- From: Basil Ell <bell@techfak.uni-bielefeld.de>
- Date: Thu, 3 Sep 2020 09:48:40 +0200
- To: semantic-web@w3.org
- Message-ID: <2d35985d-a95b-3410-3e0b-23d13394eded@techfak.uni-bielefeld.de>
** Apologies for multiple postings ** Only a couple of days left until the extended deadline: *September 8th, 2020* ****************************************************** FINAL CALL FOR PAPERS 2nd Workshop on Semantic Explainability (SemEx 2020) Co-located with the 19th International Semantic Web Conference (ISWC 2020) Venue: Virtual Date: November 2 or 3, 2020 Website: http://www.semantic-explainability.com/ ****************************************************** IMPORTANT DATES Paper Submission Deadline: September 8, 2020 Notification of Acceptance: September 30, 2020 Workshop: November 2 or 3, 2020 ****************************************************** OVERVIEW In recent years, the explainability of complex systems such as decision support systems, automatic decision systems, machine learning-based/trained systems, and artificial intelligence in general has been expressed not only as a desired property, but also as a property that is required by law. For example, the General Data Protection Regulation’s (GDPR) „right to explanation“ demands that the results of ML/AI-based decisions are explained. The explainability of complex systems, especially of ML-based and AI-based systems, becomes increasingly relevant as more and more aspects of our lives are influenced by these systems‘ actions and decisions. Several workshops address the problem of explainable AI. However, none of these workshops has a focus on semantic technologies such as ontologies and reasoning. We believe that semantic technologies and explainability coalesce in two ways. First, systems that are based on semantic technologies must be explainable like all other AI systems. In addition, semantic technologies seem predestined to support rendering systems that are not based on semantic technologies explainable. Turning a system that already makes use of ontologies into an explainable system could be supported by the ontologies, as ideally the ontologies capture some aspects of the users‘ conceptualizations of a problem domain. However, how can such systems make use of these ontologies to generate explanations of actions they performed and decisions they took? Which criteria must an ontology fulfill so that it supports the generation of explanations? Do we have adequate ontologies that enable to express explanations and enable to model and reason about what is understandable or comprehensible for a certain user? What kind of lexicographic information is necessary to generate linguistic utterances? How to evaluate a system‘s understandability? How to design ontologies for system understandability? What are models of human-machine interaction where the system enables to interact with the system until the user understood a certain action or decision? How can explanatory components be reused with other systems that they have not been designed for? Turning systems that are not yet based on ontologies but on sub-symbolic representations/distributed semantics such as deep learning-based approaches into explainable systems might be supported by the use of ontologies. Some efforts in this field have been referred to as neural-symbolic integration. This workshop, the second workshop on semantic explainability, aims to bring together international experts interested in the application of semantic technologies for explainability of artificial intelligence/machine learning to stimulate research, engineering and evaluation – towards making machine decisions transparent, re-traceable, comprehensible, interpretable, explainable, and reproducible. Semantic technologies have the potential to play an important role in the field of explainability since they lend themselves very well to the task, as they enable to model users‘ conceptualizations of the problem domain. However, this field has so far only been only rarely explored. ****************************************************** TOPICS OF INTEREST Topics of interest include, but are not limited to: – Explainability of machine learning models based on semantics/ontologies – Exploiting semantics/ontologies for explainable/traceable recommendations – Explanations based on semantics/ontologies in the context of decision making/decision support systems – Semantic user modelling for personalized explanations – Design criteria for explainability-supporting ontologies – Dialogue management and natural language generation based on semantics/ontologies – Visual explanations based on semantics/ontologies – Multi-modal explanations using semantics/ontologies – Interactive/incremental explanations based on semantics/ontologies – Ontological modeling of explanations and user profiles – Real-world applications and use cases of semantic/ontologies for explanation generation – Approaches to human expertise/knowledge capture for use in semantic/ontology based explanation generation ****************************************************** AUTHOR INSTRUCTIONS We invite research papers and demonstration papers, either in long (16 pages) or short (8 pages) format. All papers have to be submitted electronically via EasyChair: https://easychair.org/conferences/?conf=semex2020 All research submissions must be in English, and no longer than 16 pages for long papers, and 8 pages for short papers (including references). Submissions must be in PDF, formatted in the style of the Springer Publications format for Lecture Notes in Computer Science (LNCS). For details on the LNCS style, see Springer’s Author Instructions: http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0 Accepted papers will be published as CEUR workshop proceedings. At least one author of each accepted paper must register for the workshop and present the paper there. ****************************************************** WORKSHOP ORGANIZERS – Philipp Cimiano – Bielefeld University – Basil Ell – Bielefeld University, Oslo University – Agnieszka Lawrynowicz – Poznan University of Technology – Laura Moss – University of Glasgow – Axel-Cyrille Ngonga Ngomo – Paderborn University ****************************************************** PROGRAM COMMITTEE Ahmet Soylu – Norwegian University of Science and Technology / SINTEF Digital, Norway Andreas Harth – University of Erlangen–Nuremberg, Germany Anisa Rula – University of Milano – Bicocca, Italy Axel-Cyrille Ngonga Ngomo – Paderborn University, Germany Axel Polleres – Wirtschaftsuniversität Wien, Austria Basil Ell – Bielefeld University, Germany and University of Oslo, Norway Benno Stein – Bauhaus-Universität Weimar, Germany Christos Dimitrakakis – Chalmers University of Technology, Sweden Ernesto Jimenez-Ruiz – The Alan Turing Institute, UK Francesco Osborne – The Open University, UK Gong Cheng – Nanjing University, China Heiko Paulheim – University of Mannheim, Germany Heiner Stuckenschmidt – University of Mannheim, Germany Jürgen Ziegler – University of Duisburg-Essen, Germany Mariano Rico – Universidad Politécnica de Madrid, Spain Maribel Acosta – Karlsruhe Institute of Technology, Germany Martin G. Skjæveland – University of Oslo, Norway Michael Kohlhase – Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany Pascal Hitzler – Wright State University, USA Philipp Cimiano – Bielefeld University, Germany Ralf Schenkel – Trier University, Germany Serena Villata – Université Côte d’Azur, CNRS, Inria, I3S, France Stefan Schlobach – Vrije Universiteit Amsterdam, The Netherlands Steffen Staab – University of Koblenz-Landau, Germany -- Dr. Basil Ell AG Semantic Computing Bielefeld University Bielefeld, Germany CITEC, 2.311 +49 521 106 2951
Received on Thursday, 3 September 2020 07:48:59 UTC