Skip to main content
SpringerLink
Log in

SisGExp: Rethinking Long-Tail Agronomic Experiments

  • Conference paper
  • First Online:
Provenance and Annotation of Data and Processes (IPAW 2016)

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

Included in the following conference series:

Abstract

Reproducibility is a major feature of Science. Even agronomic research of exemplary quality may have irreproducible empirical findings because of random or systematic error. This work presents SisGExp, a provenance-based approach that aid researchers to manage, share, and enact the computational scientific workflows that encapsulate legacy R scripts. SisGExp transparently captures provenance of R scripts and endows experiments reproducibility. SisGExp is non-intrusive, does not require users to change their working way, it wrap agronomic experiments as a scientific workflow system.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Driemeier, C.E., et al.: Data analysis workflow for experiments in sugarcane precision agriculture. In: IEEE 10th International Conference on e-Science, vol. 1, pp. 163–168 (2014). http://doi.org/10.1109/eScience.2014.10

  2. Nascimento, J.A.P., Cruz, S.M.S.: Rflow: uma arquitetura para execução e coleta de proveniência de workflows estatísticos. X Simpósio Brasileiro de Informática na Agricultura, 12pp. (2015). (In Portuguese)

    Google Scholar 

  3. Gandrud, C.: Reproducible Research with R and R Studio, 2nd edn. Chapman and Hall/CRC, Boca Raton (2015)

    MATH  Google Scholar 

  4. McPhillips, T., et al.: YesWorkflow: a user-oriented, language-independent tool for recovering workflow information from scripts. Int. J. Digit. Curation 10(1), 298–313 (2015)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. UFRRJ – Universidade Federal Rural do Rio de Janeiro, Seropédica, Rio de Janeiro, Brazil

    Sergio Manuel Serra da Cruz & José Antonio Pires do Nascimento

Authors
  1. Sergio Manuel Serra da Cruz
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. José Antonio Pires do Nascimento
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sergio Manuel Serra da Cruz .

Editor information

Editors and Affiliations

  1. COPPE/UFRJ, Rio de Janeiro, Brazil

    Marta Mattoso

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

    Boris Glavic

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Manuel Serra da Cruz, S., do Nascimento, J.A.P. (2016). SisGExp: Rethinking Long-Tail Agronomic Experiments. 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_24

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-40593-3_24

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40592-6

  • Online ISBN: 978-3-319-40593-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation