Universal Access in the Information Society

, Volume 16, Issue 4, pp 851–862 | Cite as

A comparison of research data management platforms: architecture, flexible metadata and interoperability

  • Ricardo Carvalho AmorimEmail author
  • João Aguiar Castro
  • João Rocha da Silva
  • Cristina Ribeiro
Long paper


Research data management is rapidly becoming a regular concern for researchers, and institutions need to provide them with platforms to support data organization and preparation for publication. Some institutions have adopted institutional repositories as the basis for data deposit, whereas others are experimenting with richer environments for data description, in spite of the diversity of existing workflows. This paper is a synthetic overview of current platforms that can be used for data management purposes. Adopting a pragmatic view on data management, the paper focuses on solutions that can be adopted in the long tail of science, where investments in tools and manpower are modest. First, a broad set of data management platforms is presented—some designed for institutional repositories and digital libraries—to select a short list of the more promising ones for data management. These platforms are compared considering their architecture, support for metadata, existing programming interfaces, as well as their search mechanisms and community acceptance. In this process, the stakeholders’ requirements are also taken into account. The results show that there is still plenty of room for improvement, mainly regarding the specificity of data description in different domains, as well as the potential for integration of the data management platforms with existing research management tools. Nevertheless, depending on the context, some platforms can meet all or part of the stakeholders’ requirements.


Institutional Repository Metadata Schema Metadata Record Open Archival Information System Research Data Management 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work is supported by the Project NORTE-07-0124-FEDER000059, financed by the North Portugal Regional Operational Programme (ON.2-O Novo Norte), under the National Strategic Reference Framework (NSRF), through the European Regional Development Fund (ERDF), and by national funds, through the Portuguese funding agency, Fundação para a Ciência e a Tecnologia (FCT). João Rocha da Silva is also supported by research grant SFRH/BD/77092/2011, provided by the Portuguese funding agency, Fundação para a Ciência e a Tecnologia (FCT).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Ricardo Carvalho Amorim
    • 1
    Email author
  • João Aguiar Castro
    • 1
  • João Rocha da Silva
    • 1
  • Cristina Ribeiro
    • 1
  1. 1.INESC TEC—Faculdade de Engenharia da Universidade do PortoPortoPortugal

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