The CAiSE’27 Committee calls for full papers with a special emphasis on the theme of Hybrid Intelligent Information Systems Engineering.
Hybrid Intelligent Information Systems Engineering is considered a multidisciplinary field that combines data-driven (e.g., machine learning, deep learning) and knowledge-driven (e.g., symbolic reasoning, ontologies, rules) approaches to support intelligent, adaptive, and explainable decision-making in complex cyber-physical environments. It is concerned with the design, development, integration, and management of information systems that ensure data and information management, interoperability, scalability, and alignment with organisational and domain-specific requirements.
Within this field, Information Systems Engineering (IS Engineering) provides the foundational principles, methods, and frameworks that enable the integration of hybrid intelligence into organisational environments, ensuring that these systems are semantically grounded through data and information models; architecturally coherent and interoperable across heterogeneous components; governed and aligned with organisational processes, policies, and decision-making needs; and, sustainable and evolvable across the full lifecycle of data, models, and knowledge.
We encourage submissions that approach IS Engineering as a cohesive design endeavour, encompassing multiple aspects across the entire life cycle of information systems, including design, development, deployment, and operation. While contributions addressing specific subfields are certainly welcome, they should explicitly articulate how their results fit within the broader IS Engineering context, thereby fostering cross-disciplinary engagement and avoiding the formation of isolated research silos.
In addition to offering an exciting scientific program, CAiSE’27 will feature a best paper award and a journal special issue:
- Best Paper Award, sponsored by Springer.
- A selection of a few best papers will be invited to submit enhanced versions for consideration in a special issue of the Elsevier Information Systems journal dedicated to this conference (confirmation pending).
Papers should be submitted as PDF, following Springer’s LNCS format, and should not exceed 14 pages, excluding the references, but including all text, figures, and appendices. Submissions not conforming to the LNCS format, the page limitations, or being obviously out of the scope of the conference, will be rejected without review. For Springer’s LNCS format, see the guidelines provided at:
Springer’s LNCS Format Guidelines
The results described in the submitted paper must be unpublished and must not be under review elsewhere. Three to five keywords characterizing the paper should be listed at the end of the abstract. Each paper will be reviewed by at least two program committee members and, if positively evaluated, a third review will be conducted by one additional program board member. The selected papers will be discussed among the paper reviewers online, as well as during the program board meeting. Accepted papers will be presented at CAiSE’27 and published in the Springer Lecture Notes in Computer Science (LNCS) conference proceedings.
Anonymous submissions: CAiSE’27 implements a double-blind reviewing process. Author names and affiliations should not appear in the paper. The authors should make a reasonable effort not to reveal their identities or institutional affiliations in the text, figures, photos, links, or other data that is contained in the paper. Authors’ prior work should be referred to in the third person. Submissions that violate these requirements will be desk rejected without review. The list of authors cannot be changed after the acceptance decision is made unless approved by the Program Chairs and all involved authors.
In line with the common practice adopted by many conferences, submissions that have previously appeared as non-archival preprints or technical reports (e.g., on arXiv) are permitted. However, submissions currently under review or accepted for publication in another archival venue (conference proceedings or journal) are not eligible. Authors are also expected to preserve the integrity of the double-blind review process and should avoid actions that may compromise anonymity during the review period.
It should be noted that out of scope papers, unformatted papers, and papers beyond the page limit will be desk rejected without reviewing.
Types of Scientific Papers
We invite three types of scientific papers: technical papers, empirical papers, and exploratory papers. The type of submission must be indicated in the submission system. Each contribution should explicitly identify the IS Engineering problem addressed, its expected real-world impact, and the research method used. Furthermore, as mentioned above, submissions concerned with specific specialisations within the IS Engineering field are certainly welcome. However, they must explicitly position their results within the broader context to engage researchers across different areas and avoid silo formation. We strongly advise authors to clearly emphasise these aspects in their paper, including the abstract.
Papers must clearly articulate their contribution to the field of IS Engineering and demonstrate innovation, impact, or advancement beyond the state of the art in theories, methodologies, approaches, or technologies. Perspective authors might consider the recent paper: Oscar Pastor, John Krogstie, Selmin Nurcan, Steven Alter, Johann Eder, Xavier Franch, Monique Snoeck & Jolita Ralyté (2026): Articulating Information Systems Engineering Research Contributions, https://link.springer.com/chapter/10.1007/978-3-032-19578-4_2.
Anyhow, submissions should explicitly position their work within the existing body of research, clearly highlighting its novelty, relevance, and contribution. Contributions are expected to provide meaningful advances that extend current knowledge and support the continued development of the IS Engineering discipline.
Technical Papers
Technical papers describe original insights pertaining to the field of IS Engineering. A technical paper should clearly describe the situation or type of problem tackled, the relevant state of the art, the position or solution suggested and its potential, as well as demonstrate the benefits of the contribution through a rigorous evaluation. We explicitly welcome three kinds of technical papers:
- Technology oriented papers: produce and evaluate some technological artifact (infrastructure, tool, language, or system) in controlled/scoped experiments in lab settings.
- Method oriented papers: evaluate, produce and evaluate some socio-technological artifact (a method, approach to be used in an IS Engineering context) that needs to be evaluated in a (less controllable) real world setting.
- Conceptual and theoretical papers: deal with ontological, philosophical, semiotic, and mathematical foundations of IS Engineering. These papers typically use a deduction and/or argumentation-based approach to develop a point/contribution as part of their evaluation.
Empirical Papers
Empirical papers evaluate existing problem situations including problems encountered in practice, or validate proposed solutions with scientific means, i.e., by empirical studies, experiments, case studies, experience reports, simulations, etc. Scientific reflection on problems and practices in industry also falls into this category. The topic of the evaluation presented in the paper as well as its causal or logical properties must be clearly stated. The research method must be sound and appropriate.
Exploratory Papers
Exploratory papers describe completely new research positions or approaches, to face a generic situation arising because of new technologies, new kinds of activities, or new IS challenges. They must precisely describe the situation and demonstrate why current methods, tools, ways of reasoning, or meta-models are inadequate. They must also rigorously present their approach and demonstrate its pertinence and correctness in addressing the identified situation.
Topics of Contribution
The topics of contribution include but are not limited to:
Models, Methods and Techniques in IS Engineering
- Ontologies and Ontology Engineering
- Conceptual modeling, languages and design
- Requirements engineering
- Business process modeling, analysis and improvement
- Process automation, mining and monitoring
- Models and methods for evolution and reuse
- Low-code/no-code technology
- Domain and method engineering
- Product lines, variability and configuration management
- Compliance and alignment handling
- Active and interactive models
- Quality of IS models for analysis and design
- Visualisation techniques in IS
- Decision models and business intelligence
- Knowledge graphs
- Human-centred techniques
Architectures and Platforms for IS Engineering
- Distributed, mobile and open architecture
- Big Data architectures
- Cloud- and edge-based IS Engineering
- Service oriented and multi-agent IS Engineering
- Multi-platform IS Engineering
- Cyber-physical systems and Internet of Things (IoT)
- Workflow and Process Aware Information Systems
- Handling of real time data streams
- Content management and semantic Web
- Crowdsourcing platforms
- Conversational agents (chatbots)
- Agentic platforms
- Microservices design and deployment
In addressing the aforementioned topics, papers could bring innovation in IS Engineering by leveraging innovative techniques, tools, and platforms such as:
- Artificial Intelligence, including generative AI and Machine Learning
- Robotic Process Automation (RPA) and Intelligent Automation
- Big Data, Data Science and Analytics
- Blockchain applications in IS Engineering
- Simulation and Digital Twins
- IS Engineering for collaboration and social computing
- Virtual Reality / Augmented Reality
- Context-aware, autonomous and adaptive IS Engineering
Finally, submitted papers can address specific domains such as:
- IT governance
- eGovernment
- Autonomous and smart systems
- Healthcare
- Educational Systems and Learning Analytics
- Value and supply chain management
- Industry 4.0/Industry 5.0
- Sustainability and social responsibility management
- Privacy, security, trust, and safety management
Reproducibility
Research reproducibility is essential for scientific integrity and further scientific discovery. At CAiSE’27, we support rigorous evaluation and sharing of data, code, and methodologies to enhance the credibility and impact of scientific contributions. Authors are urged to publicly share all research artifacts such as datasets, source code, and supplementary materials as part of their submission. During paper submission, authors are requested to provide an Artifact Availability and Reproducibility Statement, which will be taken into account by the reviewers.
Authors are asked to use repository anonymization services like https://anonymous.4open.science to anonymize potential source code repositories and online supplementary material.
Use of GenAI
An AI usage statement (or acknowledgment) is required to disclose how generative artificial intelligence was used to conduct research, ensuring transparency and academic or professional integrity. In line with current ACM policies (cf. ACM’s policy on authorship), this includes detailing the creation of artifacts that are directly relevant to the conclusions of the research, such as code, datasets, charts or figures.
Submission Details
Submit your paper using the EasyChair link: https://easychair.org/my/conference?conf=caise2027
Questions and Inquiries
Questions about eligibility and other inquiries can be sent to the CAiSE’27 Program chairs at caise2027-main@easychair.org
Key Dates
- Abstract submission deadline (mandatory,
firm):
4 November 2026, AoE
- Paper submission deadline (firm):
15 November 2026, AoE
- Notification to authors:
10 February 2027
- Camera-ready version:
15 March 2027
- Author registration deadline:
20 March 2027
Deadlines correspond to Anywhere on Earth (AoE or UTC-12).
CAiSE’27 Conference: June 7-11, 2027