Citação de dados científicos: scoping review

Abstract

<jats:p>Objetivo: Para acompanhar a evolução dos estudos relacionados a dados científicos, investigou-se o significado das citações a eles, buscando responder: 1) Quais as motivações dos pesquisadores para citar dados científicos?; 2) Quais as práticas de citação de dados apresentadas nas áreas cobertas pelo presente estudo?; 3) Quais as análises métricas para citação de dados? Método: Caracteriza-se como pesquisa do tipo qualitativa e descritiva, sendo uma revisão de literatura do tipo Scoping Review, com busca às bases de dados Emerald, LISA, LISTA, Scopus e Web of Science.Resultados: Como motivação, identificaram-se estudos sobre a correlação do incremento de citações às publicações tradicionais ao citarem os dados que as embasavam, muitos confirmaram a correlação, outros não, surgindo também a hipótese de causa comum: qualidade da pesquisa associada a mais recursos. Quanto às práticas, a comunidade está ciente que as citações atuais a dados não estão padronizadas, surgindo a tendência para a adoção de um padrão de citação que atenda às demandas de diferentes tipos de dados. Esta falta de padrão dificulta a análise métrica de citação a dados científicos, que ainda precisa ser explorada em pesquisas, tendo em vista que há uma repetição em utilizar as mesmas técnicas da citação tradicional para essa nova fonte de informação.Conclusões: Promover o avanço da ciência é a principal vantagem em disponibilizar dados, mas existem dificuldades técnicas e de atribuição de crédito que precisam ser enfrentadas em conjunto pelos pesquisadores, instituições, agências de fomento, repositórios de dados e equipes editoriais de publicações.Citação de dados científicos: scoping review</jats:p>

Analysis of right-to-health litigation involving high-cost medicines in Brazil: a scoping review protocol

“…This protocol describes the stages of the methodological framework for conducting a scoping review of studies addressing right to health litigation involving high-cost medicines in Brazil. By using transparent and standardized selection criteria, the framework aims to reduce bias in the study search and selection process (Silveira et al, 2020).…”

Conceptual frameworks used in the evaluation of Telehealth initiatives: A scoping review protocol

“…Scoping review protocols assist in structuring searches and selecting studies used in a scoping review (Silveira et al, 2020), in this case, oriented to provide an expanded identification and understanding of the frameworks applied to Telehealth/Telemedicine. The option for this type of review is justified, instead of a systematic review, as it is expected that studies of quite different designs will be found exploring the topic of interest, allowing a more comprehensive research question to capture a wide range of research and related models.…”

Increasing the equitability of data citation in paleontology: capacity building for the big data future

“…Recognizing the reliance of large data compilations on the many data-producing studies from which they are built, there is a growing consensus that data users should credit data producers in a way that is on par with the credit attributed to traditionally recognized outputs, like peer-reviewed publications (Piwowar and Vision 2013;Altman et al 2015;Penev et al 2017;Cousijn et al 2018;Kaufman et al 2018;Silvello 2018;Zhao et al 2018;Lammey 2019;Pierce et al 2019;Dosso and Silvello 2020). Despite this emerging consensus, the scientific community at large has been slow to adopt the practice of citing data sources, and a common procedure for data citation-used inclusively here to refer to any attribution to data provisioners by data users (e.g., Penev et al 2017;Cousijn et al 2018;Hood and Sutherland 2021; and see "Balancing Data Use and Citation in Paleontology")-remains elusive (Ingwersen and Chavan 2011;Marwick and Birch 2018;Zhao et al 2018;Cousijn et al 2019;Tomaszewski 2019;Silveira et al 2020;Suhr et al 2020). For example, in a review of 600 papers from 12 disciplines (e.g., biology, earth sciences, ecology, and environmental sciences; Zhao et al 2018), when authors used a new or existing dataset in their analysis (n = 312), data attribution was variable: 6% included data citations, 9% used unique identifiers for the data (e.g., DOI), 24% mentioned data with only a database name, and 60% referenced their data using a URL-an imperfect citation, given that URLs can expire.…”

“…Despite this emerging consensus, the scientific community at large has been slow to adopt the practice of citing data sources, and a common procedure for data citation—used inclusively here to refer to any attribution to data provisioners by data users (e.g., Penev et al 2017; Cousijn et al 2018; Hood and Sutherland 2021; and see “Balancing Data Use and Citation in Paleontology”)—remains elusive (Ingwersen and Chavan 2011; Marwick and Birch 2018; Zhao et al 2018; Cousijn et al 2019; Tomaszewski 2019; Silveira et al 2020; Suhr et al 2020). For example, in a review of 600 papers from 12 disciplines (e.g., biology, earth sciences, ecology, and environmental sciences; Zhao et al 2018), when authors used a new or existing dataset in their analysis ( n = 312), data attribution was variable: 6% included data citations, 9% used unique identifiers for the data (e.g., DOI), 24% mentioned data with only a database name, and 60% referenced their data using a URL—an imperfect citation, given that URLs can expire.…”

“…Relatedly, 88% of studies ( n = 100, randomly drawn from 4533 studies) using data compiled by the Global Biodiversity Information Facility failed to appropriately cite the sources of the data they used (Escribano et al 2018). It has become clear that making data citation a standardized practice will require changes at all stages of academic research—from funders, publishers, editorial boards, data repositories, authors submitting analyses of compiled data, researchers producing the data, scientists evaluating each other's work, and all other persons involved in research production (Kaufman et al 2018; Marwick and Birch 2018; Cousijn et al 2019; Colavizza et al 2020; Silveira et al 2020).…”