Nursing research, open science, and data analysis are interconnected concepts. Open Science fosters transparency, collaboration, and accessibility, enabling nursing researchers to effectively share and reuse data while adhering to principles such as reaserch data management. Robust data analytics provide the conditions to improve health outcomes by transforming shared data into actionable insights.
Open Science imposes itself as a vehicle that not only promotes the social and economic impact of science, but also increases the knowledge of the scientific process and the efficiency of research, enhances scientific cooperation and, in this way, contributes decisively to the improvement of the quality of scientific knowledge and to scientific and technological progress based on sharing, contributes to the creation of new areas and research themes and to the reuse of scientific information, and, finally, makes science more inclusive and transparent. Portugal is no exception, and the political commitment to Open Science is clear from instruments such as the Council of Ministers Resolution no. 21/2016, of March 24th, which defined the guiding principles for the implementation of a National Open Science Policy, or the Decree Law no. 63/2019, of May 16th, which determines that R&D institutions should contribute to an Open Science, ensuring free and open access to scientific knowledge and promoting engagement and interaction with society.
A critical component of Open Science is Research Data Management (RDM), which ensures the proper handling, storage, sharing, and preservation of research data throughout a project’s lifecycle. RDM provides a structured approach for managing data by addressing key aspects such as data collection, documentation, metadata, storage, security, sharing, and long-term preservation.
The main thing that a researcher and data analsis needs is the availability of data.In nursing, data analysis is essential because it enables more evidence-based decision-making, identifies trends in patient care, and improves overall healthcare outcomes. Researchers may validate hypotheses, assess treatments, and advance nursing knowledge through data analysis, all of which enhance care practices. data analysis plays a pivotal role in transforming raw data into actionable insights, enabling nurses to base their clinical decisions on solid evidence rather than intuition alone.
Research Data Management (RDM) and data analysis are closely interconnected, as effective RDM provides the
foundation for meaningful and reliable analysis. By ensuring that data are well-documented, organized, and stored in accessible formats, RDM facilitates the preparation of clean and structured datasets essential for analysis. The creation of detailed metadata within RDM offers analysis critical context about data collection and processing, enabling accurate interpretation. Furthermore, RDM supports data integrity and security, ensuring that analyses are based on reliable and unaltered data. By promoting data sharing and reuse, RDM also enhances the potential for secondary and meta-analyses, aligning with Open Science principles to maximize the value of research data and drive impactful, evidence-based insights.
Open Science serves as a powerful catalyst for advancing scientific and technological progress by promoting
transparency, inclusivity, and collaboration. By encouraging the sharing and reuse of scientific information,
Open Science broadens research opportunities, fosters scientific cooperation, and enhances research efficiency,
ultimately amplifying the social and economic impact of science. In Portugal, policies such as the Council of
Ministers Resolution no. 21/2016 and Decree Law no. 63/2019 underscore the country’s commitment to
Open Science by mandating open access to scientific knowledge and societal engagement (1). These initiatives
create a foundation for more equitable and collaborative research practices, enabling the scientific community
to collectively address complex challenges.
The increasing demand of digital data sharing among scientists, has promoted a discussion about research data
management plans. research data management plans may be an emerging tool for researchers to communicate
specific intentions for storing, using, maintaining, and making data assessable to all stakeholders involved.
Research data management (RDM) not only promote transparency and accountability but also ensure
compliance with Open Science policies, facilitating the long-term usability of data (2, 3). Effective RDM
practices are critical for creating structured, well-documented datasets that can be easily shared and reused,
maximizing their value for future research.
Data analysis methods play a pivotal role in harnessing the full potential of data shared under Open Science
policies. By applying robust analytical techniques, researchers can transform open-access data into actionable
insights that drive evidence-based decision-making. In nursing, data analysis is indispensable for validating
hypotheses, evaluating interventions, and identifying care trends, ultimately improving patient outcomes and
advancing nursing knowledge. By integrating Open Science principles with effective RDM and sophisticated
data analysis, the nursing field can leverage shared datasets to generate new knowledge, optimize clinical
practices, and contribute to global healthcare improvements (4).
Awaiting information from the PI
01/05/2025
Em desenvolvimento
Care Systems, Organization, Models, and Technology