The 20th International Conference on Knowledge Engineering and Knowledge Management is concerned with the impact of time and space on the representation of knowledge. Knowledge engineering has mostly been about creating static, universal representations. Yet the world is rarely static: everything changes, including the models, and real world systems need to evolve along with the surrounding world. Also, what makes some representations valid in some contexts may make them invalid elsewhere (e.g., jurisdiction for laws).

The special focus of this year's EKAW is "evolving knowledge", which concerns all aspects of the management and acquisition of knowledge representations of evolving, contextual, and local models. This includes change management, trend detection, model evolution, streaming data and stream reasoning, event processing, time-and space dependent models, contextual and local knowledge representations, etc.

EKAW 2016 will put a special emphasis on the evolvability and localization of knowledge and the correct usage of these limits.

Proceedings
The proceedings of the research track will be published by Springer Verlag in the LNCS series.

The authors of selected best papers will be invited to submit an extended version of their manuscript to a special issue of the Semantic Web Journal by IOS Press.

Best paper award
Research and in-use papers are eligible for the Bob Wielinga Best Paper Award sponsored by Springer Nature that will award a prize of 1,000 euros to the best paper of the main track.

Topics of interest
EKAW 2016 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 relevant with regard to the following topics:

Knowledge in evolving and local contexts
Model evolution
Ontology evolution
Ontology debugging
Ontology change management and versioning
Ontology usage trends
Methods and methodologies for time awareness
Modelling of time-indexed knowledge
Ontology design patterns for time-indexed knowledge
Reasoning over time-indexed knowledge
Stream processing and stream reasoning
Event processing
Methods and methodologies for context awareness
Modelling of contextualised knowledge
Ontology design patterns for representing context
Reasoning with context
Context-aware knowledge-based applications
Lessons learned from case studies
Knowledge management in large organisations
Adoption of semantic web technologies
Maintenance of corporate knowledge repositories
Applications in specific domains 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)
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
Methods for accelerating take-up of knowledge management technologies
Corporate memories for knowledge management
Evolution, maintenance and preservation of knowledge
Web 2.0 technologies for knowledge management
Incentives for human knowledge acquisition (e.g. games with a purpose)
Knowledge Engineering and Acquisition
Tools and methodologies for ontology engineering
Ontology design patterns
Ontology localisation
Ontology alignment
Knowledge authoring and semantic annotation
Knowledge acquisition from non-ontological resources (thesauri, folksonomies etc.)
Semi-automatic knowledge acquisition, e.g., ontology learning
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
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
Trust and privacy in knowledge representation
Collaborative and social approaches to knowledge management and acquisition
Crowdsourcing in knowledge management
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 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: July 8, 2016
Submission deadline: July 15, 2016
Notification of acceptance: September 8, 2016
Camera-ready paper: September 26, 2016
Conference days: November 19-23, 2016
Submissions
Pre-submission of abstracts is a strict requirement. All papers and abstracts have to be submitted electronically via EasyChair.

All research and in-use submissions must be in English, and no longer than 15 pages. Papers that exceed this limit will be rejected without review.

Submissions must be either in PDF or in HTML, 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. For details on the HTML format, see the HTML submission guide.