Trustworthy and Data-Driven Intelligent Information Systems

Dear Colleagues,

Modern information systems increasingly rely on artificial intelligence and data-driven methods to manage complex, heterogeneous, and evolving information at scale. This Special Issue, ‘Trustworthy and Data-Driven Intelligent Information Systems’, solicits high-quality research on the design, implementation, and evaluation of information systems that effectively integrate machine learning, information retrieval, semantic technologies, and data management into cohesive, deployable architectures.

We seek contributions that will advance the state of the art in building intelligent information systems capable of operating under realistic constraints. Rather than isolated algorithmic innovations, we emphasize system-level research that examines how data, models, and architectural components jointly address complex operational requirements. Of particular interest are systems designed for environments characterized by heterogeneous metadata standards, federated data sources, long-term preservation needs, and multi-stakeholder governance, exemplified by research data infrastructures, digital libraries, scholarly communication platforms, and similar knowledge-intensive systems.

The scope includes intelligent data integration and interoperability, metadata and knowledge management, scalable retrieval and discovery mechanisms, data quality and provenance tracking, and architectural patterns that support transparency, reliability, and sustainable evolution. We welcome both methodological contributions that advance technical capabilities and empirical studies that demonstrate measurable system-level impacts in realistic deployment scenarios.

The purpose of this Special Issue is to consolidate research at the intersection of AI, data-centric methods, and information systems, fostering dialogue across scholarly communities and establishing rigorous foundations for next-generation intelligent information infrastructures. We aim to bridge advances in computational techniques with the practical challenges of building systems that remain effective, trustworthy, and maintainable over time.

We invite original submissions that combine technical innovation with system-level perspectives, empirical validations, and real-world deployment considerations.

Dr. Zeyd Boukhers
Dr. Christoph Lange
Guest Editors

Manuscript Submission Information

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