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A Model-Driven Approach for Systematic Reproducibility and Replicability of Data Science Projects
11 references·0 citing·41 second hop
A Model-Driven Approach for Systematic Reproducibility and Replicability of Data Science Projects (2022)A Model-Driven Approach for Systematic Re…Trust but Verify: How to Leverage Policies, Workflows, and Infrastructure to Ensure Computational Reproducibility in Publication (2020)Trust but Verify: How to Leve…ml-experiment: A Python framework for reproducible data science (2020)ml-experiment: A Python frame…Improving reproducibility of data science pipelines through transparent provenance capture (2020)Improving reproducibility of …Capturing and querying fine-grained provenance of preprocessing pipelines in data science (2020)Capturing and querying fine-g…Reproducibility and Replicability in Science (2019)Reproducibility and Replicabi…REANA: A System for Reusable Research Data Analyses (2019)REANA: A System for Reusable …State of the Art: Reproducibility in Artificial Intelligence (2018)State of the Art: Reproducibi…Artificial intelligence faces reproducibility crisis (2018)Artificial intelligence faces…Using ReproZip for Reproducibility and Library Services (2017)Using ReproZip for Reproducib…1,500 scientists lift the lid on reproducibility (2016)1,500 scientists lift the lid…Digital education governance: data visualization, predictive analytics, and ‘real-time’ policy instruments (2015)Digital education governance:…A Sociology of monsters: Essays on power, technology, and domination (1991)Sorting Things Out (1999)Big Data, new epistemologies and paradigm shifts (2014)Digital education governance: An introduction (2015)Big data for policymaking: fad or fasttrack? (2017)Pandemic Acceleration: Covid-19 and the emergency digitalization of European education (2021)Provenance and scientific workflows (2008)ReproZip (2016)What does research reproducibility mean? (2016)Believe it or not: how much can we rely on published data on potential drug targets? (2011)Reproducible Research in Computational Science (2011)Redefine statistical significance (2017)Threats of a replication crisis in empirical computer science (2020)Applications of deep learning in stock market prediction: Recent progress (2021)Reproducibility in machine learning for health research: Still a ways to go (2021)Workflow Patterns (2003)Common Workflow Language, draft 3 (2016)Publishing computational research - a review of infrastructures for reproducible and transparent scholarly communication (2020)Scalable Declarative HEP Analysis Workflows for Containerised Compute Clouds (2021)Building Trust in Earth Science Findings through Data Traceability and Results Explainability (2022)VisTrails (2006)Reproducibility vs. Replicability: A Brief History of a Confused Terminology (2018)Data pipeline quality: Influencing factors, root causes of data-related issues, and processing problem areas for developers (2023)Supporting Better Insights of Data Science Pipelines with Fine-grained Provenance (2024)An LLM-guided platform for multi-granular collection and management of data provenance (2025)YesWorkflow: A User-Oriented, Language-Independent Tool for Recovering Workflow Information from Scripts (2015)Big data preprocessing: methods and prospects (2016)Fairness is not static (2020)DLProv: A Data-Centric Support for Deep Learning Workflow Analyses (2024)A manifesto for reproducible science (2017)Bioconda: sustainable and comprehensive software distribution for the life sciences (2018)The nf-core framework for community-curated bioinformatics pipelines (2020)Insights From “The Machine Stops ” to Better Understand Rational Assumptions in Algorithmic Decision Making and Its Implications for Organizations (2019)Artificial intelligence and the conduct of literature reviews (2021)The AI gambit: leveraging artificial intelligence to combat climate change—opportunities, challenges, and recommendations (2021)Challenges for assessing replicability in preclinical cancer biology (2021)Replicability, Robustness, and Reproducibility in Psychological Science (2021)Prevalence of questionable research practices, research misconduct and their potential explanatory factors: A survey among academic researchers in The Netherlands (2022)Comparing containerization-based approaches for reproducible computational modeling of environmental systems (2023)Partnering With Authors to Enhance Reproducibility at JASA (2024)Reproducible research policies and software/data management in scientific computing journals: a survey, discussion, and perspectives (2025)
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References

  • 20161,500 scientists lift the lid on reproducibility4,200 cited
  • 2019Reproducibility and Replicability in Science921 cited
  • 2018Artificial intelligence faces reproducibility crisis567 cited
  • 2015Digital education governance: data visualization, predictive analytics, and ‘real-time’ policy instruments522 cited
  • 2018State of the Art: Reproducibility in Artificial Intelligence292 cited
  • 2019REANA: A System for Reusable Research Data Analyses47 cited
  • 2020Improving reproducibility of data science pipelines through transparent provenance capture43 cited
  • 2020Capturing and querying fine-grained provenance of preprocessing pipelines in data science35 cited
  • 2020Trust but Verify: How to Leverage Policies, Workflows, and Infrastructure to Ensure Computational Reproducibility in Publication28 cited
  • 2017Using ReproZip for Reproducibility and Library Services11 cited
  • 2020ml-experiment: A Python framework for reproducible data science10 cited

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