1st Call for Papers, EKAW 2020, Bolzano Summer of Knowledge, September 16-20, 2020

[Apologies for cross-posting]

===============================================================================
EKAW 2020 CALL FOR PAPERS
https://ekaw2020.inf.unibz.it

Part of the Bolzano Summer of Knowledge 2020
https://summerofknowledge.inf.unibz.it

===============================================================================
RESEARCH, IN-USE AND POSITION PAPERS

The 22nd International Conference on Knowledge Engineering and Knowledge Management concerns all aspects of eliciting, acquiring, modeling and managing knowledge, and the role of knowledge in the construction of systems and services for the semantic web, knowledge management, e-business, natural language processing, intelligent information integration, and so on.

The special theme of EKAW 2020 is "Ethical and Trustworthy Knowledge Engineering". While recent reported breaches relate predominantly to machine learning systems, it is not impossible to envision ethical breaches in knowledge engineering more broadly and, conversely, devise methods and techniques to ensure no or minimal harm in knowledge acquisition, modelling, and knowledge-driven information systems. EKAW 2020 will put a special emphasis on the importance of Knowledge Engineering and Knowledge Management to keep fostering trustworthy systems.


PROCEEDINGS
=============

The proceedings of the research track will be published by Springer Verlag in the Lecture Notes in Artificial Intelligence series.


TOPICS OF INTEREST
==================

EKAW 2020 welcomes papers dealing with theoretical, methodological, experimental, and application-oriented aspects of knowledge engineering and knowledge management.

In particular, but not exclusively, we solicit papers about methods, tools and methodologies on the following topics:

- Ethical and Trustworthy Knowledge Engineering
	* Ethics and trust in automated reasoning
	* Algorithmic transparency and explanations for knowledge-based systems
	* Knowledge and ethics
	* Ontologies for trust and ethics
	* Trust and privacy in knowledge representation
- Knowledge Engineering and Acquisition
	* Tools and methodologies for ontology engineering
	* Ontology design patterns
	* Ontology localisation
	* Multilinguality in ontologies
	* Ontology alignment
	* Knowledge authoring and semantic annotation
	* Knowledge acquisition from non-ontological resources (thesauri, folksonomies, etc.)
	* Semi-automatic knowledge acquisition, e.g., ontology learning
	* Collaborative knowledge acquisition and formalisation
	* Mining the Semantic Web and the Web of Data
	* Ontology evaluation and metrics
	* Uncertainty and vagueness in knowledge representation
	* Dealing with dynamic, distributed and emerging knowledge
- Knowledge Management
	* Methodologies and tools for knowledge management
	* Knowledge sharing and distribution, collaboration
	* Best practices and lessons learned from case studies
	* Provenance and trust in knowledge management
	* FAIR data and knowledge
	* Methods for accelerating take-up of knowledge management technologies
	* Corporate memories for knowledge management
	* Knowledge evolution, maintenance and preservation
	* Incentives for human knowledge acquisition and data quality improvement (e.g. games with a purpose)
- Social and Cognitive Aspects of Knowledge Representation
	* Similarity and analogy-based reasoning
	* Knowledge representation inspired by cognitive science
	* Synergies between humans and machines
	* Knowledge emerging from user interaction and networks
	* Knowledge ecosystems
	* Expert finding, e.g., by social network analysis
	* Collaborative and social approaches to knowledge management and acquisition
	* Crowdsourcing in knowledge management
- Knowledge discovery
	* Mining patterns and association rules
	* Mining complex data: numbers, sequences, trees, graphs
	* Formal Concept Analysis and extensions
	* Numerical data mining methods and knowledge processing
	* Mining the web of data for knowledge construction
	* Text mining and ontology engineering
	* Classification and clustering for knowledge management
	* Symbolic and sub-symbolic learning machine learning 
- Applications in specific domains such as:
	* eGovernment and public administration
	* Life sciences, health and medicine
	* Humanities and Social Sciences
	* Automotive and manufacturing industry
	* Cultural heritage
	* Digital libraries
	* Geosciences
	* ICT4D (Knowledge in the developing world)


TYPE OF PAPERS
===============

We will accept different types of papers. The papers will all have the same status and follow the same formatting guidelines in the proceedings but will receive special treatment during the reviewing phase. In particular, each paper type will be subject to its own evaluation criteria. The Programme Committee will also make sure that there is a reasonable balance of the paper types accepted. At submission time the paper has to be clearly identified as belonging to one of the following categories.

* Research papers: These are standard papers presenting a novel method, technique or analysis with appropriate empirical or other types of evaluation as a proof-of-concept. The main evaluation criteria here will be originality, technical soundness and validation.

* In-use papers: Here we are expecting papers describing applications of knowledge management and engineering in real environments. Applications need to address a sufficiently interesting and challenging problem on real-world datasets, involving many users, etc. The focus is less on the originality of the approach and more on presenting systems that solve a significant problem while addressing the particular challenges that come with the use of real-world data. Evaluations are essential for this type of paper and should involve a representative subset of the actual users of the system.

* Position papers: We invite researchers to also publish position papers, which describe novel and innovative ideas. Position papers may also comprise an analysis of currently unsolved problems, or review these problems from a new perspective, in order to contribute to a better understanding of these problems in the research community. We expect that such papers will guide future research by highlighting critical assumptions, motivating the difficulty of a certain problem or explaining why current techniques are not sufficient, possibly corroborated by quantitative and qualitative arguments.


IMPORTANT DATES
================

* Abstract deadline: April 23, 2020
* Submission deadline: April 30, 2020
* Notification of acceptance: June 23, 2020
* Camera-ready paper: July 2, 2020
* Conference days: September 16-20, 2020

All submission deadlines are 23:59:59 Hawaii Time.


SUBMISSIONS
============

Pre-submission of abstracts is a strict requirement. All papers and abstracts have to be submitted electronically via Easychair.
All submissions for research, in-use, and position papers must be in English, and no longer than 15 pages. Papers that exceed this limit will be rejected without review.

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.


ORGANIZATION
============

General Chairs
* Oliver Kutz (Free University of Bozen-Bolzano, Italy)
* Rafael Penaloza (University of Milano-Bicocca, Italy)

Program Chairs
* Michel Dumontier (Maastricht University, the Netherlands)
* Maria Keet (University of Cape Town, South Africa)

Workshop Chairs
* Anastasia Dimou (Ghent University, Belgium)
* Karl Hammar (Jonkoping University, Sweden)

Posters & Demos
* Daniel Garijo (University of Southern California, USA)
* Agnieszka Lawrynowicz (Poznan University of Technology, Poland)

Publicity
* Rafael Goncalves (Stanford University, USA)

Local Organising Committee
* Pietro Galliani (Free University of Bozen-Bolzano, Italy)
* Guendalina Righetti (Free University of Bozen-Bolzano, Italy)
* Nicolas Troquard (Free University of Bozen-Bolzano, Italy)

Received on Tuesday, 7 January 2020 06:48:20 UTC