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

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

CALL FOR PAPERS
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 extends beyond those of vendors, deployers and users of an AI, interested in its envelop 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 applies 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 use 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 use by communities to assemble and share information about applications of AI, to inform approaches to 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 applications.

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.

TOPICS OF INTEREST
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•
• Synergy between ontologies & modern databases and business intelligence

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 story telling and corporate smart content
• Ubiquitous and mobile information systems
• Information and data governance, information assurance, security, compliance
• 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 contracts
• Role of mutual impact of society on/by IT (with focus on ontologies and databases)


IMPORTANT DATES
• Conference Abstract Submission Deadline: July 07, 2019 (recommended)
• Conference Paper Submission Deadline: July 15, 2019
• Acceptance Notification: August 20, 2019
• Camera Ready Due: Aug 31, 2019
• Author Registration Due: Aug 31, 2019

SUBMISSION GUIDELINES
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 site and instructions: http://www.otmconferences.org/index.php/paper-submission

The final proceedings will be published by Springer Verlag as LNCS (Lecture Notes in Computer Science). Author instructions can be found at: http://www.springer.de/comp/lncs/authors.html
• 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 Science
Uli Sattler, The University of Manchester
Vadim Ermolayev, Zaporizhzhia National University
Vladimir Alexiev, Ontotext Corp
Witold Abramowicz, Poznan Univ. of Economics