Call for Papers: PKAW 2025

Welcome to the 2025 Principle and Practice of Data and Knowledge Acquisition Workshop (PKAW), an integral part of the 22nd Pacific Rim International Conference on Artificial Intelligence (PRICAI 2025).

PKAW 2025 will be held in Wellington, New Zealand, from November 17-18, 2025.

PKAW has served as a vital forum for researchers and practitioners to discuss the latest advancements in knowledge acquisition and machine intelligence (AI). PKAW 2025 continues this focus, encouraging contributions that embrace a multi-disciplinary approach to human and big data-driven knowledge acquisition, AI techniques, and their applications.

Important Dates

• Paper Submission Deadline: 01 August 2025 (UTC-12)
• Acceptance Notification: 15 September 2025
• Camera-ready Submission: 22 September 2025
• Workshop Date: 17-18 November 2025

All deadlines are at the end of the day specified, Anywhere on Earth (UTC-12).

Areas of Interest

We welcome contributions on all aspects of AI, machine learning, knowledge acquisition, data engineering, and management for intelligent systems. Specific areas include, but are not limited to:

• Knowledge Acquisition
  • Fundamental views on knowledge and their impact on the acquisition process.
  • Algorithmic approaches to knowledge acquisition.
  • Tools, techniques for knowledge acquisition, maintenance, and 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 Discovery
  • Knowledge representation learning.
  • Temporal knowledge graphs.
  • Data linkage.
  • Data analytics and mining.
  • Big data acquisition and analysis.
  • Machine learning/deep learning.
  • Semantic Web, Linked Data, and the Web of Data.
• Responsible Data/Knowledge Management and Systems
  • Transparency, explainability, trust, and accountability.
  • Privacy and security.
  • Other ethical concerns.
• Knowledge-aware Applications
  • Question answering.
  • Recommendation systems.
  • Domain-related applications.
• Human-centric Knowledge Engineering
  • Human-machine collaboration, integration, interaction, delegation, and dialog.
  • Hybrid approaches combining knowledge engineering and machine learning.
• Other Topics
  • Experience and lessons learned.
  • Reproducibility and negative results in knowledge engineering.
  • Innovative user interfaces.
  • Crowd-sourcing for data generation and problem-solving.

Paper Submission

• Eligibility: PKAW will not accept papers currently under review or already published elsewhere. Substantially extended versions of previously published work are encouraged.
• Review Process: A single-blind review process will be adopted, meaning authors will not know reviewer identities, but reviewers may infer author identities.
• Format: Submissions must be in PDF format and adhere to the Springer CCIS template. Templates can be found on Springer’s website. Please visit: Springer's Communications in Computer and Information Science (CCIS) Template (Note: The provided link is a general Springer author page; specific templates are usually linked from the conference site or a direct Springer publisher link).
• Length: Main content should not exceed 12 pages (excluding references) for regular papers and 8 pages (excluding references) for short papers.
• Submission Platform: All papers must be submitted electronically through the Microsoft CMT service: PKAW 2025 Paper Submission Site

Contribution Types

• Regular papers (oral presentation)
• Short papers (work in progress, oral presentation)
• Ideas contributions (oral presentation)
• Extended abstracts (oral presentation)
• Posters (paper-based, oral presentation)
• Posters (slide-based, only)
• Presentations (slide-based, only)
• Demos

Publication

Proceedings of PKAW 2025 will be published by Springer as a volume of the Communications in Computer and Information Science (CCIS) series. Papers will be indexed by EI, Scopus, DBLP, SCImago, etc.

Keynote Speaker

• Measuring urban bilateral job-housing balance based on big data: A case study of multiple cities in China
  • Speaker: Associate Professor Zhou He, University of Chinese Academy of Sciences, China

Contact Information

For any questions, please contact:

• Dr. Shiqing Wu: sqwu@cityu.edu.mo
• Dr. Weihua Li: weihua.li@aut.ac.nz

Organizing Committee

• Workshop Chairs: Shiqing Wu, Weihua Li
• Program Chairs: Xiwei (Sherry) Xu, Yanbin Liu
• Publicity Chair: Jing Ma
• Honorary Chairs: Paul Compton, Hiroshi Motoda
• Advisory Committee: Quan Bai, Qing Liu, Byeong Kang, Kenichi Yoshida, Maria R Lee, Deborah Richards
• PC Members: (List available on the conference website)