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https://github.com/leipzig/awesome-reproducible-research

A curated list of reproducible research case studies, projects, tutorials, and media
https://github.com/leipzig/awesome-reproducible-research

List: awesome-reproducible-research

awesome awesome-list reproducibility reproducible-analysis reproducible-research reproducible-science reproducible-workflows

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A curated list of reproducible research case studies, projects, tutorials, and media

Host: GitHub
URL: https://github.com/leipzig/awesome-reproducible-research
Owner: leipzig
Created: 2017-11-15T18:33:19.000Z (almost 7 years ago)
Default Branch: master
Last Pushed: 2024-05-21T05:25:30.000Z (4 months ago)
Last Synced: 2024-05-23T09:27:14.283Z (4 months ago)
Topics: awesome, awesome-list, reproducibility, reproducible-analysis, reproducible-research, reproducible-science, reproducible-workflows
Language: Python
Homepage:
Size: 1.22 MB
Stars: 297
Watchers: 19
Forks: 34
Open Issues: 57
Metadata Files:
- Readme: readme.md
- Contributing: contributing.md
- Code of conduct: code-of-conduct.md

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awesome-security-collection - **60**星
ultimate-awesome - awesome-reproducible-research - A curated list of reproducible research case studies, projects, tutorials, and media. (Other Lists / PowerShell Lists)
jimsghstars - leipzig/awesome-reproducible-research - A curated list of reproducible research case studies, projects, tutorials, and media (Python)

README

# Awesome Reproducible Research [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3564746.svg)](https://doi.org/10.5281/zenodo.3564746)

> A curated list of reproducible research case studies, projects, tutorials, and media

## Contents

- [Case studies](#case-studies)
- [Ad-hoc reproductions](#ad-hoc-reproductions)
- [Theory papers](#theory-papers)
- [Theses and dissertations](#theses-and-dissertations)
- [Tool reviews](#tool-reviews)
- [Courses](#courses)
- [Development Resources](#development-resources)
- [Literature tools](#literature-tools)
- [Scientific Data Management Systems](#scientific-data-management-systems)
- [Books](#books)
- [Databases](#databases)
- [Data Repositories](#data-repositories)
- [Exemplar Portals](#exemplar-portals)
- [Runnable Papers](#runnable-papers)
- [Journals](#journals)
- [Ontologies](#ontologies)
- [Minimal Standards](#minimal-standards)
- [Organizations](#organizations)
- [Awesome Lists](#awesome-lists)

## Case studies
The term "case studies" is used here in a general sense to describe any study of reproducibility. A _reproduction_ is an attempt to arrive at comparable results with identical data using computational methods described in a paper. A _refactor_ involves refactoring existing code into frameworks and other reproducibility best practices while preserving the original data. A _replication_ involves generating new data and applying existing methods to achieve comparable results. A _robustness test_ applies various protocols, workflows, statistical models or parameters to a given data set to study their effect on results, either as a follow-up to an existing study or as a "bake-off". A _census_ is a high-level tabulation conducted by a third party. A _survey_ is a questionnaire sent to practitioners. A _case narrative_ is an in-depth first-person account. An _independent discussion_ utilizes a secondary independent author to interpret the results of a study as a means to improve inferential reproducibility.

Study

Field

Approach

Size

Glasziou et al 2008

Medicine

Census

80 studies

Baggerly & Coombes 2009

Cancer biology

Refactor

8 studies

Hothorn et al. 2009

Biostatistics

Census

56 studies

Ioannidis et al 2009

Genetics

Reproduction

18 studies

Anda et al 2009

Software engineering

Replication

4 companies

Vandewalle et al 2009

Signal processing

Census

134 papers

Prinz 2011

Biomedical sciences

Survey

23 PIs

Horthorn & Leisch 2011

Bioinformatics

Census

100 studies

Begley & Ellis 2012

Cancer biology

Replication

53 studies

Collberg et al 2014
Collberg & Proebsting 2016

Computer science

Census

613 papers

OSC 2015

Psychology

Replication

100 studies

Bandrowski et al 2015

Biomedical sciences

Census

100 papers

Patel et al 2015

Epidemiology

Robustness test

417 variables

Chang et al
2015

Economics

Reproduction

67 papers

Iqbal et al
2016

Biomedical sciences

Census

441 papers

Baker 2016

Science

Survey

1,576 researchers

Névéol et al 2016

NLP

Replication

3 studies

Reproducibility Project 2017

Cancer biology

Replication

9 studies

Vasilevsky et al 2017

Biomedical sciences

Census

318 journals

Kitzes et al 2017

Science

Case narrative

31 PIs

Barone et al 2017

Biological sciences

Survey

704 PIs

Kim & Dumas 2017

Bioinformatics

Refactor

1 study

Camerer 2017

Economics

Replication

18 studies

Olorisade 2017

Machine learning

Census

30 studies

Strupler & Wilkinson 2017

Archaeology

Case narrative

1 survey

Danchev et al 2017

Comparative toxicogenomics

Census

51,292 claims in 3,363 papers

Kjensmo & Gundersen 2018

Artificial intelligence

Census

400 papers

Gertler et al 2018

Economics

Census

203 papers

Stodden et al 2018

Computational science

Reproduction

204 papers, 180 authors

Madduri et al 2018

Genomics

Case narrative

1 study

Camerer et al 2018

Social sciences

Replication

21 papers

Silberzahn et al 2018

Psychology

Robustness test

One data set, 29 analyst teams

Boulesteix et al 2018

Medicine and health sciences

Census

30 papers

Eaton et al 2018

Microbiome immuno oncology

Replication

1 paper

Vaquero-Garcia et al 2018

Bioinformatics

Refactor and test of robustness

1 paper

Wallach et al 2018

Biomedical Sciences

Census

149 papers

Miller et al 2018

Bioinformatics

Synthetic replication & refactor

1 paper

Konkol et al 2018

Geosciences

Survey, Reproduction

146 scientists, 41 papers

Rahtz 2018

Reinforcement Learning

Reproduction, case narrative

1 paper

Stodden et al
2018

Computational physics

Census

306 papers

AlNoamany & Borghi 2018

Science & Engineering

Survey

215 participants

Li et al 2018

Nephrology

Robustness test

1 paper

Chen 2018

Social sciences & other

Census

810 Dataverse studies

Trisovic et al
2021

Social sciences & other

Census, Survey

2109 replication datasets

Nüst et al
2018

GIScience/Geoinformatics

Census, Survey

32 papers, 22 participants

Raman et al
2018

Genomics

Robustness test

8 studies

Stagge et al 2019

Geosciences

Survey

360 papers

Bizzego et al 2019

Deep learning

Robustness test

1 analysis

Madduri et al 2019

Genomics

Case narrative

1 analysis

Mammoliti
et al 2019

Pharmacogenomics

Case narrative

2 analyses

Allen & Mehler 2019

Biomedical sciences and Psychology

Census

127 registered reports

Pimentel et al 2019

All

Census

1,159,166 Jupyter notebooks

Fergusson et al 2019

Virology

Census

236 papers

Vlisides et al 2019
Sieber et al 2019

Anaesthesia

Independent discussion

1 study

Bakker et al 2019

Psychology

Replication

1 paper

Niepel et al 2019

Cell pharmacology

Robustness test

5 labs

Dacrema et al 2019

Machine learning

Reproduction

18 conference papers

Eran et al 2019

Experimental archaeology

Replication

1 theory

Rauh et al 2019

Neurology

Census

202 papers

Sætrevik & Sjåstad 2019

Psychology

Replication

2 experiments

Feng et al. 2019

Ecology and Evolution

Census

163 papers

Botvinik-Nezer et al. 2019

Neuroimaging

Robustness test

1 data set, 70 teams

Klein et al. 2019

Psychology

Replication

1 experiment, 21 labs, 2,220 participants

Obels et al. 2019

Psychology

Census

62 papers

Wayant et al
2019

Oncology

Census

154 meta-analyses

Simoneau et al. 2020

Bioinformatics

Robustness test

1 data set

Miyakawa 2020

Neurobiology

Census

41 papers

Thelwall et al
2020

Genetics

Census

1799 papers

Maassen et al
2020

Psychology

Reproduction

33 meta-analyses

Riedel et al
2020

Biomedical science

Census

792 papers

Culina et al
2020

Ecology

Census

346 papers

Clementi & Barba
2020

Physics

Replication

2 papers

Kemper et al
2020

Reproductive endocrinology

Census

222 papers

Marqués et al
2020

Biomedical sciences

Census

240 papers

Janssen et al
2020

Environmental Modelling

Census

7500 papers

Anderson et al
2020

Cardiology

Census

532 papers

Ostermann et al
2021

GIS

Census

75 papers

Samota & Davey
2020

Life Sciences

Survey

251 researchers

Bedford & Tzovaras
2020

Genetics

Robustness test

1 paper

Krassowski et al
2020 (repo)

Life Sciences

Census

3377 articles

Boudreau et al
2021

Computational Biology

Census

622 papers

Heumos et al
2021

Computational Biology

Robustness test

6 studies

Hrynaszkiewicz et al
2021

Computational Biology

Survey

214 researchers

Päll et al
2021

Differential expression

Census

2109 GEO submissions

Wijesooriya et al
2021

Computational biology

Census

186 papers

Weisberg et al
2021

Psychology

Robustness test

1 study

Vanderaa & Gatto
2021

Proteomics

Refactor

1 analysis

Breznau et al
2021

Social science

Robustness test

73 teams

Roberts et al
2021

Radiology

Census

62 studies

McDermott et al
2021

Clinical ML

Census

511 papers

Tedersoo et al
2021

9 Fields

Census

875 articles

Gabelica et al
2022

Life Sciences

Census

3556 papers

Samuel & Mietchen
2022

Biomedical Sciences

Census

9625 Jupyter notebooks

Zaorsky et al
2022

Radiation oncology

Robustness test

300k models

Kohrt et al
2022

Behavioral sciences

Refactor

One study

Hamilton et al
2022

Cancer biology

Census

306 papers

Motoki & Iseki
2022

Marketing

Replication

10 papers

Gihawi et al
2023

Bioinformatics

Refactor

1 paper

Gould et al
2023

Ecology

Robustness test

2 datasets, 174 teams

Protzko et al
2023

Psychology

Replication

16 findings

Bochynska et al
2023

Linguistics

Census

600 articles

Kambouris et al
2024

Ecology

Census

177 papers

Standvoss et al
2024

Biology

Census

750 papers

Brodeur et al
2024

Economics

Robustness test

110 papers

## Ad-hoc reproductions

These are one-off unpublished attempts to reproduce individual studies

Reproduction

Original study

https://rdoodles.rbind.io/2019/06/reanalyzing-data-from-human-gut-microbiota-from-autism-spectrum-disorder-promote-behavioral-symptoms-in-mice/
and
https://notstatschat.rbind.io/2019/06/16/analysing-the-mouse-autism-data/

Sharon, G. et al. Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice. Cell 2019, 177 (6), 1600–1618.e17.

https://github.com/sean-harrison-bristol/CCR5_replication

Wei, X.; Nielsen, R. CCR5-∆32 Is Deleterious in the Homozygous State in Humans. Nat. Med. 2019 DOI: 10.1038/s41591-019-0459-6. (retracted)

https://github.com/leipzig/placenta

Leiby et al "Lack of detection of a human placenta microbiome in samples from preterm and term deliveries"
https://doi.org/10.1186/s40168-018-0575-4

Heilbut et al "Rigor and Replication in Alzheimer’s Therapeutic Development: A Case Study"

Wang et al "Retraction: High-Affinity Naloxone Binding to Filamin A Prevents Mu Opioid Receptor–Gs Coupling Underlying Opioid Tolerance and Dependence"

## Theory papers

Authors/Date

Title

Field

Type

Ioannidis 2005

Why most published research findings are false

Science

Statistical reproducibility

Noble 2005

A Quick Guide to Organizing Computational Biology Projects

Bioinformatics

Best practices

Sandve et al 2013

Ten Simple Rules for Reproducible Computational Research

Computational science

Best practices

Freedman et al 2015

The Economics of Reproducibility in Preclinical Research

Preclinical research

Best practices

Yarkoni 2019

The Generalizability Crisis

Psychology

Statistical reproducibility

Bouthillier et al 2019

Unreproducible Research is Reproducible

Machine Learning

Methodology

Milton & Possolo 2019

Trustworthy data underpin reproducible research

Physics

Scientific philosophy

Devezer et al 2019

Scientific discovery in a model-centric framework: Reproducibility, innovation, and epistemic diversity

Science

Statistical reproducibility

Tierney et al 2020

A Realistic Guide to Making Data Available Alongside Code to Improve
Reproducibility

Science

Best practices

Haibe-Kains et al 2020

The importance of transparency and reproducibility in artificial
intelligence research

Artificial Intelligence

Critique

Nosek & Errington 2020

What is replication?

Science

Scientific philosophy

Alston & Rick 2020

A Beginner’s Guide to Conducting Reproducible Research

Ecology

Best Practices

Hejblum et al 2020

Realistic and Robust Reproducible Research for Biostatistics

Biostatistics

Best practices

Pawlik et al 2019

A Link is not Enough – Reproducibility of Data

Databases

Best practices

Schriml et al 2020

COVID-19 pandemic reveals the peril of ignoring metadata standards

Virology

Critique

Stoudt et al 2020

Principles for data analysis workflows

Data science

Best practices

Peng & Hicks 2020

Reproducible Research: A Retrospective

Public health

Review

Reiter et al 2020

Streamlining Data-Intensive Biology With Workflow Systems

Biology

Best practices

Ulrich & Miller 2020

Meta Research: Questionable research practices may have little effect on replicability

Science

Statistical reproducibility

Kasif & Roberts 2020

We need to keep a reproducible trace of facts, predictions, and hypotheses from gene to function in the era of big data

Functional genomics

Critique

Raman 2021

A research parasite's perspective on establishing a baseline to avoid errors in secondary analyses

Science

Best practices

Hoffmann et al 2021

The multiplicity of analysis strategies jeopardizes replicability: lessons learned across disciplines

Science

Critique

Rosenberg et al 2020

Reproducible Results Policy

Water Resources

Policy

Clary et al 2022

10 Things for Curating Reproducible and FAIR Research

Social sciences

Best practices

Mongan et al 2020

Checklist for Artificial Intelligence in Medical Imaging (CLAIM): A Guide for Authors and Reviewers

Medical imaging

Best practices

Orzechowski & Moore 2022

Generative and reproducible benchmarks or comprehensive evaluation machine learning classifiers

Machine Learning

Best practices

Ziemann et al 2023

The five pillars of computational reproducibility: Bioinformatics and beyond

Bioinformatics

Best practices

Stefan & Schönbrodt 2023

Big little lies: a compendium and simulation of p-hacking strategies

Research

Statistical reproducibility

Reinagel 2023

Is N-Hacking Ever OK? The consequences of collecting more data in pursuit of statistical significance

Biology

Statistical reproducibility

Abdill et al 2024

A how-to guide for code-sharing in biology

Biology

Best practices

Hassan et al 2024

Characterising Reproducibility Debt in Scientific Software:A Systematic Literature Review

Reproducible Research

Review of reviews

## Theses and dissertations

Authors/Date

Title

Institution

Pham, Quan 2014

A Framework for Reproducible Computational Research

University of Chicago

Wallach, Joshua 2016

Reproducible Research Practices, Scientific Transparency, and Subgroup Claims: A Meta-Research Dissertation

Stanford University

Konkol, Markus 2019

Publishing Reproducible Geoscientific Papers: Status quo, benefits, and opportunities

University of Münster

Trisovic, Ana 2018

Data preservation and reproducibility at the LHCb experiment at CERN

University of Cambridge

Feger, Sebastian 2020

Interactive Tools for Reproducible Science -- Understanding, Supporting, and Motivating Reproducible Science Practices

University of Munich

Leipzig, Jeremy 2021

Tests of Robustness in Peer Review

Drexel University

Nüst, Daniel 2022

Infrastructures and Practices for Reproducible Research in Geography, Geosciences, and GIScience

University of Münster

Melcher, Wiebke 2019

Free will in psychological research : considerations on methodic procedure and reproducibility of results

Leuphana University

Abang Ibrahim, Dayang 2016

The exploitation of provenance and versioning in the reproduction of e-experiments

University of Newcastle Upon Tyne

Henderson, Peter 2018

Reproducibility and Reusability in Deep Reinforcement Learning

McGill University

Drimer-Batca, Daniel 2018

Reproducibility Crisis in Science: Causes and Possible Solutions

Boston University

Matheson, Granville 2018

Reliability, Replicability and Reproducibility in Pet Imaging

Karolinska Institutet

Patil, Prasad 2016

Assessing reproducibility and value in genomic signatures

The Johns Hopkins University

Ahmad, MKH 2016

Scientific workflow execution reproducibility using cloud-aware provenance

University of the West of England, Bristol

Samuel, Sheeba 2019

A provenance-based semantic approach to support understandability, reproducibility, and reuse of scientific experiments

Friedrich-Schiller-Universität Jena

Wayant, Christian Cole 2021

Rigor and reproducibility of cancer medicine evidence

Oklahoma State University

Vilaró Pacheco, Marta 2021

Long-term impact of an editorial intervention to improve paper transparency and reproducibility

Universitat Politècnica de Catalunya

Sebastian, Aswathy 2023

Advancing Genomic and Transcriptomic Knowledge Through Reproducible Bioinformatics Workflows

Penn State University

## Tool reviews

Authors/Date

Title

Tools

Isdahl & Gundersen 2019

Out-of-the-box Reproducibility: A Survey of Machine Learning Platforms

MLflow, Polyaxon, StudioML, Kubeflow, CometML, Sagemaker, GCPML, AzureML, Floydhub, BEAT, Codalab, Kaggle

Pimentel et al
2019

A Survey on Collecting, Managing, and Analyzing Provenance from Scripts

Astro-Wise, CPL, CXXR, Datatrack, ES3, ESSW, IncPy, Lancet, Magni, noWorkflow, Provenance Curios, pypet, RDataTracker, Sacred, SisGExp, SPADE, StarFlow, Sumatra, Variolite, VCR, versuchung, WISE, YesWorkflow

Leipzig et al
2021 (supplemental)

The Role of Metadata in Reproducible Computational Research

CellML, CIF2, DATS, DICOM, EML, FAANG, GBIF, GO, ISO/TC 276, MIAME, NetCDF, OGC, ThermoML, CRAN, Conda, pip setup.cfg, EDAM, CodeMeta, Biotoolsxsd, DOAP, ontosoft, SWO, OBCS, STATO, SDMX, DDI, MEX, MLSchema, MLFlow, Rmd, CWL, CWLProv, RO-Crate, RO, WICUS, OPM, PROV-O, ReproZip, ProvOne, WES, BagIt, BCO, ERC, BEL, DC, JATS, ONIX, MeSH, LCSH, MP, Open PHACTS, SWAN, SPAR, PWO, PAV, Manubot, ReScience, PandocScholar

Konkol, Markus, Nüst, Daniel, Goulier, Laura
2020

Publishing computational research - a review of infrastructures for reproducible and transparent scholarly communication

Authorea, Binder, CodeOcean, eLife RDS, Galaxy Project, Gigantum, Manuscript, o2r, REANA, ReproZip, Whole tale

## Courses
- MOOCs
- [Coursera Reproducible Research](https://www.coursera.org/learn/reproducible-research) - Roger Peng et al JHU. Very popular course.
- [edX Principles, Statistical and Computational Tools for Reproducible Science](https://www.edx.org/course/principles-statistical-computational-harvardx-ph527x) - John Quackenbush et al Harvard
- [Reproducible research: methodological principles for transparent science](https://www.fun-mooc.fr/en/courses/reproducible-research-methodological-principles-transparent-scie/) - Beginner level. Note taking, version control, notebooks, reproducible data analysis. Bilingual English/French.
- Online course content
- [Tools for Reproducible Research](http://kbroman.org/Tools4RR/) - Karl Broman UW, includes resources page
- [R for Reproducible Scientific Analysis](https://swcarpentry.github.io/r-novice-gapminder/) - Software Carpentry workshop primer using Gapminder data
- [R-DAVIS](https://gge-ucd.github.io/R-DAVIS/syllabus.html) - Student-developed computer literacy and data course in R
- [AMIA2019](https://github.com/StatTag/amia-2019-spring-rr/) - Pragmatic RR for Analysis, Dissemination and Publication
- [PSU-PSY525](https://github.com/psu-psychology/psy-525-reproducible-research-2020) - Transparent, Open, and Reproducible Research Practices in the Social and Behavioral Sciences
- [Monash-RRR](https://monashdatafluency.github.io/r-rep-res/) - Reproducible Research in R workshop tutorial
- [OSU-OSRR](https://github.com/cbahlai/OSRR_course) - An open science and reproducible research course targeted at organismal ecologists
- [Reproducible-Science-Curriculum](https://github.com/Reproducible-Science-Curriculum) - A curriculum for teaching reproducible computational science bootcamps

## Development Resources
- R
- [CRAN Task View - Reproducible Research](https://cran.r-project.org/web/views/ReproducibleResearch.html) - packages relevant to RCR in R
- [liftr](https://liftr.me/) - persistent reproducible reporting through containerized R Markdown documents
- [repo](https://github.com/franapoli/repo) - provenance framework package
- [orderly](https://vimc.github.io/orderly/articles/orderly.html) - R package that automates writing reproducible analyses
- Linux-related (polyglot)
- [Reproducible Builds](https://reproducible-builds.org/) - a set of software development practices that create an independently-verifiable path from source to binary code
- Python
- [mlf-core](https://mlf-core.com) - Framework to develop GPU deterministic machine learning models with PyTorch, TensorFlow and XGBoost

## Literature tools
- [Scite](https://scite.ai/) - Citation statement AI for discovering and evaluating scientific articles
- [SciScore](https://www.sciscore.com/) - SciScore methods sections for a variety of rigor criteria and analyzes sentences that contain research resources (antibodies, cell lines, plasmids and software tools) and determines how uniquely identifiable that resource is based off of the provided metadata.
- [Ripeta](https://www.ripeta.com/) - Ripeta quickly scans research manuscripts or articles to identify and record key reproducibility variables, such as data availability, code acknowledgements, and research analysis methods.

## Scientific Data Management Systems
- [DVC](https://dvc.org/) - DVC tracks machine learning models and data sets
- [DataLad](https://www.datalad.org/) - Git-based versioning for data and provenance
- [Overture](https://www.overture.bio/) - Portal, query interface, visualization and schema framework that powers ICGC, KFDC, GDC
- [Fairly Toolset](https://fairly.readthedocs.io) - Tools for preparing, publishing and downloading datasets from research data repositories directly into computing environments. It provides integration with [Zenodo](https://fairly.readthedocs.io) and [Figshare](https://figshare.com/).

## Books
- [Reproducible Research with R and R Studio 2013](https://g.co/kgs/RxcFNm)
- [Implementing Reproducible Research 2014](https://osf.io/s9tya/) - Describes projects: Sumatra, Vistrails, CDE, SOLE, JUMBO, CML, knitr. Content available on OSF.
- [The Practice of Reproducible Research 2017](https://g.co/kgs/jZiMR7) - 31 first person case narratives and intro chapters
- [Dynamic Documents with R and knitr 2015](https://g.co/kgs/dpzkF4)
- [The Turing Way: A Handbook for Reproducible Data Science 2020](https://the-turing-way.netlify.com/introduction/introduction)
- [Reproducibility and Replicability in Science](https://www.nap.edu/catalog/25303/reproducibility-and-replicability-in-science)
- [Reproducibility: Principles, Problems, Practices, and Prospects](https://www.wiley.com/en-ec/Reproducibility:+Principles,+Problems,+Practices,+and+Prospects+-p-9781118864975)

## Databases
- [ReplicationWiki](http://replication.uni-goettingen.de/wiki/index.php) - Database for empirical studies with information about methods, data and software used, availability of replication material and whether replications, corrections or retractions are known. Mostly focused on social sciences.
- [ReproCrawl](https://crawl.reproduciblescience.org/)
- [ReplicationDatabase](https://metaanalyses.shinyapps.io/replicationdatabase/) - 1211 replication findings on 333 psychology studies

## Data Repositories
All these repositories assign Digital Object Identifiers (DOIs) to data
- [DataCite](https://datacite.org) - 12M+ DOIs registered for 46 allocators. Offers APIs and a metadata schema.
- [Data Dryad](https://datadryad.org) - curated, metadata-centric, focused on articles associated with published artices, $120 submission fee (various waivers available)
- [Figshare](https://figshare.com) - 20 GB of free private space, unlimited public space, >2M articles, >5k projects
- [OSF](https://osf.io) - Project-oriented system with access control and integration with popular tools. Unlimited storage for projects, but individual files are limited to 5 gigabytes (GB) each.
- [Zenodo](https://zenodo.org/) - Allows embargoed, restricted access, metadata support. 50GB limit.

## Exemplar Portals
Places to find papers with code or portals to host them
- [Jupyter Gallery](https://github.com/jupyter/jupyter/wiki/A-gallery-of-interesting-Jupyter-Notebooks) - Gallery of interesting Jupyter notebooks
- [Papers With Code](https://paperswithcode.com/) - ML papers with code
- [NARPS](https://github.com/poldrack/narps) - Code related to Neuroimaging Analysis Replication and Prediction Study
- [Codeocean](https://codeocean.com/explore) - A gallery of cloud-based containers with reproducible analyses

## Runnable Papers
Experimental papers that have associated notebooks
### Haibe-Kains lab

### Patcher lab

Publication

Github link

Pimental et al 2017. Differential analysis of RNA-seq incorporating quantification uncertainty

sleuth_paper_analysis

Melsted et al 2019. Modular and efficient pre-processing of single-cell RNA-seq

MBGBLHGP_2019

Chari et al 2021. Whole Animal Multiplexed Single-Cell RNA-Seq Reveals Plasticity of Clytia Medusa Cell Types

CWGFLHGCCHAP_2021

### Siepel lab

Blumberg et al 2021. Characterizing RNA stability genome-wide through combined analysis of PRO-seq and RNA-seq data

https://codeocean.com/capsule/7351682

## Journals
- [ReScience](http://rescience.github.io/) - Journal dedicated to insilico reproductions and tests of robustness, lives on Github.
- [eLife](https://elifesciences.org/for-the-press/eb096af1/elife-launches-executable-research-articles-for-publishing-computationally-reproducible-results) - Executable Research Articles (ERA) inline executable blocks

## Ontologies
- [FAIRsharing](https://fairsharing.org) - standards, databases, and policies
- [BioPortal](https://bioportal.bioontology.org/) - 660 biomedical ontologies

## Minimal Standards
- [STORMS](https://www.stormsmicrobiome.org/) - Strengthening The Organization and Reporting of Microbiome Studies (STORMS) is a checklist for reporting on human microbiome studies. [Preprint](https://doi.org/10.1101/2020.06.24.167353)

## Organizations
- [ResearchObject.org](http://www.researchobject.org/) - RO specifications and publications
- [BioCompute](https://osf.io/zm97b/) - BCO specs
- [rOpenSci](https://ropensci.org) - Tools, conferences, and education
- [Open Science Framework](https://osf.io) - Open source project management
- [pyOpenSci](https://www.pyopensci.org/) - Promotes open and reproducible research through peer-review of scientific Python packages
- [Replication Network](https://replicationnetwork.com/) - Furthering the practice of replication in economics. Econ replication database.
- [repliCATS project](https://replicats.research.unimelb.edu.au/) - Estimating the replicability of research in the social sciences. [Paper](https://osf.io/preprints/metaarxiv/2pczv/)
- [ReproHack](https://reprohack.github.io/reprohack-hq/) - 1-day reproducibility hackathons held worldwide
- [CODECHECK](https://codecheck.org.uk/) - community for checking executability of scientific preprints and papers
- [CASCaD](https://www.cascad.tech/) - Certification Agency for Scientific Code and Data. Issues reproducibility certificates.
- [Reproducibility for Everyone](https://www.repro4everyone.org/) - Community-led reproducibility workshops
- [CUrating for REproducibility](https://curating4reproducibility.org/) - curation of research and code for digital preservation
- [Michigan Institute for Data Science Reproducibility Hub](https://midas.umich.edu/reproducibility-resources/) - [reproducibility challenge](https://hdsr.mitpress.mit.edu/pub/mlconlea/release/1) manuscripts & presentations
- [OpenMKT](https://openmkt.org/) - transparency and quality of marketing research published in academic journals
- [Many Co-Authors](https://manycoauthors.org/) - online platform designed to collect and share information on the provenance and availability of the data for all articles co-authored by Francesca Gino
- [FORRT](https://forrt.org/) - Framework for Open and Reproducible Research Training advancing research transparency, reproducibility, rigor, and ethics through pedagogical reform and meta-scientific research

## Awesome Lists
- [Awesome Pipeline](https://github.com/pditommaso/awesome-pipeline) - So many pipelines frameworks
- [Awesome Docker](https://github.com/veggiemonk/awesome-docker) - Everything related to the Docker containerization system
- [Awesome R](https://github.com/qinwf/awesome-R#reproducible-research) - Section on RR tools
- [Awesome Reproducible R](https://github.com/datasnakes/awesome-reproducible-R) - RRR tools
- [Awesome Jupyter](https://github.com/adebar/awesome-jupyter) - Jupyter projects, libraries and resources
- [Awesome Bioinformatics Benchmarks](https://github.com/j-andrews7/Awesome-Bioinformatics-Benchmarks) - Benchmarks are a related aspect of robustness testing
- [Awesome Open Science](https://github.com/ZoranPandovski/awesome-open-science) - Resources, data, tools, and scholarship
- [Awesome Public Datasets](https://github.com/awesomedata/awesome-public-datasets) - A topic-centric list of HQ open datasets
- [Awesome Semantic Web](https://github.com/semantalytics/awesome-semantic-web) - Semantic web and linked data resources.

## Contribute

Contributions welcome! Read the [contribution guidelines](contributing.md) first. You may find my `src/doi2md.py` script useful for quickly generating entries from a DOI.

## License

[![CC0](http://mirrors.creativecommons.org/presskit/buttons/88x31/svg/cc-zero.svg)](https://creativecommons.org/publicdomain/zero/1.0/)

To the extent possible under law, Jeremy Leipzig has waived all copyright and
related or neighboring rights to this work.