The following workshops will be conducted at i-KNOW 2016. Follow the links to find more information on each workshop as well as the issued Calls for Papers.

Active Learning: Applications, Foundations and Emerging Trends

Organizers: Georg Krempl, Vincent Lemaire, Edwin Lughofer and Daniel Kottke

Active learning is a very useful methodology in on-line industrial applications for reducing efforts for sample annotation and measurements of “target” values (e.g., quality criteria). Various approaches, application scenarios and deployment protocols have been proposed for active learning. However, despite the efforts made from academia and industry researchers alike, there are still gaps between research on theoretical and practical aspects. When designing active learning algorithms for real-world data, some specific issues are raised. The main ones are scalability and practicability. Methods must be able to handle high volumes of data, in spaces of possibly high-dimension, and the process for labeling new examples by an expert must be optimized.
The aim of this workshop is to provide a forum for researchers and practitioners to discuss approaches, identify challenges and gaps between active learning research and meaningful applications, as well as define new application-relevant research directions.


Human Computer Interaction (HCI) Perspectives on Industry 4.0

Organizers: Mario Aehnelt, Viktoria Pammer-Schindler, Ralf Klamma and Eduardo Enrique Veas

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.


Knowledge 4.0 – Knowledge Management in Digital Change

Organizers: Oliver Haas, Stefanie Lindstaedt, Ronald Maier and Klaus North

The Digitalisation makes disruption possible and demands change and reinvention in all sectors of organisation. In doing so the technical possibility to make big quantities of data and information available, to cross-connect it, evaluate it intelligently, communicate it, and visualize it have considerable effects on the managements of the knowledge resource in the context of organization and its polymorphic trade relationships with the environment.


SamI40 – 1st International Workshop on Science, Application and Methods in Industry 4.0

Organizers: Roman Kern, Gerald Reiner and Olivia Bluder

The SamI40 workshop aims at bringing together researchers and practitioners in the fastly evolving fields related to Industry 4.0. Researchers are given the opportunity to present the current state-of-the-art in science via survey papers and practitioners will present posters depicting the main challenges which have to be tackled and overcome in the foreseeable future. The main topics of the workshop will be on secure data handling, smart production, machine learning and big data analytics, as well as application of the aforementioned techniques in intelligent decision supporting systems. In conclusion, this workshop offers participants a holistic view of different aspects related to changes, which are currently happening in manufacturing and related fields.


Workshop on Recommender Systems and Big Data Analytics (RS-BDA’16)

Organizers: Elisabeth Lex, Roman Kern, Alexander Felfernig, Kris Jack, Dominik Kowald and Emanuel Lacic

The main topic of this workshop is the broad research area of recommender systems and how it is connected with big data analytics. Thus, it is our main intention to bring together researchers and practitioners in these areas to discuss novel trends in analyzing big data for recommender systems. This workshop theme should be of great interest for i-KNOW 2016 attendees since both recommender systems and big data analytics are important research instruments at the intersection of the disciplines of knowledge discovery, Web & data science as well as social computing.