Trustworthy and Data-Driven Intelligent Information Systems
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: 15 August 2026 | Viewed by 55
Special Issue Editors
Interests: machine learning; information systems; trustworthy AI; information retrieval; semantic technologies
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
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
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- advanced information systems
- data-driven methods
- machine learning
- information retrieval
- semantic technologies
- knowledge management
- Metadata management
- data quality
- data provenance
- system architectures
- digital libraries
- research data infrastructures
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