Data Products and Intelligent Data Platforms for the Future Internet

Dear Colleagues,

In modern data-driven society, organizations and societies increasingly depend on interconnected and intelligent data ecosystems to generate insights, enable innovation, and support digital transformation. As data becomes a critical resource for decision-making and value creation, the need for scalable, interoperable, and trustworthy infrastructures has never been more pressing. Concepts such as data products on the one hand and data mesh and data spaces on the other hand are redefining how data is collected, managed, processed, shared, and consumed within and across organizations, shaping the foundation of the Future Internet.

These paradigms promote the decentralization of data ownership, the empowerment of domain-oriented data responsibility, and the creation of self-contained data products that can be discovered, accessed, and utilized across different applications and systems. However, realizing such organizational concepts requires addressing profound challenges related to data quality, interoperability, privacy, security, and fairness. The need to ensure that data is adequately prepared, cleansed, transformed, and protected before being made available is essential to achieving reliable and ethical data ecosystems. Especially in light of novel threats like AI poisoning attacks targeting the underlying data products or the models themselves, research into advanced detection capabilities and robust resiliency mechanisms in both the data’s infrastructure and the AI models to maintain the data product’s trustworthiness is also a necessity in this regard.

At the same time, the demand-driven refinement and provisioning of data introduce new dimensions of technical and organizational complexity. Flexible and intelligent data pipelines, semantic modeling approaches, and dynamic governance mechanisms are vital to ensuring that the right data is delivered to the right consumer in the requested form while maintaining compliance with privacy regulations and fairness principles. Handling biases, safeguarding sensitive information, and ensuring transparency and accountability across data products are critical steps toward a trustworthy and sustainable data infrastructure for the Future Internet. The recent emergence of agentic artificial intelligence and large language models further transforms this landscape, offering new opportunities for autonomous data curation, metadata generation, and adaptive integration across data domains, yet at the same time aggravating concerns regarding bias, transparency, and accountability.

We aim to explore the latest research, methodologies, technologies, and practical experiences related to the creation, management, and governance of data products and intelligent data platforms. We seek to bring together researchers, practitioners, and industry experts from various domains to foster interdisciplinary discussions and share innovative approaches to advance both the theoretical and practical foundations of efficient, trustworthy, and sustainable data ecosystems.

We invite the submission of original research papers, comprehensive reviews, tool evaluations, and case studies addressing both scientific challenges and real-world implementations.

We look forward to receiving your contributions as we collectively shape and advance the data products and intelligent data platforms of tomorrow.

Topics of Interest

Topics include, but are not limited to, the following:

• Architectures and reference models for data mesh and data spaces;
• Modeling, design, and lifecycle management of data products;
• Techniques for data preparation, cleaning, and transformation;
• Demand-driven and context-aware data provisioning;
• Data quality management, observability, and provenance tracking;
• Privacy-preserving data sharing and anonymization strategies;
• Provenance techniques for data products to enhance transparency;
• Provenance documentation to provide evidence of compliance with privacy policies;
• Security, access control, and trust management in decentralized data platforms;
• Identification and mitigation of bias in data products and pipelines;
• Ensuring fairness, accountability, and transparency in data ecosystems;
• Detection and mitigation of AI poisoning attacks and related adversarial threats in data ecosystems;
• Applications of agentic AI and large language models in data preparation and governance;
• Automation, orchestration, and semantic interoperability of data pipelines;
• Evaluation and benchmarking of tools and frameworks for data product management;
• Industrial case studies and practical lessons learned from data mesh and data space implementations;
• Human-centered and ethical aspects of data product and platform design.

With this Special Issue, we seek to establish a multidisciplinary forum for advancing the scientific and practical understanding of data products and data platform ecosystems as essential enablers of the Future Internet. By combining technological innovation with human-centered and ethical considerations, we aim to foster a reliable, transparent, and intelligent data infrastructure that supports a sustainable and equitable digital society.

Dr. Christoph Stach
Dr. Iouliana Litou
Dr. Laura Erhan
Dr. Tanja Auge
Dr. Clémentine Gritti
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. Future Internet is an international peer-reviewed open access monthly 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 1800 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.

• • Data Products
• • Data Mesh and Data Spaces
• • Intelligent Data Platforms
• • Decentralized Data Governance
• • Data Quality and Provenance
• • Trustworthy Data Ecosystems
• • Privacy-Preserving Data Sharing
• • AI-Driven Data Pipelines
• • Agentic AI and Large Language Models
• • Resilient Data and AI Systems