Can I use this publicly available dataset to build commercial AI software? -- A Case Study on Publicly Available Image Datasets
Not on the map. Why?
Abstract (arXiv)
Publicly available datasets are one of the key drivers for commercial AI software. The use of publicly available datasets is governed by dataset licenses. These dataset licenses outline the rights one is entitled to on a given dataset and the obligations that one must fulfil to enjoy such rights without any license compliance violations. Unlike standardized Open Source Software (OSS) licenses, existing dataset licenses are defined in an ad-hoc manner and do not clearly outline the rights and obligations associated with their usage. Further, a public dataset may be hosted in multiple locations and created from multiple data sources each of which may have different licenses. Hence, existing approaches on checking OSS license compliance cannot be used. In this paper, we propose a new approach to assessing the potential license compliance violations if a given publicly available dataset were to be used for building commercial AI software. We conduct a case study with our approach on 6 commonly used publicly available image datasets. Our results show that there exists potential risks of license violations associated with all of the studied datasets if they were used for commercial purposes.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 9 of its 61 references that are in the map. First posted on arXiv 3 Nov 2021.
Builds on
9 of 61 references.
References · 9
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- 2014ImageNet Large Scale Visual Recognition Challengecited by 8,498
- 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 6,013
- 2017VGGFace2: A dataset for recognising faces across pose and agecited by 914
- 2017Machine Learning Models that Remember Too Muchcited by 169
- 2018A Marketplace for Data: An Algorithmic Solutioncited by 76
- 2021Mitigating Dataset Harms Requires Stewardship: Lessons from 1000 Paperscited by 49
- 2019Towards Standardization of Data Licenses: The Montreal Data Licensecited by 19
- 2020What Makes a Popular Academic AI Repository?cited by 6
Built on by
Citing papers per year: 2024: 4; 2025: 2.
6 papers.
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- 2025Do Not Trust Licenses You See: Dataset Compliance Requires Massive-Scale AI-Powered Lifecycle Tracingcited by 4
- 2024"They've Stolen My GPL-Licensed Model!": Toward Standardized and Transparent Model Licensingcited by 3
- 2025Compliance Rating Scheme: A Data Provenance Framework for Generative AI Datasetscited by 2
- 2024SimClone: Detecting Tabular Data Clones using Value Similaritycited by 0
- 2025Compliance Rating Scheme: A Data Provenance Framework for Generative AI Datasets25 Dec 2025
- 2025Do Not Trust Licenses You See: Dataset Compliance Requires Massive-Scale AI-Powered Lifecycle Tracing4 Mar 2025
- 2024"They've Stolen My GPL-Licensed Model!": Toward Standardized and Transparent Model Licensing16 Dec 2024
- 2024Benchmark Data Repositories for Better Benchmarking31 Oct 2024
- 2024SimClone: Detecting Tabular Data Clones using Value Similarity24 Jun 2024
- 2024Rethinking Software Engineering in the Foundation Model Era: A Curated Catalogue of Challenges in the Development of Trustworthy FMware25 Feb 2024