# Towards Traceability in Data Ecosystems using a Bill of Materials Model

arXiv: https://arxiv.org/abs/1904.04253 · HTML: https://mlsanity.com/paper/1904.04253/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Apr 2019.

## Built on by (most cited first, 12 of 12)

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- [Developer Perspectives on Licensing and Copyright Issues Arising from Generative AI for Software Development](https://mlsanity.com/paper/2411.10877/) (2024)
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- [An investigation of licensing of datasets for machine learning based on the GQM model](https://mlsanity.com/paper/2303.13735/) (2023)
- [Blockchain-Enabled Accountability in Data Supply Chain: A Data Bill of Materials Approach](https://mlsanity.com/paper/2408.08536/) (2024)
- [Situated Ground Truths: Enhancing Bias-Aware AI by Situating Data Labels with SituAnnotate](https://mlsanity.com/paper/2406.07583/) (2024)

## Abstract (arXiv)

Researchers and scientists use aggregations of data from a diverse combination of sources, including partners, open data providers and commercial data suppliers. As the complexity of such data ecosystems increases, and in turn leads to the generation of new reusable assets, it becomes ever more difficult to track data usage, and to maintain a clear view on where data in a system has originated and makes onward contributions. Reliable traceability on data usage is needed for accountability, both in demonstrating the right to use data, and having assurance that the data is as it is claimed to be. Society is demanding more accountability in data-driven and artificial intelligence systems deployed and used commercially and in the public sector. This paper introduces the conceptual design of a model for data traceability based on a Bill of Materials scheme, widely used for supply chain traceability in manufacturing industries, and presents details of the architecture and implementation of a gateway built upon the model. Use of the gateway is illustrated through a case study, which demonstrates how data and artifacts used in an experiment would be defined and instantiated to achieve the desired traceability goals, and how blockchain technology can facilitate accurate recordings of transactions between contributors.