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[CFP] Data Journal Special Issue "Semantics in the Deep: Semantic Analytics for Big Data"

From: <kotsomit@ceid.upatras.gr>
Date: Wed, 11 Jul 2018 17:32:56 +0300
To: <kotsomit@ceid.upatras.gr>
Message-ID: <004701d41924$13f5a610$3be0f230$@ceid.upatras.gr>
**apologies for cross-postings**

                                Call for papers
                         Data Journal Special Issue on
            "Semantics in the Deep: Semantic Analytics for Big Data"

       21/9/2018: Abstract submission, 2/11/2018: full submission deadline

The wide availability of information on the Internet, storage space, and
web-generated content put still more impetus on devising applications that
would take advantage of such unprecedented resources, but would also stand
up to the challenges posed by processing and value extraction out of big
data. Now that big data have become everyday data, two fundamental questions
naturally arise:
- How can semantic technologies contribute towards big data analysis?
- What is the relationship between Semantic Web logical formalisms and
automated- and deep-learning techniques?
The aim of this Special Issue is to put emphasis on big data analysis and,
more specifically, on how semantics-aware applications can contribute in
this field. The interplay between the logical formalisms of the Semantic Web
and automated learning and deep learning techniques is currently an open
research topic for both technologies to achieve their next step and forms
the state-of-the-art in this area. In this sense, there are numerous open
problems, ranging from efficient ontological processing of big data
ontologies to knowledge graphs maintenance to ontology evolvement with
machine learning techniques.

Following the theme of SEDSEAL 2018, this special issue solicits
contributions to the open problems above, such as innovative techniques,
tools, case studies, comparisons, and theoretical advances. The papers
should consider and present contributions towards how Semantic Web
technologies can help to implement and enhance big data analytics. This can
be achieved either by extracting value out of these data (e.g., through
reasoning), creating sustainable ontology models, offering a solid
foundation for deploying learning techniques or anything in between. In
particular, topics of interest include, but are not limited to, the

Ontologies for big data
Semantic applications in big data domains including:
open datasets, linked data, scholarly information, e-learning
economics, insurance, sensors, bioinformatics
Reasoning approaches for knowledge extraction
Ontology learning and topic modeling
NLP and word embedding
Semantic deep learning
Semantic lakes and blockchain
OBDA approaches for big data access
Data Science and semantics
Evaluation techniques
Semantic deep learning
Ontologies as training sets
Ontology evolution and learning feedback
Scalability issues

Manuscripts should be submitted online at www.mdpi.com. Submitted
manuscripts should not have been published previously, nor be under
consideration for publication elsewhere (except conference proceedings
papers). All manuscripts are thoroughly refereed through a single-blind
peer-review process.
Authors are encouraged to send a short abstract and tentative title to guest
editor Dr. Dimitrios Koutsomitropoulos at the email address found here:
Guidelines for authors are available at this page:
The Article Processing Charge (APC) is waived for well-prepared manuscripts
submitted to this issue. Submitted papers should be well formatted and use
good English. 

Guest Editors
Dr. Dimitrios A. Koutsomitropoulos
Department of Computer Engineering & Informatics, University of Patras,

Prof. Dr. Spiridon D. Likothanassis
Department of Computer Engineering & Informatics, University of Patras,

Prof. Dr. Panos Kalnis
Computer, Electrical and Mathematical Science and Engineering Division, King
Abdullah University of Science and Technology, Saudi Arabia

Important Dates

21/9/2018: Abstract submission
2/11/2018: Manuscript submission deadline
7/1/2019: Author Notification
11/2/2019: Final Revisions
Spring 2019: Special Issue Publication

Editorial Review Board (TBC)
Andreas Andreou, Cyprus University of Technology, Cyprus
Christos Alexakos, University of Patras, Greece
Dimitrios Tsolis, University of Patras, Greece
Dimitrios Tzovaras, CERTH/ITI, Greece
Efstratios Georgopoulos, Technological Institute of Kalamata, Greece
Filipe Portela, University of Minho, Portugal
Jouni Tuominen, University of Helsinki, Finland
Konstantinos Votis, CERTH/ITI, Greece
Miguel-Angel Sicilia, University of Alcala, Spain
Minjuan Wang, San Diego State University, US
Vassilis Plagianakos, University of Thessaly, Greece
Received on Wednesday, 11 July 2018 14:34:13 UTC

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