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CKG2018 is concerned with knowledge graphs with contexts, i.e., every fact is enriched by the contexts (e.g., provenance, time, location, or confidence). Contextualized Knowledge Graphs (CKGs) have been gaining importance in the recent years. Research topics include contextualized and distributed Description Logics, annotation of statements in the Semantic Web, and Distributed Knowledge Repositories. Real-world use cases include the creation of collaborative knowledge bases, such as Wikidata, where qualifiers and references can be attached to every statement. This workshop aims to serve as a gathering point for researchers and industry interested in CKGs to discuss current challenges and future solutions, and raise awareness about this emerging topic to a more broader Semantic Web community. This workshop addresses fundamental as well as practical topics including (i) logical models to encode the contextual annotations in the graph, (ii) reasoning and querying over CKGs, (iii) using CKGs in applications such as query answering, data mining, or machine learning, (iv) techniques to benchmark or improve the performance of CKG storage and querying systems. This workshop is complemented by a W3C community on this topic.

The rise of knowledge graphs in the industry over the last decade with Google Knowledge Graph, Facebook’s Entity Graph, Microsoft’s Satori, Apple’s Siri, and Amazon’s True Knowledge has shown the maturity and the high impact of the Semantic technologies. At the same time, we have seen a raise in interest in adding contextual annotations to statements in Knowledge Graphs, with different research communities proposing solutions for representing, reasoning, and querying this knowledge, to actual initiatives to create Knowledge Graphs with contextual annotations, such as Yago, Wikidata, or The Open Knowledge Network.

The Open Knowledge Network (OKN), a community effort led by the Big Data Interagency Working Group (IWG) 10 at NITRD, has the vision to create an open knowledge graph of all public, private, and government sectors. OKN is meant to be an inclusive, open, and community-driven, resulting in a knowledge infrastructure that could facilitate and empower a host of applications and open new research avenues including how to create trustworthy knowledge networks in the form of CKGs. CKGs for answering more complex questions requires the contextual information to be incorporated to the data model. The complex questions are ranging from the macro (have there been unusual clusters of earthquakes in the US in the past six months?) to the micro (what is the best combination of chemotherapeutic drugs for a 56 y/o female with stage 3 glioblastoma and an FLT3 mutation but no symptoms of AML?). While three OKN workshops have been held largely focused on understanding the requirements and building a community, the proposed workshop will be a technical and technological counterpart for OKN workshops.

Remote Connection Info


LOCATION: Oak Shelter room, Asilomar conference hotel.


Phone Dial-in

+1.408.740.7256 (US (San Jose))

+1.888.240.2560 (US Toll Free)

+1.408.317.9253 (US (Primary, San Jose))


File Sharing

Papers and presentations from the CKG workshop is temporarily available at

Workshop Program (tentative)


  • 9:00 - 9:10 Welcome
  • 9:10 - 9:50 Invited talks
    • Denny Vrandečić
    • Aidan Hogan
  • 9:50 - 10:30 Paper presentation
    • 9:50 - 10:10 Provision and Usage of Provenance Data in the WebIsALOD Knowledge Graph
      Sven Hertling and Heiko Paulheim
    • 10:10 - 10:30 i18n-CKG: Considerations in Building Internationalization Contextualized Knowledge Graphs
      Niel Chah
  • 10:30 - 11:00 Morning coffee break
  • 11:00 - 12:20 Paper presentation
    • 11:00 - 11:20 Provenance-Aware LOD Datasets for Detecting Network Inconsistencies
      Leslie F. Sikos, Dean Philp, Shaun Voigt, Catherine Howard, Markus Stumptner, Wolfgang Maye
    • 11:20 - 11:40 The Case for Contextualized Knowledge Graphs in Air Traffic Management
      Christoph G. Schuetz, Bernd Neumayr, Michael Schrefl, Eduard Gringinger, Audun Vennesland, and Scott Wilson
    • 11:40 - 12:00 Personalized Health Knowledge Graph
      Amelie Gyrard, Manas Gaur, Saeedeh Shekarpour, Krishnaprasad Thirunarayan, Amit Sheth
    • 12:00 - 12:20 Contextualization via Qualifiers
      Peter F. Patel-Schneider
  • 12:20 - 14:00 Lunch


  • 14:00 - 14:20 Invited talks
    • Evan Bolton
  • 14:20 - 16:20 Paper presentation
    • 14:20 - 14:40: NELL2RDF: Reading the Web, Tracking the Provenance, and Publishing it as Linked Data
      Jose M. Gimenez-Garcıa, Maısa Duarte, Antoine Zimmermann, Christophe Gravier, Estevam R. Hruschka Jr., and Pierre Maret
    • 14:40 - 15:00: NdProperties: Encoding Contexts in RDF predicates with Inference Preservation
      Jose M. Gimenez-Garcia, Antoine Zimmermann
    • 15:00 - 15:20: Towards capturing contextual semantic information about statements in web tables
      Felipe Quecole, Romao Martines, Jose M. Gimenez-Garcia, and Harsh Thakkar
  • 15:20 - 16:00 Afternoon coffee break
  • 16:00 - 16:20 Paper presentation
    • 16:00 - 16:20: Towards Knowledge-based Systems for GDPR Compliance
      Harshvardhan J. Pandit, Declan O’Sullivan, and Dave Lewis
  • 16:20 - 17:00 Panel discussion
    • Peter F. Patel-Schneider, Nuance
    • Denny Vrandečić, Google
    • Aidan Hogan, Chile
    • Olivier Bodenreider, NLM/NIH
    • Vinh Nguyen, NLM/NIH


  • Dimensions of Context: such as provenance, time, location, confidence, trust, certainty, and etc.
  • Modeling and Representing context on knowledge graphs
  • Logical reasoning over contextualized knowledge graphs
  • Sharing and Linking contextualized knowledge graphs
  • Applications/use cases of contextualized knowledge graphs
  • NLP and ML techniques for extracting facts along with contextual information
  • Question answering over contextualized knowledge graphs
  • Curation and Maintenance of contextualized knowledge graphs
  • Evaluating and optimization of the performance for queries with contexts.
  • Benchmarking contextualized knowledge graphs
  • Compression techniques for contextualized knowledge graphs
  • Mining and learning algorithms with CKG as Background knowledge
  • Publishing models for contextualized knowledge graphs
  • Social media and contextualized knowledge graphs
  • Domain specific knowledge graph and context (esp. Health and biomedicine)

Submissions Guidelines

Paper submission and reviewing for this workshop will be electronic via EasyChair. The papers should be written in English, following the Springer LNCS format, and be submitted in PDF on or before June 1, 2018.

Submission site:

CKG2018 explicitly welcomes alternative and enhanced submission formats, such as communicative online materials. Authors who are preparing such a submission should contact the workshop organizers in advance to make sure we can accommodate for them in the submission and review process. All deadlines are midnight Hawaii time.

The following types of contributions are welcome.

  • Full research papers (8 pages)
  • Position papers (4-6 pages)
  • Short research papers (4-6 pages)
  • System/tool papers (4-6 pages)

We especially welcome the papers describing the datasets and use cases with contextual information such as provenance, time, location, certainty, and probability.

  • Dataset paper (4-6 pages)
  • Usecase paper (4-6 pages)

Accepted papers will be published at the CEUR workshop series.

Important Dates

  • Deadline extended to: June 8, 2018
  • Notification of accepted workshop papers: June 27, 2018
  • Publication of workshop proceedings: August 15, 2018
  • Workshops held: October 9, 2018

Workshop Organizers



Program Committee

  • Olivier Bodenreider, US National Library of Medicine.
  • Paolo Bouquet, Università degli Studi di Trento.
  • Kalpa Gunaratna, Wright State University.
  • Aidan Hogan, Universidad de Chile.
  • Katja Hose, Aalborg University.
  • Lucie-Aimée Kaffee, University of Southampton.
  • Sarasi Lalithsena, Wright State University.
  • Kody Moodley, Maastricht University.
  • Sujan Perera, IBM Watson.
  • Alessandro Piscopo, University of Southampton.
  • Satya Sahoo, Case Western Reserve University.
  • Luciano Serafini, Fondazione Bruno Kessler.
  • Harsh Thakkar, University of Bonn.
  • Krishnaprasad Thirunarayan, Wright State University.
  • Antoine Zimmermann, École des Mines de Saint-Étienne.

Invited talks

  • Denny Vrandečić, Google
  • Aidan Hogan, Chile
  • Evan Bolton, NCBI/NLM/NIH (remote participation)

Panel discussion

  • Peter F. Patel-Shneider, Nuance
  • Denny Vrandečić, Google
  • Aidan Hogan, Chile
  • Olivier Bodenreider, NLM/NIH
  • Vinh Nguyen, NLM

CKG Community