Projects

This page provides an overview of current and former projects I am involved in.

Current Projects

VISDOM: Improving computational and human performance with highly realistic three-dimensional geographic visualizations by means of biomimicry

The project seeks to implement biologically-inspired solutions for visual analytics of big data to study complex phenomena. A special focus will be on highly realistic three-dimensional (3D) representations and virtual/augmented reality within the Digital Earth framework.
The project started in 2014.

mSAFE: mobile Smart Applications for Evacuation

I am one of the researchers involved in this EU FP7-PEOPLE-IRSES program. The project will deliver advances in the understanding of cognition under stress, real-time semantic querying and mobile human-computer interaction. Partners in this project are the University of Bremen, Germany (lead); the University of Zurich, Switzerland; the University of Melbourne, and La Trobe University.

 

Former Projects

From Environmental Monitoring to Management:  Extracting Knowledge about Environmental Events from Sensor Data

Technologies for capturing data about the environment have advanced rapidly; our ability to use this data for effective decision making has not. This ARC Discovery Project will design and evaluate new techniques for extracting common-sense knowledge about environmental events from complex geospatial sensor data. By closing the gap between environmental monitoring and environmental management, this project will equip scientists, engineers, and managers with the tools to more easily understand and use high-detail, dynamic, heterogeneous, and uncertain environmental data.

Talking about Place – Tapping Human Knowledge to Enrich National Spatial Data Sets

Place descriptions are a common way for people to describe a location, but no current software tools are smart enough to understand them. This way, emergency call centres are risking lives, postal services are wasting billions of dollars per year by addressing problems, and users of navigation or web services are frustrated about restrictive interfaces or prolonged search.

This ARC Linkage Project will develop a novel, interdisciplinary approach to automatically interpret human place descriptions. It will develop methods to capture placenames with their meaning — their true location — for smarter databases and automatic interpretation procedures. The acquired knowledge will be an important step forward for data custodians and for service users.

Spatial Learning in Location-Based Services

Navigation devices, such as car navigation systems or smart-phones, have become widespread. People often blindly follow instructions of these devices without paying much attention to the world around them-this has led to several (sometimes spectacular) accidents. This is mainly caused by the way the information is presented and interacted with.

This project will set the stage for research into countering these effects. Novel principles of information presentation need to be developed that foster understanding your surroundings while being assisted.  Keeping users informed all the time during assistance will result in assistance services that increase user satisfaction and are safer to use.

This project is funded through an Early Career Grant by the Department of Geomatics, the University of Melbourne.

I2-[MapSpace]

Have you ever wondered why you get lost despite having a map with you? Or why your navigation system explains in tedious detail how to get from your home on to the main street, but then fails to navigate you through this complex intersection in a new town? We do!
This project develops smart, adaptive wayfinding assistance systems. Our goal is to improve wayfinding in outdoor, indoor, and virtual environments. We look for ways of representing environments in a way that it matches with human understanding of space and allows for efficient communication. We develop maps for small mobile devices, principles for automatic route directions, and transformations for virtual environments, all with improved usability and ease of understanding in mind.

Our aim is to develop efficient forms of wayfinding assistance. Schematic maps, route directions, and schematized virtual environments are the primary forms under investigation. We analyze the mutual influence of task, user, environment, and form of assistance to develop appropriate ways of representing the environment. Of further importance is the mutual impact of structural and functional characteristics on the conceptualization of environments. Finally, we account for the integration of individual prior knowledge of users, requirements of sub-tasks of wayfinding, as well as constraints put in by the assistance device on the resulting representations.

This project is part of the Transregional Collaborative Research Center SFB/TR 8 Spatial Cognition, funded by DFG.

Cognitive Engineering for Navigation Assistance

This was a project within the Go8/DAAD Australian-German Research Exchange Scheme, funded from 2008 to 2010. We looked at various aspects of spatial representation and communication in the context of navigation assistance.

Spatial Structures in Aspect Maps

The project investigates geographic maps and map-like depictions as knowledge representation structures which combine spatial and symbolic knowledge in a joint representation medium. Of particular interest are representations which focus on specific aspects of the spatial environment they represent. The construction and interpretation of these structures is analyzed and modeled under an interdisciplinary perspective. From a cognitive science point of view, examining maps is interesting as this may help to improve the understanding of mental spatial knowledge processing; this, in turn, may lead to cognitively more adequate presentations of spatial information. The project deals with schematic maps (e.g. public transportation network maps) to examine how these maps represent spatial knowledge and how they are used and misused for spatial information purposes. Moreover, automatic schematization methods for map-like representations are developed. An artificial intelligence architecture for representing and processing spatial knowledge has been designed and implemented. The project’s results are applied in using schematic spatial representations for the communication with autonomous robots and in designing cognitively adequate you-are-here maps for human orientation purposes.

This project was part of the Spatial Cognition Priority Program, funded by DFG.

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