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Provenance-Based Retrieval: Fostering Reuse and Reproducibility Across Scientific Disciplines

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Provenance and Annotation of Data and Processes (IPAW 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9672))

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Abstract

When computational researchers from several domains cooperate, one recurrent problem is finding tools, methods and approaches that can be used across disciplines, to enhance collaboration through reuse. The paper presents our ongoing work to meet the challenges posed by provenance-based retrieval, proposed as a solution for transdisciplinary scientific collaboration via reuse of scientific workflows. Our work is based upon a case study in molecular dynamics experiments, as part of a larger multi-scale experimental scenario.

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Notes

  1. 1.

    http://www.escience.org.br.

  2. 2.

    http://myexperiment.org.

  3. 3.

    http://vcvcomputing.com/provone/provone.html.

  4. 4.

    http://openprovenance.org/model/opmo.

References

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Acknowledgments

Work partially financed by FAPESP (2014/23861-4) and FAPESP/CEPID CCES (2013/08293-7).

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Authors and Affiliations

  1. Institute of Computing, University of Campinas (UNICAMP), Campinas, Brazil

    Lucas Augusto Montalvão Costa Carvalho & Claudia Bauzer Medeiros

  2. Institute of Chemistry, University of Campinas (UNICAMP), Campinas, Brazil

    Rodrigo L. Silveira, Caroline S. Pereira & Munir S. Skaf

Authors
  1. Lucas Augusto Montalvão Costa Carvalho
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  2. Rodrigo L. Silveira
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  3. Caroline S. Pereira
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  4. Munir S. Skaf
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  5. Claudia Bauzer Medeiros
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Corresponding author

Correspondence to Lucas Augusto Montalvão Costa Carvalho .

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Editors and Affiliations

  1. COPPE/UFRJ, Rio de Janeiro, Brazil

    Marta Mattoso

  2. Illinois Institute of Technology, Chicago, Illinois, USA

    Boris Glavic

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© 2016 Springer International Publishing Switzerland

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Carvalho, L.A.M.C., Silveira, R.L., Pereira, C.S., Skaf, M.S., Medeiros, C.B. (2016). Provenance-Based Retrieval: Fostering Reuse and Reproducibility Across Scientific Disciplines. In: Mattoso, M., Glavic, B. (eds) Provenance and Annotation of Data and Processes. IPAW 2016. Lecture Notes in Computer Science(), vol 9672. Springer, Cham. https://doi.org/10.1007/978-3-319-40593-3_17

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  • DOI: https://doi.org/10.1007/978-3-319-40593-3_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40592-6

  • Online ISBN: 978-3-319-40593-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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