The First IEEE SERVICES Workshop on Knowledge Graph as a Service (KGaaS)

The First IEEE SERVICES Workshop on Knowledge Graph as a Service (KGaaS)

Workshop Chair

Yucong Duan, Hainan University (

Workshop Program Chair

Katsunori Oyama, Nihon University (

Workshop Steering Group

Carl K. Chang, Iowa State University
Peter Chen, Carnegie-Mellon University
Michael Goul, Arizona State University

For general questions about this workshop, please contact the workshop chair or program chair.

Workshop Program

Description & Scope

Everything as a Service (EaaS or XaaS) has followed the development of Software-Defined Everything as stakeholders determine the ultimate culmination of human production of both tangible and intangible services. However, in the light of the overall trend of AI driven conversion from traditional services to intelligent services, prevailing challenges arise for both conceptual foundations and technical preparation, especially involving semantic understanding and utilizations. As Knowledge Graphs are increasingly recognized as an important approach to solving problems related to semantic understanding beyond question and answering systems, various solutions focusing on Knowledge Graphs have been proposed. These cover Knowledge Graph creation, understanding, searching, reasoning, modification and especially and most recently embedding technologies with Machine Learning. A foreseeable AI landscape with explainable and interactive human interactions is becoming feasible based on Knowledge Graphs. The boundaries of the capability of Knowledge Graph usages are constantly expanding, but there are also open questions as to what issues can be solved by Knowledge Graphs alone. Hierarchical architectures which project Data, Information, Knowledge and Wisdom (DIKW) seem to be well paired with the organizing capability of Knowledge Graph technologies in terms of the 5W ( What, Where, When, How and Why). Although not yet formally settled as a uniform concept itself, Knowledge Graphs have been actually or implicitly functioning as Data Graph, Information Graph, Knowledge Graph and Wisdom Graph according to the DIKW hierarchy. Recently we have also seen the emergence of various applications and models of Knowledge Graph as a Service (KGaaS) as a gradual acceleration towards an era of strong AI in contrast to the currently prevailing weak AI. This workshop aims to bring together scientists, researchers, and industrial engineers to discuss and exchange experimental and theoretical results, novel designs, work-in-progress and case studies on theories, design mechanisms and extensions on Knowledge Graph as a Service.

Topics of interest include but are not limited to:

  • Small data learning
  • Knowledge Graph as a Service
  • AI as a Service
  • Explainable Machine Learning Services
  • Knowledge Management and creation in Context-aware and Situation-aware Services
  • Ontology modeling for IR
  • Data acqusition and linking for Edge Computing
  • Information analysis and abstraction for Edge Computing
  • Knowledge creation and reasoning for Edge Computing
  • DIKW architecture-based content/resource processing and service provision
  • Security and Privacy Services based on Knowledge Graphs
  • Load balancing based on transformations among layers of DIKW
  • Edge and Fog Network Services related to DIKW architecture-based
  • Theories and methods for transformations and coordination among layers of DIKW
  • Meta Modeling and formal modeling, and verification methods of semantic rich graphs

Program Committee

Carl K. Chang, Iowa State University
Shizhan Chen, Tianjin University
Wuhui Chen, Sun Yat-Sen University
Peter Chen, Carnegie Mellon University
Christophe Cruz, CNRS-Le2i
Shuiguang Deng, Zhejiang University
Qiang Duan, The Pennsylvania State University
Abdelrahman Osman Elfaki, University of Tabuk
Honghao Gao, Shanghai University
Michael Goul, Arizona State University
Jing He, Swinburne University of Technology
Zhao Li, Alibaba Group
Antonella Longo, University of Salento
Zhihui Lu, Fudan University
Riccardo Martoglia, Universita' di Modena e Reggio Emilia
Hua Ming, Oakland University
Nan Niu, University of Cincinnati
Alexander Norta, Tallinn University of Technology
Katsunori Oyama, Nihon University
Incheon Paik, University of Aizu
Guilin Qi, Southeast University
Lianyong Qi, Qufu Normal University
Stephan Reiff-Marganiec, University of Leicester
Xiaobing Sun, Yangzhou University
Hideyuki Takahashi, Tohoku University
Joe Tekli, Lebanese American University
Gianluigi Viscusi, École Polytechnique Fédérale de Lausanne
Shangguang Wang, Beijing University of Posts & Telecommunications
Bin Xu, Tsinghua University
Gao Yang, Northeastern University
Jingwei Yang, California State University
Jianwei Yin, Zhejiang University
Pengcheng Zhang, Hohai University
Jun Zeng, Chongqing University
Nianjun Zhou, IBM
Zhangbing Zhou, China University of Geosciences