SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Ten simple rules for writing and sharing computational analyses in Jupyter Notebooks
8 references·16 citing·36 second hop
Ten simple rules for writing and sharing computational analyses in Jupyter Notebooks (2019)Ten simple rules for writing and sharing …Exploration and Explanation in Computational Notebooks (2018)Exploration and Explanation i…Binder 2.0 - Reproducible, interactive, sharable environments for science at scale (2018)Binder 2.0 - Reproducible, in…Good enough practices in scientific computing. (2017)Good enough practices in scie…Ten Simple Rules for Taking Advantage of Git and GitHub (2016)Ten Simple Rules for Taking A…Positioning and Power in Academic Publishing: Players, Agents and Agendas (2016)Positioning and Power in Acad…Jupyter Notebooks – a publishing format for reproducible computational workflows (2016)Jupyter Notebooks – a publish…Ten Simple Rules for Reproducible Computational Research (2013)Ten Simple Rules for Reproduc…Reproducible Research in Computational Science (2011)Reproducible Research in Comp…Toward open science in marketing research (2024)Toward open science in market…Computational reproducibility of Jupyter notebooks from biomedical publications (2024)Computational reproducibility…The five pillars of computational reproducibility: bioinformatics and beyond (2023)The five pillars of computati…Developing and reusing bioinformatics data analysis pipelines using scientific workflow systems (2023)Developing and reusing bioinf…Eliciting Best Practices for Collaboration with Computational Notebooks (2022)Eliciting Best Practices for …Advancing code sharing in the computational biology community (2022)Advancing code sharing in the…Using Jupyter for Reproducible Scientific Workflows (2021)Using Jupyter for Reproducibl…Ten simple rules to cultivate transdisciplinary collaboration in data science (2021)Ten simple rules to cultivate…Open data products-A framework for creating valuable analysis ready data (2021)Open data products-A framewor…A Reproducible Data Analysis Workflow (2021)A Reproducible Data Analysis …The Design Space of Computational Notebooks: An Analysis of 60 Systems in Academia and Industry (2020)The Design Space of Computati…Ten simple rules for writing Dockerfiles for reproducible data science (2020)Ten simple rules for writing …Practical Reproducibility in Geography and Geosciences (2020)Practical Reproducibility in …Keeping modelling notebooks with TRACE: Good for you and good for environmental research and management support (2020)Keeping modelling notebooks w…Improving reproducibility in computational biology research (2020)Improving reproducibility in …Assessing and restoring reproducibility of Jupyter notebooks (2020)Assessing and restoring repro…Taverna: a tool for the composition and enactment of bioinformatics workflows (2004)Galaxy: A platform for interactive large-scale genome analysis (2005)Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences (2010)Preferred reporting items for systematic reviews and meta‐analyses in ecology and evolutionary biology: a PRISMA extension (2021)WaveLab and Reproducible Research (1995)Git can facilitate greater reproducibility and increased transparency in science (2013)Four simple recommendations to encourage best practices in research software (2017)Toward standard practices for sharing computer code and programs in neuroscience (2017)Heterogeneous green innovations and carbon emission performance: Evidence at China's city level (2021)The WyCash portfolio management system (1992)Does high public debt consistently stifle economic growth? A critique of Reinhart and Rogoff (2013)A Large-Scale Study About Quality and Reproducibility of Jupyter Notebooks (2019)Human-AI Collaboration in Data Science (2019)What's Wrong with Computational Notebooks? Pain Points, Needs, and Design Opportunities (2020)Statistical Analyses and Reproducible Research (2007)1,500 scientists lift the lid on reproducibility (2016)Appyters: Turning Jupyter Notebooks into data-driven web apps (2021)A large-scale study on research code quality and execution (2022)The magical number seven, plus or minus two: Some limits on our capacity for processing information. (1956)The magical number seven, plus or minus two: Some limits on our capacity for processing information. (1994)Our path to better science in less time using open data science tools (2017)Identifying and Overcoming Threats to Reproducibility, Replicability, Robustness, and Generalizability in Microbiome Research (2018)An introduction to Docker for reproducible research (2015)Singularity: Scientific containers for mobility of compute (2017)Consensus-based guidance for conducting and reporting multi-analyst studies (2021)Containers for computational reproducibility (2023)Increasing value and reducing waste in research design, conduct, and analysis (2014)Reproducibility in Science (2014)Open science challenges, benefits and tips in early career and beyond (2019)The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2020 update (2020)NeuroKit2: A Python toolbox for neurophysiological signal processing (2021)KBase: The United States Department of Energy Systems Biology Knowledgebase (2018)Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2 (2019)Topic Modeling in Management Research: Rendering New Theory from Textual Data (2019)Means to valuable exploration II: How to explore data to modify existing claims and create new ones (2023)Corpus-based discourse analysis: from meta-reflection to accountability (2024)
this work references cited by second hop

References

  • 2016Jupyter Notebooks – a publishing format for reproducible computational workflows3,069 cited
  • 2011Reproducible Research in Computational Science1,446 cited
  • 2016Positioning and Power in Academic Publishing: Players, Agents and Agendas935 cited
  • 2013Ten Simple Rules for Reproducible Computational Research875 cited
  • 2017Good enough practices in scientific computing.452 cited
  • 2018Exploration and Explanation in Computational Notebooks343 cited
  • 2018Binder 2.0 - Reproducible, interactive, sharable environments for science at scale302 cited
  • 2016Ten Simple Rules for Taking Advantage of Git and GitHub231 cited

Cited by

  • 2021Using Jupyter for Reproducible Scientific Workflows132 cited
  • 2020Ten simple rules for writing Dockerfiles for reproducible data science107 cited
  • 2023The five pillars of computational reproducibility: bioinformatics and beyond80 cited
  • 2020Assessing and restoring reproducibility of Jupyter notebooks79 cited
  • 2020Practical Reproducibility in Geography and Geosciences73 cited
  • 2020Keeping modelling notebooks with TRACE: Good for you and good for environmental research and management support65 cited
  • 2021

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

Open data products-A framework for creating valuable analysis ready data
62 cited
  • 2024Computational reproducibility of Jupyter notebooks from biomedical publications51 cited
  • 2020The Design Space of Computational Notebooks: An Analysis of 60 Systems in Academia and Industry46 cited
  • 2021A Reproducible Data Analysis Workflow45 cited
  • 2020Improving reproducibility in computational biology research42 cited
  • 2023Developing and reusing bioinformatics data analysis pipelines using scientific workflow systems41 cited
  • 2022Eliciting Best Practices for Collaboration with Computational Notebooks28 cited
  • 2024Toward open science in marketing research21 cited
  • 2021Ten simple rules to cultivate transdisciplinary collaboration in data science17 cited
  • 2022Advancing code sharing in the computational biology community16 cited