[CfP] JWS: Community-based KBs and KGs

The Journal of Web Semantics (JWS) invites submissions for a special 
issue on Community-based Knowledge Bases and Knowledge Graphs, edited by 
Tim Finin, Sebastian Hellmann, and David Martin. (contact email: 
cbkb@cs.umbc.edu <mailto:cbkb@cs.umbc.edu>) *Submissions are due by 
November 01, 2021.* Please see the JWS post here: 
http://www.websemanticsjournal.org/2021/06/cfp-community-based-knowledge-bases-and.html 
<http://www.websemanticsjournal.org/2021/06/cfp-community-based-knowledge-bases-and.html>


  Introduction

Community-based knowledge bases (KBs) and knowledge graphs (KGs) are 
critical to many domains. They contain large amounts of information, 
used in applications as diverse as search, question-answering systems, 
and conversational agents. They are the backbone of linked open data, 
helping connect entities from different datasets. Finally, they create 
rich knowledge engineering ecosystems, making significant, empirical 
contributions to our understanding of KB/KG science, engineering, and 
practices.  From here forward, we use "KB" to include both knowledge 
bases and knowledge graphs. Also, "KB" and "knowledge" encompass both 
ontology/schema and data.

Community-based KBs come in many shapes and sizes, but they tend to 
share a number of commonalities:

  *

    They are created through the efforts of a group of contributors,
    following a set of agreed goals, policies, practices, and quality norms.

  *

    They are available under open licenses.

  *

    They are central to knowledge-sharing networks bringing together
    various stakeholders.

  *

    They serve the needs of a community of users, including, but not
    restricted to, their contributor base.

  *

    Many draw their content from crowdsourced resources (such as
    Wikipedia, OpenStreetMap).

Examples of community-based KBs include Wikidata, DBpedia, ConceptNet, 
GeoNames, FrameNet, and Yago. This special issue will highlight recent 
research, challenges, and opportunities in the field of community-based 
KBs and the interaction and processes between stakeholders and the KBs.

We welcome papers on a wide variety of topics. Papers that focus on the 
participation of a community of contributors are especially encouraged.


  Topics of interest

We are looking for studies, frameworks, methods, techniques and tools on 
topics such as the following:

  *

    The impact of community involvement on characteristics of KBs such
    as requirements, design, technology choices, policies, etc.  For
    example, how are KB characteristics driven by the community and
    reflective of the community's needs?

  *

    Conversely, the impact of KB characteristics on community
    involvement. For example, how do changes in these characteristics
    affect the participation and behavior of members of the community?

  *

    Organizational challenges and solutions in developing and managing
    community-based KBs.

  *

    Technical challenges and solutions in community-based KBs,
    concerning a technical area such as:

      o

        Representation of knowledge and logical foundations

      o

        Reasoning, querying, and constraint-checking

      o

        Knowledge acquisition

      o

        Knowledge preparation (e.g., cleaning, deduplication, alignment,
        merging)

      o

        Maintaining consistency with external sources

      o

        Representing and managing metadata (including issues involved in
        adding metadata to relation instances)

      o

        Provenance

      o

        Quality assurance

  *

    User interfaces and experience, both for contributing to the KB and
    using it, by different user groups.

  *

    Implemented metrics and quality tests to guide the community in
    improving KG quality and expanding KG coverage.

  *

    Achieving and managing knowledge diversity, for instance, in the
    form of multilinguality, multi-cultural coverage, multiple points of
    view, and a diverse and inclusive contributor base.

  *

    Detecting and avoiding malicious, inappropriate, and misleading
    content in community-based KBs.

  *

    Biases in community-based KBs and their impact on downstream uses of
    KB content.

  *

    Community-based KBs in science, medicine, law, government, or other
    domains.

  *

    Handling specialized types of knowledge (such as commonsense,
    probabilistic, or linguistic knowledge) in a community setting.

  *

    Methods and tools to manage KB evolution, including change
    detection, change management, conflict resolution, visualization of
    change history.

  *

    Tools and affordances supporting community or collaborative
    activities, including discussions, feedback, decision making, task
    allocation, etc.

  *

    Motivations and incentives affecting community participation.

  *

    Approaches and metrics for community health, including but not
    restricted to community growth or diversity.

  *

    Roles and participation profiles in communities building and
    maintaining KBs.

  *

    Frameworks and approaches to support group decision-making and
    resolve conflicts.


  Types of Papers

We invite submission of Research, Survey, Ontology, and System papers, 
according to the guidelines given at https://www.jws-volumes.com 
<https://www.jws-volumes.com/>.


  Submission Guidelines

The Journal of Web Semantics solicits original scientific contributions 
of high quality. Following the overall mission of the journal, we 
emphasize the publication of papers that combine theories, methods and 
experiments from different subject areas in order to deliver innovative 
semantic methods and applications. 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.

Submission of your manuscript is welcome provided that it, or any 
translation of it, has not been copyrighted or published and is not 
being submitted for publication elsewhere.

Manuscripts should be prepared for publication in accordance with 
instructions given in the JWS guide for authors 
<http://www.elsevier.com/journals/journal-of-web-semantics/1570-8268/guide-for-authors>. 
The submission and review process will be carried out using Elsevier's 
Web-based EM system 
<https://www.editorialmanager.com/JOWS/default.aspx>. Please state the 
name of the SI in your cover letter and, at the time of submission, 
please select “VSI:CBKB” when reaching the Article Type selection.

Upon acceptance of an article, the author(s) will be asked to transfer 
copyright of the article to the publisher. This transfer will ensure the 
widest possible dissemination of information. Elsevier's liberalpreprint 
policy<https://www.elsevier.com/authors/journal-authors/submit-your-paper/sharing-and-promoting-your-article>permits 
authors and their institutions to host preprints on their web sites. 
Preprints of the articles will be made freely accessible viaJWS First 
Look 
<https://papers.ssrn.com/sol3/JELJOUR_Results.cfm?form_name=journalbrowse&journal_id=3169691>. 
Final copies of accepted publications will appear in print and at 
Elsevier's archival online server.


  Important Dates

  *

    Submission deadline: November 1, 2021

  *

    Author notification: February 7, 2022

  *

    Minor revisions due: February 21, 2022

  *

    Major revisions due: March 14, 2022

  *

    Papers appear on JWS preprint server: May 2, 2022

  *

    Publication: Fall or Winter 2022


  Guest Editors

Tim Finin is the Willard and Lillian Hackerman Chair in Engineering and 
a Professor of Computer Science and Electrical Engineering at the 
University of Maryland, Baltimore County (UMBC).


Sebastian Hellmann is the head of the “Knowledge Integration and 
Language Technologies (KILT)" Competence Center at InfAI, Leipzig. He 
also is the executive director and board member of the non-profit 
DBpedia Association with over 30 key players 
<https://www.dbpedia.org/members/overview/>in the knowledge graph area. 
He earned a rank in AMiner’s top 10 of the most influential scholars in 
knowledge engineering of the last decade.


David L. Martinis a Research & Development Scientist in Artificial 
Intelligence.  He has held positions at SRI International, Siri, Inc., 
Apple, Nuance Communications, Samsung Research America, and the 
University of California at Santa Cruz.  He is a Senior Member of the 
Association for the Advancement of Artificial Intelligence, and 
currently works as an independent consultant in Silicon Valley, California.

Received on Thursday, 7 October 2021 05:02:54 UTC