ODBASE 2019: Final CFP the 18th International Conference on Ontologies, DataBases, and Applications of Semantics

ODBASE 2019 - The 18th International Conference on Ontologies, DataBases,
and Applications of Semantics
22-23 October 2019, Rhodes, Greece
Proceedings will be published by Springer Verlag

•    Dave Lewis, Trinity College Dublin, Ireland
•    Rob Brennan, Dublin City University, Ireland

The conference on Ontologies, DataBases, and Applications of Semantics for
Large Scale Information Systems (ODBASE’19) provides a forum on the use of
ontologies, rules and data semantics in novel applications. Of particular
relevance to ODBASE are papers that bridge traditional boundaries between
disciplines such as artificial intelligence and Semantic Web, databases,
data science, data analytics and machine learning, human-computer
interaction, social networks, distributed and mobile systems, data and
information retrieval, knowledge discovery, and computational linguistics.

The increasing effectiveness and adoption of data-driven AI technologies
into a widening range of applications has thrown a spotlight into the
trustworthiness of such AI applications. Such concerns extend beyond those
of vendors, deployers and users of an AI, interested in its envelope of
performance and reliability, but also wider professional, governmental and
civil society stakeholders who are concerned by the potential impact of
bias, safety, robustness and liability issues. This concern is amplified by
the opaque nature of techniques such as deep machine learning and the ease
with which they can be applied over large varieties of datasets and
therefore impact is many different areas of life. Key to addressing these
concerns, therefore, is transparency in how data is collected, selected and
prepared in training and using AI and how these processes can be governed,
not just within organisations, but in concert with external stakeholders.
Ontologies and semantic models are powerful techniques for representing,
exchanging and controlling the processing of data for AI applications. They
can be used to define and monitor integration mappings between data sets
that train AI. They can track the provenance and quality assessments of
data selected for training AI. They can be used to track and compare the
selection of data in different linguistic and societal settings to ensure
AI is developed in a fair, unbiased and inclusive manner. They can be used
for tracking and explaining the processing of personal data in AI, which is
increasingly a requirement for data protection regulation. They can be used
to assess the value of datasets and the contributions to that value made by
individual stakeholders. They can be used by communities to assemble and
share information about applications of AI, to inform approaches to the
ethical use of AI and thereby establish trust. In all these areas semantic
models offer a promising basis for establishing sector-specific or
international standards for interoperable data governance in AI

ODBASE’19 intends to draw a highly diverse body of researchers and
practitioners by being part of the Federated conferences Event "On the Move
to Meaningful Internet Systems 2019 (OnTheMove'19)" that co-locates three
conferences: ODBASE'19, C&TC'19 (International Symposium on Secure Virtual
Infrastructures), and CoopIS'19 (International Conference on Cooperative
Information Systems).

ODBASE 2019 will consider two categories of papers: research and
experience. Research papers must contain novel, unpublished research
results. Experience papers must describe performance or usability of
existing real-world systems, empirical studies, business/industry cases
with (proven) solutions/systems for applied technological challenges, and
concrete results demonstrating real-world importance and impact; preference
will be given to papers that describe software products or systems that are
in use in the community and/or the industry.

Specific areas of interest to ODBASE’19 include but are not limited to:

1) Management of Semantically Expressive Information and Knowledge
•    Data governance
•    Knowledge representation and semantic knowledge management
•    Data modeling
•    Data quality
•    Data value assessment
•    Data integration, including transformation rules, ontology matching,
merging, etc.
•    Ontology-based data management, ontology-based data access (OBDA),
linked data management, semantic big data management
•    Ontology and rule engineering and metadata management
•    Governance aspects such as workflows, roles, and responsibilities in
semantic information and knowledge management•
•    The synergy between ontologies & modern databases and business

2) Large Scale and Complex Information Management and Analysis
•    Semantic indexing, search, and query answering and formulation in
large volumes of data
•    Semantic digital curation, semantic annotation, extraction,
enrichment, summarization, and integration
•    Semantic (smart/big) data analytics, data mining, data visualization,
and machine learning
•    Semantic social network analysis
•    Semantic information extraction and text mining
•    Semantics in event-driven architectures, streaming analytics, and
semantic complex event processing

3) Applications, Evaluations, and Experiences of applying ontology, rule,
and database techniques, standards, and tools including but not limited to
the following domains:
•    Semantic Web and Linked Data
•    Corporate Semantic Web (CSW)
•    Semantic enterprise information systems and knowledge management
•    Semantic business process management (SBPM) and decision models
•    Semantic Web and the Internet of Things (IoT)
•    Semantic Web and Human-Computer Interaction (HCI)
•    Crowdsourcing, human computation, and the People Web
•    Pragmatic Web
•    Semantic services and semantic Multi-Agent Systems (MAS)
•    Online social networks and social Semantic Web
•    Personalisation and digital content interaction
•    Hypertext, multimedia, and hypermedia
•    Semantic storytelling and corporate smart content
•    Ubiquitous and mobile information systems
•    Information and data governance, information assurance, security,
•    Semantic cloud computing, edge computing, fog computing
•    Semantic Web applications and tools for, e.g., biomedical and
healthcare domain, eCommerce, eScience, virtual organizations,
4) Industry 4.0
•    Legal ontologies, rules, and reasoning
•    Distributed ledger/blockchain databases, e.g. for rule-based smart
•    Role of mutual impact of society on/by IT (with focus on ontologies
and databases)

•    Conference Paper Submission Deadline: July 15, 2019
•    Acceptance Notification: August 20, 2019
•    Camera Ready Due: Aug 31, 2019
•    Author Registration Due:  Aug 31, 2019

Papers submitted to ODBASE’19 must not have been accepted for publication
elsewhere or be under review for another workshop or conference.

All submitted papers will be carefully evaluated based on originality,
significance, technical soundness, and clarity of expression. All papers
will be refereed by at least three members of the program committee, and at
least two will be experts from industry in the case of practice reports.
All submissions must be in English.

Submissions must not exceed 18 pages in the final camera-ready paper style.
Submissions must be laid out according to the final camera-ready formatting
instructions and must be submitted in PDF format.

Submission link: https://easychair.org/conferences/?conf=otm2019

 The final proceedings will be published by Springer Verlag as LNCS
(Lecture Notes in Computer Science). Author instructions can be found at
•    Failure to comply with the formatting instructions for submitted
papers will lead to the outright rejection of the paper without review.
•    Failure to commit to presentation at the conference automatically
excludes a paper from the proceedings.

PROGRAM COMMITTEE (to be completed)
Ademar Crotti Junior, Trinity College Dublin
Ahmet Soylu, Norwegian University of Science and Technology
Alfredo Maldonado, Adapt Centre - Trinity College Dublin
Carlos A. Iglesias, Universidad Politécnica de Madrid
Christoph Bussler, Google
Christophe Debruyne, Trinity College Dublin
Costin Badica, University of Craiova, Computer and Information Technology
Department, Romania
Cristina Feier, University of Bremen
Csaba Veres, UiB
Diego Calvanese, Free University of Bozen-Bolzano
Dimitris Plexousakis, Institute of Computer Science, FORTH
Dumitru Roman, SINTEF
Evgenij Thorstensen, Dept. of Informatics, University of Oslo
Fabrizio Orlandi, Trinity College Dublin
Georg Rehm, DFKI
George Konstantinidis, University of Southampton
George Vouros, University of Piraeus
Giorgos Stamou, National Technical University of Athens
Guido Governatori, CSIRO
Guohui Xiao, KRDB Research Centre, Free University of Bozen-Bolzano
Harald Sack, FIZ Karlsruhe, Leibniz Institute for Information
Infrastructure & KIT Karlsruhe
Harry Halpin, World Wide Web Consortium
Ioan Toma, STI Innsbruck
Jacek Kopecky, University of Portsmouth
James Hodson, AI for Good Foundation
Jan Jürjens, Fraunhofer Institute for Software & Systems Engineering ISST
and University of Koblenz-Landau
Judie Attard, Trinity College Dublin
Manolis Koubarakis, National and Kapodistrian University of Athens
Markus Stumptner, University of South Australia
Martin Hepp, Universität der Bundeswehr München
Milan Dojchinovski, Czech Technical University in Prague
Nikolay Nikolov, SINTEF
Paul Fodor, Stony Brook University
Simon Scerri, Fraunhofer
Stefano Pacifico
Steffen Lamparter, Siemens AG, Corporate Technology
Sungkook Han, Wonkwang University
Sören Auer, TIB Leibniz Information Center Science & Technology and
University of Hannover
Tiantian Gao, Stony Brook University
Till C. Lech, SINTEF
Tomi Kauppinen, Department of Computer Science, Aalto University School of
Uli Sattler, The University of Manchester
Vadim Ermolayev, Zaporizhzhia National University
Vladimir Alexiev, Ontotext Corp
Witold Abramowicz, Poznan Univ. of Economics

Received on Monday, 8 July 2019 09:41:31 UTC