Since 2007, the RCIS conference series aims to bring together researchers, engineers, academics, and professionals of information science in a wide sense. This conference aims to facilitate knowledge sharing and dissemination of the latest advancements in key areas such as information systems and their engineering, user-oriented approaches, data and information management, enterprise management and engineering, domain-specific IS engineering, data science, information infrastructures, and reflective research and practice.

Nowadays Systems increasingly integrate cloud computing, AI, IoT, big data, and microservices. This technical complexity makes systems more difficult to grasp, especially for non-technical users and decision-makers. In addition, regulations such as the GDPR, AI Act, and Digital Services Act emphasize the need for transparency and accountability. All of these require that systems be understandable not only by technical experts but also by the general public.

Understandability plays a crucial role in bridging the gap between complexity and usability. It refers to how easily a human can comprehend the structure, behavior, and purpose of a system, based on how it is designed, documented, and presented. Understandability supports effective communication, design, education, and software development. It is not necessarily about simplicity, but about making complexity more approachable and clear.

Explainability and understandability are related but distinct concepts, particularly in contexts involving AI and complex decision-making systems. While understandability focuses on the user's ability to comprehend a system, explainability refers to the system's ability to describe or justify its outputs and decisions in a human-understandable way. Both contribute to trust, the extent to which users believe a system is reliable, secure and fair.

In a world where systems are getting smarter and more pervasive, understandability is what makes them usable and ultimately valuable. Ensuring that systems are understandable is foundational to making them ethical, accessible, and effective in 2026 and beyond.

Submission Guidelines

The proceedings of RCIS 2026 will be published by Springer in the Lecture Notes in Business Information Processing series. Papers shall be formatted according to the Springer LNCS/LNBIP conference proceedings template (for LaTeX and Word): https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines.

Papers that have already been accepted or are currently under review for other conferences or journals will not be considered for publication at RCIS 2026. Papers should be in English and must be associated to one of the following categories:

• Technical solution papers (max 16 pages Springer) present solutions that are novel or significantly improve existing approaches. A technical solution paper must include a preliminary validation of the proposed solution, and results must be stated clearly enough so that it is possible to validate them in follow-up research.
• Evaluation papers (max 16 pages Springer) evaluate existing problem situations or validate proposed solutions through scientific means, i.e., by empirical studies, experiments, case studies, simulations, mathematical proofs, etc. The research method must be sound and appropriate.
• Industrial practice and experience papers (max 16 pages Springer) thoroughly present problems or challenges encountered in practice, elaborate on success or failure with existing approaches, or report on industrial practice (e.g., methods and tools). A paper in this category shall provide a clear context, detail the problem or the industrial practice, and explain the lessons learned.

Important Dates

Contact

https://www.rcis-conf.com/rcis2026