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Using ReproZip for Reproducibility and Library Services
8 references·1 citing·36 second hop
Using ReproZip for Reproducibility and Library Services (2017)Using ReproZip for Reproducibility and Li…Challenges Facing the Preservation of Born-Digital News Applications (2017)Challenges Facing the Preserv…What does research reproducibility mean? (2016)What does research reproducib…ReproZip (2016)ReproZipUsing provenance for repeatability (2013)Using provenance for repeatab…Enhancing reproducibility (2013)Enhancing reproducibilityMaking Computations and Publications Reproducible with VisTrails (2012)Making Computations and Publi…Saving Second Life: Issues in Archiving a Complex, Multi-User Virtual World (2011)Saving Second Life: Issues in…Provenance and scientific workflows (2008)Provenance and scientific wor…A Model-Driven Approach for Systematic Reproducibility and Replicability of Data Science Projects (2022)A Model-Driven Approach for S…Provenance for Visualizations: Reproducibility and Beyond (2007)Provenance for Computational Tasks: A Survey (2008)Reproducible Research in Computational Harmonic Analysis (2008)A Minimum Standard for Publishing Computational Results in the Weather and Climate Sciences (2015)Embedding data provenance into the Learning Health System to facilitate reproducible research (2016)Reproducibility Using VisTrails (2018)Workflow mining: discovering process models from event logs (2004)A survey of data provenance in e-science (2005)Scientific workflow management and the Kepler system (2005)Artifact-Centric Business Process Models: Brief Survey of Research Results and Challenges (2008)The Open Provenance Model: An Overview (2008)A survey on provenance: What for? What form? What from? (2017)The Open Provenance Model core specification (v1.1) (2010)Computational reproducibility (2012)An invariant framework for conducting reproducible computational science (2015)Utilizing Provenance in Reusable Research Objects (2018)Reproducible Notebook Containers using Application Virtualization (2022)Policy: NIH plans to enhance reproducibility (2014)The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update (2016)A solution to minimum sample size for regressions (2020)CONSORT 2025 statement: updated guideline for reporting randomised trials (2025)CONSORT 2025 statement: updated guideline for reporting randomised trials (2025)Reproducible research in signal processing (2009)How scientists fool themselves – and how they can stop (2015)The Sacred Infrastructure for Computational Research (2017)Sharing interoperable workflow provenance: A review of best practices and their practical application in CWLProv (2019)Reproducibility in machine‐learning‐based research: Overview, barriers, and drivers (2025)Plans to save born-digital news content examined (2015)1,500 scientists lift the lid on reproducibility (2016)Artificial intelligence faces reproducibility crisis (2018)Reproducibility and Replicability in Science (2019)Fleeting Film: Using Story to Seek Archival Permanence in the Transitory and Globalized Digital Visual Effects Industry (2018)Transcoding authenticity: preserving unreleased gaming software outside of memory institutions (2021)Advancements in RNASeqGUI towards a Reproducible Analysis of RNA-Seq Experiments (2016)Enhancing reproducibility: Failures from Reproducibility Initiatives underline core challenges (2017)How measurement science can improve confidence in research results (2018)
this work references cited by second hop

References

  • 2016What does research reproducibility mean?1,291 cited
  • 2008Provenance and scientific workflows470 cited
  • 2016ReproZip128 cited
  • 2012Making Computations and Publications Reproducible with VisTrails65 cited
  • 2013Enhancing reproducibility37 cited
  • 2013Using provenance for repeatability34 cited
  • 2011Saving Second Life: Issues in Archiving a Complex, Multi-User Virtual World10 cited
  • 2017Challenges Facing the Preservation of Born-Digital News Applications3 cited

Cited by

  • 2022A Model-Driven Approach for Systematic Reproducibility and Replicability of Data Science Projects8 cited

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