Essenkially a mulkidisciplinary journal, the AABC cover, with both reviews and original researches, the diverse areas represented in the Academy, such as Biology, Physics, Biomedical Sciences, Chemistry, Agrarian Sciences, Engineering, Mathemakics, Social, Health and Earth Sciences.
期刊最新文献
Physiological and oxidative responses of Colossoma macropomum and hybrid ♀ C. macropomum × ♂ Piaractus brachypomus subjected to different stressors in a recirculating aquaculture system (RAS). Probing of MEP1A gene to identify biomarkers associated with post-partum anestrus in buffalo. Relations between sensory quality and spectral indices in brazilian arabica coffees. Revealing the first records of endoparasitic interactions in the non-native fish Moenkhausia costae within a reservoir in Northeastern Brazil. Show me the image: a systematic analysis on how results are represented in publications from different fields of biomedical and biological research.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1