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Towards Trust Engineering in Open Data Systems: A Layered Conceptual Framework Integrating Quality Assurance and Governance Perspectives

Authors:
Luciano Santos Pinheiro
Cristiane de Holanda de Barros e Silva
Vitor Barros Aquino
Thays Maria da Conceição Silva Carvalho
Cristiano Vale do Rego Barros Filho
Washington Henrique Carvalho Almeida

Keywords: data quality; trust engineering; open data; data governance; FAIR principles

Abstract:
Open data systems face persistent trust deficits due to silent quality regressions, schema drift, and inadequate provenance tracking. While existing frameworks address either data quality measurement or governance structures in isolation, a unified conceptual model integrating quality assurance mechanisms with governance principles remains absent. This paper proposes a five-layer conceptual framework for trust engineering in open data systems, synthesizing insights from data quality theory, data trust models, and software engineering validation practices. The framework organizes quality assurance mechanisms into a hierarchical pyramid—from structural contracts to semantic policy checks, anomaly monitoring, and observability—with each layer addressing distinct quality dimensions while collectively building trust through transparency and accountability. We position this framework within existing theoretical landscapes, including Findability, Accessibility, Interoperability, and Reusability (FAIR) principles, data trust governance, and International Organization for Standardization (ISO) quality standards, demonstrating how it extends current models by explicitly linking quality dimensions to executable validation mechanisms and publication governance decisions. Through comparative analysis of existing frameworks, we identify gaps in operationalizing trust through continuous validation and propose testable propositions for future empirical investigation. This work contributes a conceptual foundation for engineering trustworthy open data systems that balances transparency, risk management, and stakeholder accountability.

Pages: 21 to 28

Copyright: Copyright (c) IARIA, 2026

Publication date: May 24, 2026

Published in: conference

ISSN: 2519-8394

ISBN: 978-1-68558-398-9

Location: Venice, Italy

Dates: from May 24, 2026 to May 28, 2026