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Dendro: Collaborative Research Data Management Built on Linked Open Data

  • João Rocha da SilvaEmail author
  • João Aguiar Castro
  • Cristina Ribeiro
  • João Correia Lopes
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8798)

Abstract

Research datasets in the so-called “long-tail of science” are easily lost after their primary use. Support for preservation, if available, is hard to fit in the research agenda. Our previous work has provided evidence that dataset creators are motivated to spend time on data description, especially if this also facilitates data exchange within a group or a project. This activity should take place early in the data generation process, when it can be regarded as an actual part of data creation. We present the first prototype of the Dendro platform, designed to help researchers use concepts from domain-specific ontologies to collaboratively describe and share datasets within their groups. Unlike existing solutions, ontologies are used at the core of the data storage and querying layer, enabling users to establish meaningful domain-specific links between data, for any domain. The platform is currently being tested with research groups from the University of Porto.

Notes

Acknowledgements

This work is supported by project NORTE-07-0124-FEDER-000059, 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 Ciêancia 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).

References

  1. 1.
    Castro, J., Ribeiro, C., Rocha, J.: Designing an application profile using qualified dublin core: a case study with fracture mechanics datasets. In: Proceedings of the DC-2013 Conference, pp. 47–52 (2013)Google Scholar
  2. 2.
    Chan, L.: Metadata interoperability and standardization - a study of methodology Part I. D-Lib Mag. 12, 1–34 (2006)Google Scholar
  3. 3.
    Heery, R., Patel, M.: Application profiles: mixing and matching metadata schemas. Ariadne Issue 25, September 2000. http://www.ariadne.ac.uk/issue25/app-profiles/
  4. 4.
    Heidorn, P.B.: Shedding light on the dark data in the long tail of science. Libr. Trends 57(2), 280–299 (2008)CrossRefGoogle Scholar
  5. 5.
    Hodson, S.: ADMIRAL: A Data Management Infrastructure for Research Activities in the Life sciences. University of Oxford, Technical report (2011)Google Scholar
  6. 6.
    Li, Y.-F., Kennedy, G., Ngoran, F., Wu, P.: An ontology-centric architecture for extensible scientific data management systems. Future Gener. Comput. Syst. 29(2), 1–38 (2013)Google Scholar
  7. 7.
    Rocha, J., Barbosa, J., Gouveia, M., Ribeiro, C., Correia Lopes, J.: UPBox and DataNotes: a collaborative data management environment for the long tail of research data. In: iPres 2013 Conference Proceedings (2013)Google Scholar
  8. 8.
    Treloar, A., Wilkinson, R.: Rethinking metadata creation and management in a data-driven research world. In: 2008 IEEE Fourth International Conference on eScience, pp. 782–789, December 2008Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • João Rocha da Silva
    • 1
    Email author
  • João Aguiar Castro
    • 1
  • Cristina Ribeiro
    • 2
  • João Correia Lopes
    • 2
  1. 1.Faculdade de Engenharia da Universidade do Porto/INESC TECPortoPortugal
  2. 2.DEI—Faculdade de Engenharia da Universidade do Porto/INESC TECPortoPortugal

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