Workshop at I-KNOW 2016
Today we are facing a new era of industrial automation and interconnection which drives the transition of human workplaces. New technologies but also novel business processes lead to a shift of worker related requirements at the data-intensive manufacturing workplace on the shop floor or in knowledge-intensive maintenance field operations. HCI research is already dealing with these new challenges by developing and providing practical assistance solutions which bring together again the power of industrial automation with the flexibility of human intelligence.
This workshop aims to pick up and present examples of best practice and lessons learned from researching and rolling out novel methods and technologies for worker focused assistance under industrial conditions. The topics of interest here include, but are not limited to:
Cognitive support and cognitive automation for human sense making and decision making processes
Visual assistance with augmented or virtual reality for complex data or knowledge-intensive work tasks
Smart and situated learning for a professional and self-directed work life on the shop floor
Data usability for enabling the worker to deal intuitively with complex and heterogeneous data
Both scientists as well as industrial participants are invited to contribute to the workshop with their own work related to the mentioned topics. We accept scientific papers with a maximum of 4 pages (ACM SIGCHI Paper Format) and industrial best-practice examples (description not longer than 2 pages).
Scientific submissions undergo a peer review process to assure high quality content being presented. Industrial best-practice examples are curated by the workshop editors. Accepted contributions from scientific and industrial participants are given a 5-10 minute time slot to present the major findings and lessons learned from their work.
If technically possible, presenters are cordially invited to bring with them hands-on experiences for the workshop.
The workshop is intended to be a means for bringing together scientific excellence from multiple fields and industrial demands in a vivid dialog. Therefore, it encourages scientists in the field of manufacturing, production management, computer science and psychology to participate with their scientific contribution and to provide interesting stimuli as well as research insights. Vice versa it focuses on the industrial audience which searches for answers and partnerships in todays’ discussion of emerging Industry 4.0 terms and claims.
We are aiming with the workshop at the growing demand of exchanging not ideas but real experiences (including questions arising from practice) on how Industry 4.0 works best without leaving the human worker behind. Here, we want to discuss with our scientific and industrial audience both sides of the story: the abilities but also the borders and limitations of today’s solutions.
All accepted contributions will be listed on a workshop website, and accepted papers will be made available for download on the workshop website if the authors agree.
In addition, the best accepted workshop contributions will be suggested by the workshop editors for inclusion in additional conference proceedings in the ACM digital library.
i-KNOW Ticket Discounts
In order to support the scientific community we offer reduced prices to workshop participants: €390 for the full 2 day conference. This is not visible on the i-KNOW website. Workshop participants will receive a promotion code for the reduced pricing.
Mario Aehnelt (Fraunhofer IGD Rostock, Germany)
Viktoria Pammer-Schindler (Graz University of Technology, Know-Center Graz, Austria)
Ralf Klamma (RWTH Aachen University, Germany)
Eduardo Enrique Veas (Know-Center Graz, Graz University of Technology, Austria)
Deadline Workshop Papers: July 25, 2016
Accept/Reject Notification of Workshop Papers: August 22, 2016
Camera ready version of Workshop Papers: September 12, 2016
i-KNOW 2016 Conference in Graz: October 18-19, 2016
Questions regarding the workshop? Don’t hesitate to contact us: firstname.lastname@example.org!