Call for Papers: Special Issue on Knowledge Graphs Validation and Quality

Call for papers: Special Issue on

Knowledge Graphs Validation and Quality

There has been a rise in the number of knowledge graphs, including some of the most popular such as YAGO, DBpedia, Wikidata, and the Google Knowledge Vault. Knowledge graphs store millions of statements about entities of interest in a domain, for instance, people, places, organisations and events. They are extensively used in various AI contexts, from search and natural language processing to data integration, as a means to add context and depth to machine learning and generate human-readable explanations.

Although building and using knowledge graphs is important, they give rise to quality concerns which may be a limitation to their usage. Independently of the (kinds of) source(s) from which a knowledge graph is created, data extracted for the initial knowledge graph will usually be incomplete, and will contain duplicate, contradictory or even incorrect statements – especially when taken from multiple sources. Assessing the quality of the resulting knowledge graphs is a crucial step. By quality, we here refer to fitness for purpose. Quality assessment then helps to ascertain for which purposes a knowledge graph can be reliably used.

To objectively assess the quality of knowledge graphs, we need more effective methods than those proposed by the state of the art. To guarantee and to ensure that our knowledge graph is of a certain quality we need to assess quality at both instance and schema level. There are several approaches to describe and validate knowledge graphs data as well as checking data constraints, which have been proposed and that open new practical applications. This special issue at the Semantic Web Journal seeks original articles describing theoretical and practical methods and techniques for assessing and validating the quality of knowledge graphs. Besides regular scientific papers, the special issue also accepts system papers and use cases descriptions.

Topics relevant to this special issue include – but are not limited to – the following:

  • Validation technologies: ShEx, SHACL, etc.
  • RDF Validation
  • Performance and scalability of validation approaches
  • Knowledge graph quality and data/constraint modelling
  • Constraint/restriction quality and completeness
  • Knowledge graph generation and quality
  • Knowledge graph quality for machine learning applications
  • Emergent and latent knowledge graph data models
  • Enforcing constraints on knowledge graphs
  • Extracting schemas from data
  • Knowledge graph quality
  • Community-based knowledge graphs and quality: Wikidata, DBpedia, YAGO, etc.
  • Quality of enterprise-based knowledge graphs
  • Validation and description of labelled property graphs
  • UX design for validation pipelines
  • Applications of validation languages: summarizing, transformation, subsetting, form generation, etc.
  • Methods for knowledge graph and data cleansing and completion
  • Knowledge graph curation and quality
  • Real-time validation of knowledge graphs
  • Open-world validation at scale
  • Socio-technological concerns of validation across integrated knowledge graphs
  • Trustworthiness assessment
  • Relevant use cases


  • Submission deadline: 23rd of December 2020. Papers submitted before the deadline will be reviewed upon receipt.

Author Guidelines

Submissions shall be made through the Semantic Web journal website at Prospective authors must take notice of the submission guidelines posted at

We welcome four main types of submissions: (i) full research papers, (ii) reports on tools and systems, (iii) application reports, and (iv) survey articles. The description of the submission types is posted at While there is no upper limit, paper length must be justified by content.

Note that you need to request an account on the website for submitting a paper. Please indicate in the cover letter that it is for the "Special Issue on Transport Data on the Web" special issue. All manuscripts will be reviewed based on the SWJ open and transparent review policy and will be made available online during the review process.

Guest editors

The guest editors can be reached at .
Jose Emilio Labra Gayo, University of Oviedo, Spain
Anastasia Dimou, IDLab, Ghent University, Belgium
Katherine Thornton, Yale University Library, USA
Anisa Rula, University of Milano-Bicocca, Italy and University of Bonn, Germany

Guest Editorial Board

Charlie Abela, University of Malta, Malta
Vladimir Alexiev, Ontotext corp., Bulgaria
Jose María Álvarez Rodríguez, University Carlos III Madrid, Spain
Tom Baker, DCMI, Germany
Jerven T. Bolleman, Swiss Institute of Bioinformatics, Switzerland
Nicholas Car, SURROUND, Australia
Remzi Çelebi, Maastricht University, Netherlands
Julien Corman, University of Bolzano, Italy
Leyla Garcia Castro, ZB MED Information Centre for Life Sciences, Germany
Rafael Gonçalves, Stanford University, USA
Gregg Kellogg, USA
Dimitris Kontokostas, Diffbot, Greece
Jakub Klimek, Charles University, Czech Republic
Petr Kremen, Czech Technical University, Czech Republic
Ben De Meester, imec - Ghent University, Belgium
Chris Mungall, Lawrence Berkeley National Laboratory, USA
Eric Prud’hommeaux, Janeiro Digital, USA
Artem Revenko, Semantic Web Company, Austria
Alejandro Rodríguez González, Universidad Politécnica Madrid, Spain
John Samuel, Ecole d'Ingénieurs en Chimie et Sciences du Numérique, France
Ognjen Savković, University of Bolzano, Italy
Harold Solbrig, Johns Hopkins University, USA
Blerina Spahiu, University of Milano-Bicocca, Italy
Sławek Staworko, University of Lille & INRIA, France
Simon Steyskal, Siemens AG Austria, Austria
Houcemeddine Turki, University of Sfax, Tunisia
Andra Waagmeester, Micelio, Belgium
Yasunori Yamamoto, Research Organization of Information and Systems (ROIS), Japan