PKAW (Principle and Practice of Data and Knowledge Acquisition Workshop) was established in 1980s as an integral part of PRICAI (Pacific Rim International Conference on Artificial Intelligence). PKAW 2026 will be held at the 23rd Pacific Rim International Conference on Artificial Intelligence (PRICAI 2026) in Guangzhou, China. A wide range of topics related to knowledge acquisition and representation are greatly welcome.

Important Dates

Topics of Interest

All aspects of AI, machine learning, knowledge acquisition, data engineering and management for intelligent systems, including (but not restricted to):

• Knowledge Acquisition
  • Fundamental views on knowledge that affect the knowledge acquisition process and the use of knowledge in knowledge engineering
  • Algorithmic approaches to knowledge acquisition
  • Tools and techniques for knowledge acquisition, knowledge maintenance and knowledge validation
  • Evaluation of knowledge acquisition techniques, tools and methods.
  • Ontology and its role in knowledge acquisition
  • Knowledge acquisition applications tested and deployed in real-life settings
• Knowledge Representation and Discovering
  • Knowledge representation learning
  • Temporal knowledge graph
  • Data linkage
  • Data analytics and mining
  • Big data acquisition and analysis
  • Machine learning/deep learning
  • Semantic Web, the Linked Data and the Web of Data
• Responsible Data/Knowledge Management and System
  • Transparency, explainability, trust, and accountability
  • Privacy and security
  • Other ethical concerns
• Knowledge-aware Application
  • Question answering
  • Recommendation system
  • Domain-related application
• Human-centric Knowledge Engineering
  • Human-machine collaboration, integration, interaction, delegation, dialog
  • Hybrid approaches combining knowledge engineering and machine learning
• Other Topics
  • Experience and Lesson learned
  • Reproducibility and negative results of knowledge engineering
  • Innovative user interfaces
  • Crowd-sourcing for data generation and problem solving

submission instruction

Please use the below links to download the Springer template and to submit your work. The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.

PKAW will not accept any paper that, at the time of submission, is under review for, has already been published in, or has already been accepted for publication in, a journal or another venue with formally published proceedings. If part of the work has been previously published, authors are strongly encouraged to cite and compare/contrast the new contributions with the parts that were already published before. The paper must substantially extend the previously published work.

PKAW 2026 will adopt single-blind rule for the reviewing process, i.e., the authors do not know the names of the reviewers, but the reviewers can infer the names of the authors from the submission.

All papers for the review should be submitted electronically using the conference management tool in PDF format and formatted using the Springer LNCS template. The main content of the paper should not exceed 16 pages long (including references). For accepted papers, the latex source files and a camera-ready version are required to be submitted using the Springer LNCS template.

Contacts

For any questions, please contact Dr. Shiqing Wu (sqwu@cityu.edu.mo) and Dr. Weihua Li (weihua.li@aut.ac.nz).