Scope
Various approaches have been developed to grasp Big Data. Machine Learning addresses Big Data by using algorithmic approaches to tackle the sheer size and complexity of data. On the other hand, Visual Analytics is a field that tries to combine information visualization – the science of visually displaying quantitative information – with nearby fields, such as knowledge discovery, cognitive and perceptual sciences, statistical analysis. Bringing those two approaches together is the aim of Human-Computer Interaction and Knowledge Discovery in Databases. The overall aim is to support decision-making on the basis of data. Or, how do we get from large amounts of data from the digital world into actionable knowledge in the mental world?
Many of the hard questions have been approached, yet remain partially unanswered.
– Where is the place of the Human in the Loop?
– How do we design interfaces that support the users in making decisions?
– How do we technically create visualizations that represent hard scientific problems?
– How much does a visualization tool need to be tailored the specific problem, how much generalization is possible?
– What insights can be drawn from a specific visualization, and by whom?
Aims
The aim of the HFIDSS sessions is to identify a research agenda for the intersection of Big Data, human-computer interaction and information visualization. What are the most pressing research topics?
Topics
Prospective authors are invited to submit papers on the following topics, but not limited to:
– Human Factors in Information Visualization
– Human Factors in Decision Support Systems
– Human Factors in Visual Analytics
– Human Factors in Recommender Systems
– Human Factors in Scientific Visualizations
– Human in the Loop Data Analysis
– Design Studies for Information Visualization
– Usability and UX of Visualizations
– Studies on Visualization Insight
Important Dates
Saturday, 31 December 2016 Abstract submission (800 words) through the CMS, for the review process
Tuesday, 31 January 2017 Notification of review outcome
Friday, 10 February 2017 Submission through the CMS of the camera-ready version (full papers, typically 10 pages, with minimum 8 pages long, maximum 12 pages long) of all papers
Authors that wish to contribute should send an email asking for an invitation.