DataHub: Collaborative Data Science & Dataset Version Management at Scale
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Abstract (arXiv)
Relational databases have limited support for data collaboration, where teams collaboratively curate and analyze large datasets. Inspired by software version control systems like git, we propose (a) a dataset version control system, giving users the ability to create, branch, merge, difference and search large, divergent collections of datasets, and (b) a platform, DataHub, that gives users the ability to perform collaborative data analysis building on this version control system. We outline the challenges in providing dataset version control at scale.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Sep 2014.
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Citing papers per year: 2021: 4; 2022: 1; 2023: 3; 2024: 1; 2025: 1.
10 papers.
- 2023Data-centric Artificial Intelligence: A Surveycited by 202
- 2021How AI Developers Overcome Communication Challenges in a Multidisciplinary Team: A Case Studycited by 29
- 2021Reusable Templates and Guides For Documenting Datasets and Models for Natural Language Processing and Generation: A Case Study of the HuggingFace and GEM Data and Model Cardscited by 24
- 2021Ember: No-Code Context Enrichment via Similarity-Based Keyless Joinscited by 7
- 2024Data Collection and Labeling Techniques for Machine Learningcited by 4
- 2021Data Science Methodologies: Current Challenges and Future Approachescited by 1
- 2022EdnaML: A Declarative API and Framework for Reproducible Deep Learningcited by 1
- 2023AI for Open Science: A Multi-Agent Perspective for Ethically Translating Data to Knowledgecited by 1
- 2023Experimental Insights Towards Explainable and Interpretable Pedestrian Crossing Predictioncited by 1
- 2025SAVeD: Semantic Aware Version Discoverycited by 0
- 2025SAVeD: Semantic Aware Version Discovery21 Nov 2025
- 2024Data Collection and Labeling Techniques for Machine Learning19 Jun 2024
- 2023Experimental Insights Towards Explainable and Interpretable Pedestrian Crossing Prediction5 Dec 2023
- 2023AI for Open Science: A Multi-Agent Perspective for Ethically Translating Data to Knowledge28 Oct 2023
- 2023Data-centric Artificial Intelligence: A Survey17 Mar 2023
- 2022EdnaML: A Declarative API and Framework for Reproducible Deep Learning13 Nov 2022
- 2021Reusable Templates and Guides For Documenting Datasets and Models for Natural Language Processing and Generation: A Case Study of the HuggingFace and GEM Data and Model Cards16 Aug 2021
- 2021Data Science Methodologies: Current Challenges and Future Approaches14 Jun 2021
- 2021Ember: No-Code Context Enrichment via Similarity-Based Keyless Joins2 Jun 2021
- 2021How AI Developers Overcome Communication Challenges in a Multidisciplinary Team: A Case Study13 Jan 2021