[agents] Special issue of the Journal of Web Semantics on Community-based Knowledge Bases & Knowledge Graphs

[Tim Finin]

The Journal of Web Semantics (JWS) invites submissions for a special issue
on Community-based Knowledge Bases and Knowledge Graphs
<http://www.websemanticsjournal.org/2021/06/cfp-community-based-knowledge-bases-and.html>,
edited by Tim Finin, Sebastian Hellmann, and David Martin. (Contact email
for the special issue: cbkb at cs.umbc.edu.) *The deadline has been extended, *and
submissions are now* due by January 11, 2022.*
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:
   -

      Representation of knowledge and logical foundations
      -

      Reasoning, querying, and constraint-checking
      -

      Knowledge acquisition
      -

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

      Maintaining consistency with external sources
      -

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

      Provenance
      -

      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 and *Submission Guidelines*

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


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 the
copyright of the article to the publisher. This transfer will ensure the
widest possible dissemination of information. Elsevier's liberal preprint
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 via JWS 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*
These dates are extended by 10 weeks from the timeline of the original
announcement.

   -

   Submission deadline: January 10, 2022
   -

   Author notification: April 18, 2022
   -

   Minor revisions due: May 2, 2022
   -

   Major revisions due: May 23, 2022
   -

   Papers appear on JWS preprint server: July 11, 2022
   -

   Publication: 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. Martin is a Software
Engineer and Research & Development Scientist in Artificial Intelligence.
He has recently joined the staff of the Wikimedia Foundation and has
previously 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.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <https://lists.cs.umbc.edu/pipermail/agents/attachments/20211205/3b24c895/attachment-0001.html>