Reproducibility in e-Science: An overview of the related concepts and the most cited support tools
DOI:
https://doi.org/10.5007/1518-2924.2025.e103385Keywords:
Research reproducibility, Data reuse, Research data managementAbstract
Objective: To present concepts related to research reproducibility, such as repeatability and replicability, as well as reuse, and explore how the most cited research support tools in the literature can be used to promote the reproducibility of research in e-Science.
Methods: A bibliographic search was conducted in the Web of Science, Scopus, and Google Scholar databases, along with a document analysis of the manuals of the investigated tools.
Results: Concepts of reproducibility, repeatability, and replicability were presented, with a discussion of their origins, and an exploration of how reuse differs from data use. The literature review also revealed tools that support the development of research in e-Science and promote the reproducibility of scientific research and data reuse, with the four most cited tools were, in order: the source code versioning tool Git Hub, the container tool Docker, the research project management tool Open Science Framework (OSF), and the Jupyter Notebook tool for interactive data processing program descriptions.
Conclusions: Science must go beyond sharing its results through literature; it is necessary to share the artifacts used in research to achieve reproducibility and reuse, concepts that require clear and consensual definitions. These artifacts must be shared with complete and error-free documentation, which is essential for understanding their meaning. For e-Science fields that require computational infrastructure to process large amounts of data, tools are available to facilitate this documentation. The current research context requires that information management teams and data repository managers understand such concepts and tools used by researchers.
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References
ACM. Artifact Review and Badging. [S. l.: s. n.], 2020. Disponível em: https://www.acm.org/publications/policies/artifact-review-and-badging-current. Acesso em: 18 out. 2023.
BAKER, Monya. 1,500 scientists lift the lid on reproducibility. Nature, [s. l.], v. 533, p. 452-454, maio 2016. Disponível em: https://doi.org/10.1038/533452a. Acesso em: 29 abr. 2022. DOI: https://doi.org/10.1038/533452a
BARBA, Lorena A. Terminologies for reproducible research. arXiv. [S. l.: s. n.], 2018. arXiv:1802.03311. Disponível em: https://doi.org/10.48550/arXiv.1802.03311. Acesso em: 28 set. 2023.
BOETTIGER, Carl. An introduction to Docker for reproducible research. ACM SIGOPS Operating Systems Review, [s. l.], v. 49, n. 1, p. 71-79, Jan. 2015. Disponível em: http://doi.acm.org/10.1145/2723872.2723882. Acesso em: 21 fev. 2022. DOI: https://doi.org/10.1145/2723872.2723882
BRINCKMAN, Adam; CHARD, Kyle; GAFFNEY, Niall; HATEGAN, Mihael; JONES, Matthew B.; KOWALIK, Kacper; KULASEKARAN, Sivakumar; LUDÄSCHER, Bertram; MECUM, Bryce D.; NABRZYSKI, Jarek; STODDEN, Victoria; TAYLOR, Ian J.; TURK, Matthew J.; TURNER, Kandace. Computing environments for reproducibility: capturing the “Whole Tale”. Future Generation Computer Systems, [s. l.], v. 94, p. 854-867, 2019. Disponível em: https://doi.org/10.1016/j.future.2017.12.029. Acesso em: 13 jan. 2023. DOI: https://doi.org/10.1016/j.future.2017.12.029
CAREGNATO, Sônia Elisa; ROCHA, Rafael Port da; GABRIEL JUNIOR, Rene Faustino. Reúso de dados: princípios FAIR e o ecossistema de pesquisa. In: SALES, Luana Farias; VEIGA, Viviane dos Santos; HENNING, Patrícia; SAYÃO, Luís Fernando (org.). Princípios FAIR aplicados à gestão de dados de pesquisa. Rio de Janeiro: Ibict, 2021. p. 187-200. Disponível em: https://ridi.ibict.br/bitstream/123456789/1182/2/IBICT_Principios%20FAIR%20aplicados%20a%20gest%C3%A3o%20de%20dados%20de%20pesquisa_2021.pdf. Acesso em: 15 abr. 2023.
CHEIFET, Barbara. Promoting reproducibility with code ocean. Genome Biology, [s. l.], v. 22, n. 1, p. 1-2, 2021. Disponível em: https://doi.org/10.1186/s13059-021-02299-x. Acesso em: 13 jan. 2023. DOI: https://doi.org/10.1186/s13059-021-02299-x
CHEN, Xiaoli; DALLMEIER-TIESSEN, Sünje; DASLER, Robin; FEGER, Sebastian; FOKIANOS, Pamfilos; GONZALEZ, Jose Benito; HIRVONSALO, Harri; KOUSIDIS, Dinos; LAVASA, Artemis; MELE, Salvatore; RODRIGUEZ, Diego Rodriguez; ŠIMKO, Tibor; SMITH, Tim; TRISOVIC, Ana; TRZCINSKA, Anna; TSANAKTSIDIS, Ioannis; ZIMMERMANN, Markus; CRANMER, Kyle; HEINRICH, Lukas; WATTS, Gordon; HILDRETH, Michael; IGLESIAS, Lara Lloret; LASSILA-PERINI, Kati; NEUBERT, Sebastian. Open is not enough. Nature Physics, [s. l.], v. 15, p. 113-119, Feb. 2019. Disponível em: https://doi.org/10.1038/s41567-018-0342-2. Acesso em: 24 maio 2022. DOI: https://doi.org/10.1038/s41567-018-0342-2
CITO, Jürgen; GALL, Harald C. Using Docker Containers to improve reproducibility in software engineering research. In: IEEE/ACM INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING COMPANION (ICSE-C), 38., 2016, Austin, TX, USA. Proceedings […]. Austin: IEEE, 2016. p. 906-907. Disponível em: http://dx.doi.org/10.1145/2889160.2891057. Acesso em: 12 maio 2025. DOI: https://doi.org/10.1145/2889160.2891057
CLAERBOUT, Jon F.; KARRENBACH, Martin. Electronic documents give reproducible research a new meaning. In: SEG TECHNICAL PROGRAM EXPANDED, 1992, [s. l.]. Abstracts […]. [S. l.]: Society of Exploration Geophysicists, 1992. p. 601-604. Disponível em: https://doi.org/10.1190/1.1822162. Acesso em: 28 nov. 2023. DOI: https://doi.org/10.1190/1.1822162
FASEB. Enhancing research reproducibility. Bethesda: FASEB, 2016. Disponível em: https://www.faseb.org/FASEB/media/PDF/News/Washington%20Update/FASEB_Enhancing-Research-Reproducibility_1.pdf. Acesso em: 23 nov. 2023.
FEGER, Sebastian Stefan; WOŹNIAK, Paweł W.; NIESS, Jasmin; SCHMIDT, Albrecht. Tailored science badges: enabling new forms of research interaction. In: ACM DESIGNING INTERACTIVE SYSTEMS CONFERENCE, 21., 2021, New York. Proceedings […]. New York: Association for Computing Machinery, 2021. p. 576-588. Disponível em: https://doi.org/10.1145/3461778.3462067. Acesso em: 03 jan. 2022. DOI: https://doi.org/10.1145/3461778.3462067
FIGUEIREDO FILHO, Dalson; LINS, Rodrigo; DOMINGOS, Amanda; JANZ, Nicole; SILVA, Lucas. Seven reasons why: a user’s guide to transparency and reproducibility. Brazilian Political Science Review, [s. n.], v. 13, n. 2, e0001, 2019. Disponível em: https://doi.org/10.1590/1981-3821201900020001. Acesso em: 20 nov. 2023. DOI: https://doi.org/10.1590/1981-3821201900020001
GOODMAN, Steven N.; FANELLI, Daniele; IOANNIDIS, John P. A. What does research reproducibility mean? Science translational medicine, [s. n.], v. 8, n. 341, p. 341ps12-341ps12, 2016. Disponível em: https://doi.org/10.1126/scitranslmed.aaf5027. Acesso em: 12 set. 2023. DOI: https://doi.org/10.1126/scitranslmed.aaf5027
HARZING, Anne-Wil. Publish or perish. Versão 8.8.4384, 2021. Software. Disponível em: https://harzing.com/resources/publish-or-perish/command-line. Acesso em: 23 fev. 2023.
HERNÁNDEZ, José Armando; COLOM, Miguel. Repeatability, Reproducibility, replicability, reusability (4R) in Journals' Policies and Software/Data Management in Scientific Publications: a survey, discussion, and perspectives. arXiv. [S. l.: s. n.], 2023. arXiv:2312.11028. Disponível em: https://doi.org/10.48550/arXiv.2312.11028. Acesso em: 13 mar. 2024.
MALIK, Tanu. Reproducible eScience: the data containerization challenge. In: IEEE INTERNATIONAL CONFERENCE ON E-SCIENCE (E-SCIENCE), 19., 2023, Limassol. Proceeedings [...]. Limassol: IEEE, 2023. p. 1-5. Disponível em: https://doi.org/10.1109/e-Science58273.2023.10254837. Acesso em: 9 out. 2023. DOI: https://doi.org/10.1109/e-Science58273.2023.10254837
MOREAU, David; WIEBELS, Kristina; BOETTIGER, Carl. Containers for computational reproducibility. Nature Reviews Methods Primers, [s. n.], v. 3, n. 1, p. 1-16, 2023. Disponível em: https://doi.org/10.1038/s43586-023-00236-9. Acesso em: 9 set. 2023. DOI: https://doi.org/10.1038/s43586-023-00236-9
MOUAT, Adrian. Using docker: developing and deploying software with containers. Boston: O’Reilly, 2016. Disponível em: https://books.google.com.br/books?hl=pt-BR&lr=&id=wpYpCwAAQBAJ&oi=fnd&pg=PP1&dq=container+history+docker&ots=QhL5yLnT9Q&sig=7PVD3sSBTX9ab0gIq5lrMIqkVps#v=onepage&q&f=false. Acesso em: 20 nov. 2022.
MUNAFÒ, Marcus R.; NOSEK, Brian A.; BISHOP, Dorothy V. M.; BUTTON, Katherine S.; CHAMBERS, Christopher D.; PERCIE DU SERT, Nathalie; SIMONSOHN, Uri; WAGENMAKERS, Eric-Jan; WARE, Jennifer J.; IOANNIDIS, John P. A. A manifesto for reproducible science. Nature human behaviour, [s. n.], v. 1, n. 1, p. 1-9, 2017. Disponível em: http://dx.doi.org/10.1038/s41562-016-0021. Acesso em: 29 fev. 2024. DOI: https://doi.org/10.1038/s41562-016-0021
NATIONAL ACADEMIES OF SCIENCES, ENGINEERING, AND MEDICINE. Reproducibility and replicability in science. Washington: The National Academies Press, 2019. Disponível em: https://doi.org/10.17226/25303. Acesso em: 23 nov. 2023. DOI: https://doi.org/10.17226/25303
PASQUETTO, Irene V.; RANDLES, Bernadette M.; BORGMAN, Christine L. On the reuse of scientific data. Data Science Journal, [s. n.], v. 16, n. 8, p. 1-9, 2017. Disponível em: https://doi.org/10.5334/dsj-2017-008. Acesso em: 15 abr. 2023. DOI: https://doi.org/10.5334/dsj-2017-008
PENG, Roger D.; DOMINICI, Francesca; ZEGER, Scott L. Reproducible epidemiologic research. American Journal of Epidemiology, [s. n.], v. 163, n. 9, p. 783-789, 2006. Disponível em: https://doi.org/10.1093/aje/kwj093. Acesso em: 20 nov. 2023. DOI: https://doi.org/10.1093/aje/kwj093
PENG, Roger D.; HICKS, Stephanie. C. Reproducible research: a retrospective. Annual Review of Public Health, [s. n.], v. 42. p. 79-93, 2021. Disponível em: https://doi.org/10.1146/annurev-publhealth-012420-105110. Acesso em: 24 abr. 2022. DOI: https://doi.org/10.1146/annurev-publhealth-012420-105110
PEREZ-RIVEROL, Yasset; GATTO, Laurent; WANG, Rui; SACHSENBERG, Timo; USZKOREIT, Julian; LEPREVOST, Felipe da Veiga; FUFEZAN, Christian; TERNENT, Tobias; EGLEN, Stephen J.; KATZ, Daniel S.; POLLARD, Tom J.; KONOVALOV, Alexander; FLIGHT, Robert M.; BLIN, Kai; VIZCAÍNO, Juan Antonio. Ten simple rules for taking advantage of Git and GitHub. PLoS Computational Biology, [s. n.], v. 12, n. 7, e1004947, 2016. Disponível em: https://doi.org/10.1371/journal.pcbi.1007142. Acesso em: 15 nov. 2023. DOI: https://doi.org/10.1371/journal.pcbi.1004947
POTTERBUSCH, Megan; LOTRECCHIANO, G. R. Shifting paradigms in information flow: an open science framework (OSF) for knowledge sharing teams. Informing Science, [s. n.], v. 21, p. 179, 2018. Disponível em: https://doi.org/10.28945/4031. Acesso em: 14 jan. 2023. DOI: https://doi.org/10.28945/4031
ROUGIER, Nicolas P.; HINSEN, Konrad; ALEXANDRE, Frédéric; ARILDSEN, Thomas; BARBA, Lorena A.; BENUREAU, Fabien C.Y.; BROWN, C. Titus; DE BUYL, Pierre; CAGLAYAN, Ozan; DAVISON, Andrew P.; DELSUC, Marc-André; DETORAKIS, Georgios; DIEM, Alexandra K.; DRIX, Damien; ENEL, Pierre; GIRARD, Benoît; GUEST, Olivia; HALL, Matt G.; HENRIQUES, Rafael N.; HINAUT, Xavier; JARON, Kamil S.; KHAMASSI, Mehdi; KLEIN, Almar; MANNINEN, Tiina; MARCHESI, Pietro; MCGLINN, Daniel; METZNER, Christoph; PETCHEY, Owen; PLESSER, Hans Ekkehard; POISOT, Timothée; RAM, Karthik; RAM, Yoav; ROESCH, Etienne; ROSSANT, Cyrille; ROSTAMI, Vahid; SHIFMAN, Aaron; STACHELEK, Jemma; STIMBERG, Marcel; STOLLMEIER, Frank; VAGGI, Federico; VIEJO, Guillaume; VITAY, Julien; VOSTINAR, Anya E.; YURCHAK, Roman; ZITO, Tiziano. Sustainable computational science: the ReScience initiative. PeerJ Computer Science, [s. n.], v. 3, e142, 2017. Disponível em: https://doi.org/10.7717/peerj-cs.142. Acesso em 23 nov. 2023. DOI: https://doi.org/10.7717/peerj-cs.142
SAYÃO, Luis F.; SALES, Luana F. Dados abertos de pesquisa: ampliando o conceito de acesso livre. RECIIS, Rio de Janeiro, v. 8, n. 2, p. 76-92, jun. 2014. Disponível em: https://www.arca.fiocruz.br/handle/icict/17102. Acesso em: 21 fev. 2022.
SCHAEFER, B.; CAMPOS, L. A.; CANDIDO, M. R. Revista DADOS cria editoria especializada em replicabilidade. In: SCIELO. SciELO em Perspectiva, 20 out. 2023. Disponível em: https://blog.scielo.org/blog/2023/10/20/revista-dados-cria-editoria-especializada-em-replicabilidade/. Acesso em: 05 fev. 2025.
TRISOVIC, Ana; DURBIN, Philip; SCHLATTER, Tania; DURAND, Gustavo; BARBOSA, Sonia; BROOKE, Danny; CROSAS, Mercê. Advancing computational reproducibility in the dataverse data repository platform. In: INTERNATIONAL WORKSHOP ON PRACTICAL REPRODUCIBLE EVALUATION OF COMPUTER SYSTEMS, 3., 2020, Stockholm. Proceedings […]. New York: Association for Computing Machinery, 2020. p. 15–20. Disponível em: https://doi.org/10.1145/3391800.3398173. Acesso em: 8 jun. 2022. DOI: https://doi.org/10.1145/3391800.3398173
UNESCO. Recommendation on open science. [S.l.: s.n.], 2021. Disponível em: https://unesdoc.unesco.org/ark:/48223/pf0000379949.locale=en. Acesso em: 27 maio 2024.
VAN DE SANDT, Stephanie; DALLMEIER-TIESSEN, Sünje; LAVASA, Artemis; PETRAS, Vivien. The definition of reuse. Data Science Journal, [s. l.], v. 18, n. 1, p. 1–19, 2019. Disponível em: http://dx.doi.org/10.5334/dsj-2019-022. Acesso em: 28 nov. 2022. DOI: https://doi.org/10.5334/dsj-2019-022
VANZ, Samile Andrea de Souza; PAVÃO, Caterina Marta Groposo; CAREGNATO, Sônia Elisa; PASSOS, Paula Caroline Schifino Jardim; MOURA, Ana Maria Mielniczuk de; BORGES, Eduardo Nunes; GABRIEL JUNIOR, Rene Faustino; ROCHA, Rafael Port da. Diretrizes para o estabelecimento de um checklist para curadoria de dados de pesquisa. Informação em Pauta, [s. l.], v. 6, n. 00, p. 1-18, 26 out. 2021. Disponível em: http://www.periodicos.ufc.br/informacaoempauta/article/view/68088/197501. Acesso em: 22 out. 2022
WILKINSON, Mark D.; DUMONTIER, Michel; AALBERSBERG, IJsbrand Jan; APPLETON, Gabrielle; AXTON, Myles; BAAK, Arie; BLOMBERG, Niklas; BOITEN, Jan-Willem; BONINO DA SILVA SANTOS, Luiz; BOURNE, Philip E.; BOUWMAN, Jildau; BROOKES, Anthony J.; CLARK, Tim; CROSAS, Mercè; DILLO, Ingrid; DUMON, Olivier; EDMUNDS, Scott; EVELO, Chris T.; FINKERS, Richard; GONZALEZ-BELTRAN, Alejandra; GRAY, Alasdair J.G.; GROTH, Paul; GOBLE, Carole; GRETHE, Jeffrey S.; HERINGA, Jaap; ’T HOEN, Peter A.C.; HOOFT, Rob; KUHN, Tobias; KOK, Ruben; KOK, Joost; LUSHER, Scott J.; MARTONE, Maryann E.; MONS, Albert; PACKER, Abel L.; PERSSON, Bengt; ROCCA-SERRA, Philippe; ROOS, Marco; VAN SCHAIK, Rene; SANSONE, Susanna-Assunta; SCHULTES, Erik; SENGSTAG, Thierry; SLATER, Ted; STRAWN, George; SWERTZ, Morris A.; THOMPSON, Mark; VAN DER LEI, Johan; VAN MULLIGEN, Erik; VELTEROP, Jan; WAAGMEESTER, Andra; WITTENBURG, Peter; WOLSTENCROFT, Katherine; ZHAO, Jun; MONS, Barend. Comments: The FAIR Guiding Principles for scientific data management and stewardshi. Scientific Data, [s. l.], v. 3, n. 160018, Mar. 2016. Disponível em: https://doi.org/10.1038/sdata.2016.18. Acesso em: 21 fev. 2022. DOI: https://doi.org/10.1038/sdata.2016.18
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