# EKAW 2026 - Call For Papers
The 25th International Conference on Knowledge Engineering and Knowledge Management (EKAW-26) encompasses the diverse realms of eliciting, acquiring, modeling, and managing knowledge in a variety of information objects ranging from taxonomies, to ontologies and knowledge graphs. The conference addresses the pivotal role of knowledge in constructing systems and services for the semantic web, knowledge management, knowledge discovery, information integration, natural language processing, intelligent systems, AI systems in e-business, e-health, humanities, cultural heritage, sustainability and beyond.

This year’s special theme is investigating “New Frontiers in Knowledge Engineering”.  Indeed, the current AI technological landscape is marked by major new trends and technologies emerging at an unprecedented pace. Generative AI systems, neuro-symbolic AI, agentic AI, AI regulations are just a few of the ground-breaking, ongoing trends. In such a setting, it is natural for each community to embark in a “soul-searching” and strategic positioning activity: What is our role in AI? What are major current and long-term developments in the field? What are new challenges and opportunities brought about by this context? In this year’s EKAW, we invite the community to reflect on how this extraordinary backdrop could affect current ways to engineer and manage knowledge, including: what are limitations of generative AI systems and how can knowledge engineering be used to alleviate those? What are novel requirements for “high-quality” knowledge in neuro-symbolic architectures? What are emerging neuro-symbolic system patterns for performing knowledge engineering?  

All submissions, including those related to the technologies mentioned on the special theme, should establish a clear connection to Knowledge Engineering and Knowledge Management or demonstrate a significant impact on the field. While acknowledging the interdisciplinary nature of knowledge and its interplay with other disciplines and technologies, such as Machine Learning, Natural Language Processing, and Computer Vision, contributions lacking direct relevance to Knowledge Engineering and Knowledge Management will not be considered pertinent to the EKAW conference.


## IMPORTANT DATES
All submission deadlines are 23:59:59 AoE.

* Abstract Submission Deadline: May 8, 2026

* Full Paper Submission Deadline: May 15, 2026

* Notification of Acceptance: July 10, 2026z

* Camera Ready Deadline: July 31, 2026

* Conference Days: September 29 - October 1, 2026


## TOPICS OF INTEREST

### Knowledge Engineering

* Methods, techniques, and tools for knowledge engineering

* Evaluation methods and metrics for ensuring knowledge quality

* Collaborative knowledge engineering

* Ontology mapping and alignment

* Ontology design patterns

* Multimodal knowledge engineering

* Methods for benchmarking/comparing Language Models for KE tasks

* Uncertainty and vagueness in knowledge representation

* Dealing with dynamic, distributed and emerging knowledge

* Neuro-symbolic, GenAI and AI agent-based methodologies and architectures for knowledge engineering

* Engineering of complex types of knowledge (e.g., causality, workflows, procedures)

* (Ontological) knowledge memorization in LMs

* Translating between explicitly represented (symbolic) knowledge and knowledge captured in machine learning models (parametric knowledge) or embeddings




### Knowledge Management and Governance

* Methods, techniques, and tools for knowledge management and governance

* Knowledge evolution, maintenance, and preservation

* Knowledge sharing and distribution

* Methods for accelerating take-up of knowledge management technologies

* Question answering over knowledge graphs via LMs

* Robust and scalable knowledge management

* Conversational AI and dialogue systems for knowledge management




### Ethical and Trustworthy KE

* Ethics, trust, and privacy in knowledge representation and reasoning

* Explainable AI

* Provenance, trust, and transparency in knowledge management

* FAIR data and FAIR knowledge

* Inclusivity and diversity in knowledge representation

* Ontologies for trust and ethics

* Policies for ownership, management and usage of knowledge




### Social and Cognitive Aspects of KE

* Knowledge representation inspired by cognitive science

* Synergies between humans and machines

* Knowledge emerging from user interaction and (social) networks

* Knowledge ecosystems

* Collaborative and social approaches to knowledge management and acquisition

* Hybrid Humani-AI approaches to KE




### Knowledge Discovery and Acquisition

* Data and text mining for knowledge construction

* Classification and clustering for knowledge management

* Mining patterns and association rules

* Formal Concept Analysis and extensions

* Neuro-symbolic, GenAI and AI agent-based methodologies and architectures for knowledge discovery and acquisition

* Knowledge graph extension, link prediction




### Domain-specific Applications

* eGovernment and public administration

* Life sciences, health, and medicine

* Humanities and Social Sciences

* Cultural Heritage, Media and Digital Libraries

* ICT4D (Knowledge in the developing world)

* Manufacturing and automotive industry (Industry 4.0/5.0)



## CONTRIBUTION TYPES
EKAW-25 distinguishes between research, in-use, and vision papers. The papers will all have the same status and follow the same formatting guidelines in the proceedings but will receive special treatment during the reviewing phase. In particular, each paper type will be subject to its own evaluation criteria:

* Research papers: These are standard papers presenting a novel method, technique, or analysis with appropriate empirical or other types of evaluation as a proof-of-concept. We also welcome papers that reproduce previous studies, as well as papers that report on negative findings derived through a sound methodological approach. The main evaluation criteria will be originality, novelty with respect to state of the art, technical soundness,  methodological clarity and validation.

* In-use papers: These are papers describing knowledge management and engineering applications in real environments. Applications must address a sufficiently interesting and challenging problem, work with real-world data, and involve real users. The focus is less on the originality of the approach and more on presenting systems that solve a significant problem while addressing the particular challenges that come with the use of real-world data. Evaluations are essential for this type of paper and should involve a representative subset of the actual users of the system. The main evaluation criteria will be the contribution of the knowledge engineering approach to solving the real-world problem, potential for (re)using the same approach in other use cases or contexts, technical soundness,  methodological clarity and real-world validation with actual users. 

* Vision papers: Along the lines of this year’s special theme, we invite papers discussing how major technological advances will impact our field within the next 10+ years, including both opportunities and challenges. Vision papers may ask questions such as:  What is our role in AI? What are new frontiers brought about by the new AI landscapes forming? How can knowledge engineering alleviate limitations in other types of AI approaches, such as generative AI or agentic AI? What are novel requirements for “high-quality” knowledge in neuro-symbolic AI architectures? Vision papers must be firmly grounded in the state-of-the-art but may then contain an element of hypothesising and discussing potential future developments, which should be justified with realistic arguments, but may be of a more blue-sky nature.  The main evaluation criteria will be the relevance and significance of the problem or opportunity discussed, grounding in current state-of-the-art, soundness of the argumentation,  clarity and potential impact of the ideas and vision proposed.


##SUBMISSIONS AND PUBLICATIONS

Pre-submission of abstracts is a strict requirement.
All papers and abstracts have to be submitted electronically via EasyChair: [https://easychair.org/conferences/?conf=ekaw2026](https://easychair.org/conferences/?conf=ekaw2026).

As in [past editions](https://link.springer.com/conference/ekaw), accepted papers will be published by Springer in an LNAI volume. Submissions must be in PDF, formatted in the style of LNCS conference proceedings. For details and available templates (Latex, Microsoft Word), see the [Springer’s conference proceedings guidelines](https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines).

Submissions must be in English and must be prepared for single-blind review. Manuscripts that are already uploaded on Arxiv but not published anywhere are allowed for submission. However, dual submissions are not allowed.

Neither plagiarism nor self-plagiarism is tolerated, nor double-submissions (i.e., content currently under review for this or any other venue). Please be advised that a plagiarism-checking tool may be applied to screen for plagiarism.

The following page limits (references excluded) apply:

* Research and In-use papers: 15 pages;

* Vision papers: 8 pages.


Large Language Models Policy of EKAW-26: We adopt the principles and guidelines stated in the [ACM Policy on Authorship](https://www.acm.org/publications/policies/new-acm-policy-on-authorship) specifically about “Criteria for Authorship” regarding the use of Generative AI technologies for authoring papers:

* “Generative AI tools and technologies, such as ChatGPT, may not be listed as authors of an ACM published Work. 

* The use of generative AI tools and technologies to create content is permitted but must be fully disclosed in the Work. For example, the authors could include the following statement in the Acknowledgements section of the Work: ChatGPT was utilized to generate sections of this Work, including text, tables, graphs, code, data, citations, etc. If you are uncertain ­about the need to disclose the use of a particular tool, err on the side of caution, and include a disclosure in the acknowledgements section of the Work.

* Basic word processing systems that recommend and insert replacement text, perform spelling or grammar checks and corrections, or systems that do language translations are to be considered exceptions to this disclosure requirement and are generally permitted and need not be disclosed in the Work.”


## REGISTRATION

One full registration for the conference at the regular rate is required for each accepted paper.


## CHAIRS

Eva Blomqvist, Linköping University, Sweden

Marta Sabou, Vienna University of Economics and Business, Austria