Updated CfP: Visualizations and User Interfaces for Knowledge Engineering and Linked Data Analytics


Visualizations and User Interfaces for Knowledge Engineering and Linked 
Data Analytics

International Workshop at EKAW 2014, 19th International Conference on 
Knowledge Engineering and Knowledge Management
November 24 or 25, 2014, Linköping, Sweden


Submission Deadline: September 30, 2014 (extended)

Motivation and Objectives

With data continuously generated as a result of daily activities within 
organizations and new data sources (sensor streams, linked datasets, 
etc.) introduced within knowledge management, the growth of information 
is unprecedented. Providing knowledge engineers and data analysts with 
visualizations and well-designed user interfaces can significantly 
support understanding of the concepts, data instances and relationships 
of different domains.

The development of appropriate visualizations and user interfaces is a 
challenging task, given the size and complexity of the information that 
needs to be displayed and the varied backgrounds of the users. Further 
challenges emerge from technological developments and diverse 
application contexts. There is no "one size fits all" solution but the 
various use cases demand different visualization and interaction 
techniques. Ultimately, providing better visualizations and user 
interfaces will foster user engagement and likely lead to higher-quality 
results in different areas of knowledge engineering and linked data 

This full-day workshop will be divided into two half-day tracks, one in 
the morning and the other in the afternoon, each focusing on one of the 
two workshop themes.

Track 1: Visualizations and User Interfaces for Knowledge Engineering

Visualizations and user interfaces are an integral part of knowledge 
engineering. They help to bridge the gap between domain experts and data 
management, and are essential to handle the increasing diversity of 
knowledge that is being modeled in ontologies, ensuring that it is 
easily accessible to a wide community. As knowledge-based systems and 
ontologies grow in size and complexity, the demand for comprehensive 
visualization and optimized interaction also rises.

A number of knowledge visualizations have become available in recent 
years, with some being already well-established, particularly in the 
field of ontology development. In other areas of knowledge engineering, 
such as ontology alignment and debugging, although several tools have 
recently been developed, few have a user interface, not to mention 
navigational aids or comprehensive visualization techniques. Other 
activities, such as data integration, rely on the relationships between 
the concepts of different ontologies, which not only multiplies the 
number of objects to be displayed but also compounds the problem with 
the portrayal of different kinds of relationships between concepts.

Topics of interest in this track include (but are not limited to):

- visualizations for (large and complex) ontologies
- user interfaces for ontology alignment and debugging
- visualizations and user interfaces for non-experts
- applications of novel interaction techniques (e.g. touch and gesture 
- user interfaces for mobile knowledge engineering
- requirements analysis for visualizations in knowledge engineering
- user interfaces assisting people with disabilities
- knowledge visualizations for large displays and high resolutions
- user interfaces for collaborative knowledge engineering
- case studies of applying visualizations in knowledge engineering
- user interfaces and visualizations for linked data
- context-aware visualization and interaction techniques

Track 2: Visualizations and User Interfaces for Linked Data Analytics

New and traditional knowledge practices, digitization of organizational 
processes, high performance computing and affordable datastores create 
an unprecedented amount of data as a part of daily organizational 
activities, at break-neck speed in a variety of formats. Conventional 
systems struggle to capture, store and analyze such dynamic and large 
scale data continuously generated. On its own, raw data has little 
value, but its value and significance is only unleashed when the data is 
extracted, processed and interpreted.

Visual Analytics attempts to address this challenge by harmoniously 
combining the strengths of human processing and electronic data 
processing. While semi-automated processes result in generating 
visualizations, humans can use visual processing and interactions to 
quickly identify trends, patterns and anomalies from large volumes of 
visual data. The growing challenges of analyzing big data, social media, 
linked data, and data streams have created an excellent opportunity for 
research in Visual Analytics.

Topics of interest in this track include (but are not limited to):

- interactive semantic systems
- design of interactive systems
- visual pattern discovery
- (semi-)automatic hypothesis generation
- augmented human reasoning
- novel visualizations of data and metadata
- visual approaches for semantic similarity measurement
- exploratory information visualization
- domain-specific visual analytics
- interactive systems in business intelligence
- cognition and sensemaking in visual contexts
- evaluation of interactive systems

Submission Guidelines

Paper submission and reviewing for this workshop will be electronic via 
EasyChair. The papers should be written in English, following Springer 
LNCS format, and be submitted in PDF.

The following types of contributions are welcome:

- Full research papers (8-12 pages);
- Experience papers (8-12 pages);
- Position papers (6-8 pages);
- Short research papers (4-6 pages);
- System papers (4-6 pages).

Accepted papers will be published as a volume in the CEUR Workshop 
Proceedings series.

Important Dates

- Submission: September 30, 2014
- Notification: October 21, 2014
- Camera-ready: November 11, 2014
- Workshop: November 24 or 25, 2014


- Valentina Ivanova, Linköping University, Sweden
- Tomi Kauppinen, Aalto University, Finland, and University of Bremen, 
- Steffen Lohmann, University of Stuttgart, Germany
- Suvodeep Mazumdar, The University of Sheffield, UK
- Catia Pesquita, University of Lisbon, Portugal
- Toomas Timpka, Linköping University, Sweden
- Kai Xu, Middlesex University, UK

Steffen Lohmann . Institute for Visualization and Interactive Systems
University of Stuttgart . Universitaetstrasse 38 . D-70569 Stuttgart
Phone: +49 711 685-88438 . http://www.vis.uni-stuttgart.de/~lohmansn

Received on Monday, 15 September 2014 08:56:12 UTC