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RESUMO Objetivo: O desenvolvimento tecnológico das últimas décadas tem impulsionado a produção massiva de recursos informacionais e mudanças significativas nos processos de coleta e gestão de dados em praticamente todas as áreas. Tal cenário não é diferente no âmbito científico, onde a coleta e tratamento adequado de dados tem se apresentado como um desafio para pesquisadores. A presente pesquisa teve como objetivo apresentar um protótipo de Web scraper, denominado como ScraperCI, e analisar as potencialidades da utilização de ferramentas computacionais como esta para a coleta em bases de dados disponíveis na Web. Método: A pesquisa caracteriza-se como aplicada, de natureza exploratória e descritiva, com abordagem qualitativa que visa identificar as potencialidades da utilização de Web scrapers no processo de coleta de dados. Resultado: Conclui-se que o protótipo desenvolvido possibilita avanços consideráveis no processo de automação da coleta de dados científicos e que tais ferramentas possibilitam a automatização de processos de recuperação, favorecendo maior produtividade no que tange a extração de recursos informacionais na Web. Conclusões: Espera-se que esta pesquisa possa estimular os profissionais da informação a desenvolver novas competências e enxergar possibilidades inovadoras em suas áreas de atuação profissional, atuando com protagonismo nesse meio interdisciplinar. ABSTRACT Objective: The technological development of the last few decades has driven the massive production of informational resources and significant changes in data collection and management processes in practically all areas. This scenario is no different in the scientific field, where the collection and proper treatment of data has been a challenge for researchers. This research aimed to present a prototype of Web scraper, called ScraperCI, and to analyze the potential of using computational tools as it is for collection in databases available on the Web. Methods: The research is characterized as applied, exploratory and descriptive in nature, with a qualitative approach that aims to identify the potential of using Web scrapers in the data collection process. Results: It is concluded that the developed prototype enables considerable advances in the process of automating the collection of scientific data and that such tools enable the automation of retrieval processes, favoring greater productivity in terms of the extraction of informational resources on the Web. Conclusions: It is hoped that this research can encourage information professionals to develop new skills and see innovative possibilities in their areas of professional activity, acting with protagonism in this interdisciplinary environment.

Data Management Plan is the formal document that describes the data management processes integrating their life cycle. The elaboration of the Data Management Plan assists the researchers and professionals working in the repositories. The objective of this study was to investigate how many and which data repositories of the world's 100 best universities provide Data Management Plans and identify aspects related to possible benefits generated by their use. The methodology was based on documental and exploratory research of a qualitative and quantitative nature. The exploratory methodology was used to survey the universities through the webometrics.info website and its repositories. The results show that only 36 repositories make available Data Management Plans and that their instructions vary depending on the characteristics of the repositories and the data sets deposited in them. It is concluded that its use provides several benefits to all actors involved in data management such as the indication that the data controllers should be mentioned, highlighting the value of the collection work, the maximization of data reuse, the indication of which licenses are assigned to the datasets, which determines how the data is licensed and the forms of data collection, use and guidance on data privacy issues.