Journal Information
Journal of Web Semantics (JWS)
Impact Factor:

Call For Papers
The Journal of Web Semantics is an interdisciplinary journal based on research and applications of various subject areas that contribute to the development of a knowledge-intensive and intelligent service Web. These areas include: knowledge technologies, ontology, agents, databases and the semantic grid, obviously disciplines like information retrieval, language technology, human-computer interaction and knowledge discovery are of major relevance as well. All aspects of the Semantic Web development are covered. The publication of large-scale experiments and their analysis is also encouraged to clearly illustrate scenarios and methods that introduce semantics into existing Web interfaces, contents and services. The journal emphasizes the publication of papers that combine theories, methods and experiments from different subject areas in order to deliver innovative semantic methods and applications.

The Journal of Web Semantics addresses various prominent application areas including: e-business, e-community, knowledge management, e-learning, digital libraries and e-sciences.

The Journal of Web Semantics features a multi-purpose web site, which can be found at: Readers are also encouraged to visit the Journal of Web Semantics blog, at for more information and related links.

The Journal of Web Semantics includes, but is not limited to, the following major technology areas:
• The Semantic Web
• Knowledge Technologies
• Ontology
• Agents
• Databases
• Semantic Grid and Peer-to-Peer Technology
• Information Retrieval
• Language Technology
• Human-Computer Interaction
• Knowledge Discovery
• Web Standards

Major application areas that are covered by the Journal of Web Semantics are:
• eBusiness
• eCommunity
• Knowledge Management
• eLearning
• Digital Libraries
• eScience

Each of these areas is covered by an area editor who supports the editors-in-chief. Furthermore, area editors manage the review process for submitted papers in the respective areas.

The Journal of Web Semantics publishes four types of papers:
• Research papers: Research papers are judged by originality, technical depth and correctness, as well as interest to our target readership. Research papers are recommended to have 15 - 25 pages in double column format.
• Survey papers: We rarely accept survey papers, and beyond a sheer enumeration of relevant methods and systems, we expect a substantial technical insight to be gained by a survey paper. Survey papers are recommended to have 15 - 25 pages in double column format.
• Ontology papers: We publish community-oriented description of ontology papers, if they generate interests from real-world users and semantic Web experts. Ontology papers are recommended to have 6 - 8 pages in double column format. Interested authors may here find a detailed Call-for-Ontology papers
• System papers: Widely adopted semantic systems and systems that generate a far above average amount of interest in the Semantic Web community, may be explained in systems papers. Systems papers are recommended to have 6 - 8 pages in double column format.

Shorter or longer papers are allowable, if the objectives of a paper warrant deviating length. Descriptions that are either unnecessarily short or long will negatively impact chances of acceptance.
Last updated by Dou Sun in 2019-11-24
Special Issues
Special Issue on Content Credibility
Submission Date: 2021-01-25

Digital misinformation is becoming pervasive in all online media, and is affecting our perceptions in critical domains, such as health, politics, foreign policy, economy, and environment. In spite of this rising addiction to rapid consumption of online information, people and current technologies are yet to adapt to the proliferation of misinformation. Semantics can play a significant role in battling misinformation, such as by contributing to detection of misinformation content, monitoring its spread and impact, predicting its evolution, identifying misinforming sources, mobilising knowledge graphs to support fact-checking, representing claims and fact-checks. With this special issue, we aim to capture the state of the art in semantic web research towards misinformation. Topics of interest include, but are not limited to: Ontologies for representing rumors, misinformation, disinformation, and other deceptive content Semantic models of misinformation detection Knowledge graphs for integrating and analysing misinformation content Semantic analysis of opinion and sentiment towards misinformation Misinformed-behaviour semantic representation and analysis Detection of information and semantic frame manipulation Semantic similarity of articles with more/less exaggerated/biased content Semantic topic affinity analysis of users sharing unreliable content Semantic extraction of misinforming topics and events Misinformation semantic patterns identification and prediction Semantically-enriched datasets of misinformation content and sources Semantic matching of Fact-Checking misinformation assessment labels Modelling user/information source trustworthiness Semantic annotation standards for misinformation annotation ClaimReview schema usage and structure assessment Semantic applications for tackling the spread of misinformation Using Linked Open Data as a source of factual information
Last updated by Dou Sun in 2020-11-03
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