# Open data, explainable artificial intelligence and legal conditions for forming trusted data ecosystems

- Type: Literature
- Source: Military strategy and technology
- Date: 2026-07-17
- Original: https://doi.org/10.63978/3083-6476.2026.2.5.03
- Canonical: https://overview.legal/posts/132109
- Topics: Monitoring, Personal Data

## Summary

The subject of this study is the legal regime of open data as a foundational element for the development of explainable artificial intelligence (XAI) and trusted data ecosystems. The topic focuses on the intersection of public information law, data quality standards, citizen-generated data, and the regulatory frameworks supporting reusable, high-value datasets in the context of digital governance and anti-corruption efforts. The purpose of the article is to analyze the legal preconditions for us

## Full text

The subject of this study is the legal regime of open data as a foundational element for the development of explainable artificial intelligence (XAI) and trusted data ecosystems. The topic focuses on the intersection of public information law, data quality standards, citizen-generated data, and the regulatory frameworks supporting reusable, high-value datasets in the context of digital governance and anti-corruption efforts. The purpose of the article is to analyze the legal preconditions for using open data in XAI systems, identify gaps in Ukrainian legislation, and propose directions for harmonization with European standards, particularly those related to high-value datasets and trustworthy AI. The research methodology combines doctrinal legal analysis (examination of national laws such as the Law of Ukraine “On Access to Public Information”, Cabinet of Ministers resolutions, and EU Implementing Regulation 2023/138), comparative legal method (contrasting Ukrainian practices with EU approaches under the Open Data Directive and AI Act), and systemic analysis of data lifecycles. Empirical elements include case studies from projects like CEDAR and review of scholarly literature on citizen-generated data and XAI. Qualitative interpretation of regulatory texts, policy documents (e.g., OECD AI Principles, Ukrainian Green Book on Open Data), and practical examples of data reuse in compliance and public procurement analytics was employed. The results demonstrate that while Ukraine has established a robust legal framework for open data publication, persistent challenges remain in data quality, machine-readability, interoperability, timely updates, and integration of citizen-generated data. Open data serves as a critical resource for training and auditing XAI models, provided personal data protection (GDPR-aligned), intellectual property, and restricted information rules are observed. The study distinguishes citizen-generated data from citizen science and public participation data, highlighting its potential as a complementary layer while noting risks of bias and the need for verification mechanisms. High-value datasets (e.g., company registers, public procurement, court decisions, land resources) are identified as priorities for Ukraine to maximize socio-economic impact. In conclusion, the article argues for a comprehensive National Data Strategy covering the full data lifecycle. Ukrainian data-driven solutions, exemplified by YouControl’s participation in the CEDAR project, contribute meaningfully to European trusted data ecosystems. The findings have direct application in public administration reform, anti-corruption tools, compliance software development, sustainable development monitoring (SDGs), and the creation of explainable AI systems for decision support in justice, finance, and governance. Recommendations include mandatory quality standards, API access, metadata requirements, and legal provisions for citizen data portals. These outcomes advance both theoretical legal scholarship on data ecosystems and practical policy implementation in transitioning economies.

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Generated by overview.legal · https://overview.legal/posts/132109 · 2026-07-18