CFP Semantic Web Journal : Special Issue on Industrial Applications of Semantic Web Technologies

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                                              CALL FOR PAPERS
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The journal *Semantic Web – Interoperability, Usability, Applicability*
(published and printed by IOS Press, ISSN: 1570-0844), in short *Semantic
Web journal*, brings together researchers from various fields which share
the vision and need for more effective and meaningful ways to share
information across agents and services on the future internet and
elsewhere.


In this Special issue (
http://www.semantic-web-journal.net/blog/call-papers-special-issue-industrial-applications)
we invite submissions that illustrate the use and impact of Semantic Web
technologies in industry. A large number of companies are intently focused
on embedding intelligence into all aspects of their business, from the
consumer products and services on offer to their own internal processes and
logistic operations. The technological challenges and solutions required to
realize this goal are vast and varied, but those related to the following
areas are of particular interest for this Special Issue:

    Autonomous Systems - systems that have a high level of self-governance
with respect to sensing, perception, reasoning, learning, decision-making
and action.
    Connected Systems - systems and technologies that lay the foundations
of an Internet of Things
    Human-machine Interaction - multimodal interfaces between users and
computer systems
    User-centric Computing - intuitive, interactive and intelligent
user-centric systems that enable a seamless user-experience for products
and services.

In particular, we are interested in use cases focusing on cyber-physical
systems that utilize and combine semantic technologies with the Internet of
Things (IoT), cloud computing, cognitive computing, robotics, etc. in order
to drive the digital transformation of industry and industrial applications.
If data exchange and interoperability have always played an important role
in industrial information management, their criticality has become even
more prominent in Industry 4.0: in fact, cyber-physical systems require
distributed processing and ubiquitous computing, and ensuring consistency
and coherence in the information workflow, up to the service level, is of
paramount importance for industrial applications.

Semantic data modeling, with its different methodologies and tools,
represents in and of itself a core application of Semantic Web technologies
in industry, and it’s also important for the functionalities it enables,
i.e. automatic reasoning and validation: these functionalities, in
combination with machine learning algorithms and deep network
infrastructures, are transforming the value chain further, by introducing
AI-based analytics into the industrial ecosystem.

In addition to success stories, this Special Issue also welcomes papers
that justifiably demonstrate and expose the current deficiencies (or
failures) of Semantic Web technologies in relation to the above stated
challenges.

Topics include, but are not limited to:

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Topics of Interest
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    Knowledge Graphs
        Creation and maintenance
        Cross domain integration
        Deployment and utilization of knowledge graphs
    Standard ontologies and vocabularies for industry
    Ontology Management tools at scale
    Semantic Web Services
    Inference and Reasoning
    Ontology-based Data Access
    Knowledge-based Artificial Intelligence: integration between machine
learning algorithms and semantic web technologies
    Obstacles and challenges related to large-scale adoption of semantic
technologies in Industry.
    Impact of semantic technologies in addressing business problems
    Deficiencies of Semantic Web technologies for industrial applications
    Use of semantic technologies for question answering and digital
assistance/virtual assistants
    Challenges associated with monetization and commercialization of
Semantic technologies.
    Success stories and challenges associated with use of SPARQL querying
systems within Industrial settings
    Integration of heterogeneous datasets within Industrial settings using
Semantic Web technologies
    Linked data reuse and consumption within Industrial settings


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Important Dates
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Submission deadline: 30 September 2018.

Papers submitted before the deadline will be reviewed upon receipt.


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Submission
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Submissions shall be made through the Semantic Web journal website at
http://www.semantic-web-journal.net. Prospective authors must take notice
of the submission guidelines posted at http://www.semantic-web-
journal.net/authors.

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
http://www.semantic-web-journal.net/authors#types. 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. When submitting, please indicate in the cover letter that it is for
the Special Issue on Industrial Applications and the chosen submission
type. 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 swj-industrial-issue@googlegroups.com



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Guest Editors:
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Alessandro Oltramari, Bosch Research and Technology Center, Pittsburgh (USA)
Cory Henson, Bosch Research and Technology Center, Pittsburgh (USA)
Prateek Jain, AppZen, San Jose (USA)



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Guest Editorial Board
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William Jarrold, Nuance Communications
Mariana Damova, Mozaika
Steven Gustafson, Maana
Peter Z. Yeh, Nuance Communications
Charles Ortiz, Nuance Communications
Vijayaraghava Mutharaju, GE Global Research
Stefan Schmid, Bosch Research
Sarasi Lalithsena, IBM Research
Varish Mulwad, GE Global Research
Stefano Borgo, ISTC-CNR
John Hodges Jr, Siemens
Peter Haase, Metaphacts
Anna Tordai, Elsevier
Andreas Thalhammer, Roche
(to be completed)


-- 
Prateek
Jain
http://prateekjain.name/