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Design and Implementation of a Data Repository for Collaborative Research: A Pilot Platform for Dataset Management and Continuity: Supporting Sustainable Research Through Structured Data Access and Collaboration
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| 4.55 MB | Adobe PDF |
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Orientador(es)
Resumo(s)
With researchers now putting so much weight on data driven methods, datasets are
becoming fundamental assets that lead the way to innovation. Thus making them
reproducible, collaborative and lasting is a main concern and storing, versioning, and
organizing them should not be taken lightly. This project consists of the design and
development of a centralized data repository application that is suited for academic and
research environments, and gives solutions that are tailored for researcher students. The
platform offers a well-designed, secure and easy-to-use interface to store various research
datasets with a focus on version control, documentation of datasets and role-based access
control. Built using modern web technologies such as NextJS for the backbone of the app,
MongoDB for data storage, and mechanisms for versioning, the application bridges a major
gap between data management practices and the needs of research teams. With making
research processes more transparent and researchers more accountable in mind, this project
introduces primary functions such as dataset metadata tracking, API-based retrieval of the
data, and role controlled access. These tools essentially make the process of documentation
easy while providing an extra layer of security. The thing that is actually interesting about
this project is that it leads our field to reproducible research - which is a big deal in most
contemporary scientific investigations. Combined with the standardization of
documentation, the strength of version tracking, and the safety of the permission scheme,
such a repository offers a good, long-term scaffolding to future collaborations. In a nutshell,
the project provides students with the working tools they need to handle, share, and
develop their data sets more efficiently, encouraging openness, trust, and sharing across
each other.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science
Palavras-chave
Data Management Data Repository Data Reproducibility Centralized Storage Data Sharing SDG 4 - Quality education SDG 9 - Industry, innovation and infrastructure SDG 16 - Peace, justice and strong institutions SDG 17 - Partnerships for the goals