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Enhancing the Reuse of Scientific Experiments for Agricultural Software Ecosystems

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Abstract

Scientific experiments involve complex interactions between geographically distributed researchers, who act as units and require a substantial volume of data and services. This scenario categorizes a Scientific Software Ecosystem, which involves researchers and scientists working together, using scientific software and related services through scientific workflows. However, to develop scientific workflows, users need suitable platforms to comply with experiment requirements. This paper describes two services designed on top of an open-source E-science Software Ecosystem (E-SECO) platform to support researchers’ activities during the scientific workflow life cycle. Such services focus on data integration and provenance data to support experiment reuse. We conducted two different case studies in a Brazilian Agricultural Research Corporation. Our results show that the proposed platform facilitates the reuse of scientific experiments through data integration in an agriculture context.

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Data Availability

The datasets generated during and/or analyzed during the current study are available on Github at (https://github.com/mateusgon/FeedEfficiencyServiceBase and https://github.com/mateusgon/ProvSe-Service) and also at https://www.dropbox.com/s/wilbaxwkz3f5975/analise%20dos%20dados.xlsx?dl=0. Appendices 1 and 2 present the questionnaires from CS1 and CS2.

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Acknowledgements

We would like to thank the researchers who participated in the evaluation of this proposal, as well as the Brazilian Agricultural Research Corporation (Embrapa/Brazil).

Funding

This work was partially funded by UFJF/Brazil, CAPES/Brazil, CNPq/Brazil (grant: 311595/2019-7), and FAPEMIG/Brazil (grant: APQ-02685-17), (grant: APQ-02194-18).

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Correspondence to Regina Braga.

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Ambrósio, L., Linhares, H., David, J.M.N. et al. Enhancing the Reuse of Scientific Experiments for Agricultural Software Ecosystems. J Grid Computing 19, 44 (2021). https://doi.org/10.1007/s10723-021-09583-x

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