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Article . 2021 . Peer-reviewed
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Data quality in research data management: a bibliometric study

Authors: Piccolo, Daiane Marcela; Wolf Tadini, Antonio Victor; Teixeira, Heytor Diniz; Botega, Leonardo Castro; Goncalves Sant'Ana, Ricardo Cesar; Santarem Segundo, Jose Eduardo; Vesu Alves, Rachel Cristina;

Data quality in research data management: a bibliometric study

Abstract

A gestão dos dados de pesquisa é reconhecida pela comunidade científica como parte importante das boas práticas de pesquisa. Desta maneira, acredita-se que os mesmos devem estar sempre disponíveis para acesso e reuso. Neste contexto, a curadoria e a qualidade de dados são entendidas como elementos estratégicos. Este trabalho tem como objetivo caracterizar e especificar a produção científica existente sobre o tema “qualidade de dados em gestão de dados de pesquisa”, por meio da aferição de indicadores bibliométricos. Em termos metodológicos, esta pesquisa possui natureza quantitativa e qualitativa, é de tipo exploratória quanto a seus objetivos e utilizasse das bases de dados Web of Science e Scopus para a composição do corpus do estudo bibliométrico. Como resultado, identificou-se, a partir de um corpus de 77 artigos, um período de publicações relevantes entre os anos de 1984 e 2020, sendo o ano de 2019 aquele com mais trabalhos publicados. Adicionalmente, 7 veículos de publicação apresentaram mais de um artigo no tópico pesquisado, sendo os Estados Unidos o país com mais trabalhos publicados, totalizando 34. A área da Ciência da Computação foi a que mais produziu nesse tema e constitui uma tendência em sua interdisciplinaridade com as ciências biológicas, sociais aplicadas e da saúde. Finalmente, conclui-se que, a partir da consciência de que a qualidade de dados é um parâmetro relativo, a implementação de serviços de gestão de dados de pesquisa deve passar por preparação, com foco no atendimento a requisitos como os concernentes ao domínio e aos usos pretendidos.

Research data management is recognized by the scientific community as an important part of best practices in research, so that these data should be available for access and reuse. Within the context of research data management, data curation and data quality are understood as strategic elements. This work aims to characterize and specify the existing scientific production on the theme “data quality in research data management” through the measurement of bibliometric indicators. In methodological terms, this research has a quantitative and qualitative nature, is exploratory in its objectives and uses the Web of Science and Scopus databases to compose the corpus of the bibliometric study. As a result, it was identified from a corpus of 77 articles a period of relevant publications between the years 1984 and 2020, being 2019 the year with more published works. Additionally, 7 publication vehicles presented more than one publication for the researched topic, being the United States the country with more published papers, totaling 34 articles. The area of Computer Science was the one that produced the most on this topic and constitutes a trend in its interdisciplinarity with biological, applied social and health sciences. Finally, we conclude that, based on the awareness that data quality is a relative parameter, the implementation of research data management services must go through preparation, focusing on meeting requirements such as those concerning the domain and the intended uses.

Country
Brazil
Keywords

Dados de pesquisa, Digital curation, Data quality, Research data management, Scientific data, Gestão de dados de pesquisa, Curadoria digital, 001, Dados científicos, Qualidade de dados, Research data

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green