We aim to deepen our knowledge of real, mental, and virtual worlds to find solutions for pressing societal needs and environmental problems of the mobile digital information society, increasingly living in densely populated urban areas.
Our research lies at the interface of geographic information science, geographic information visualization/geovisual analytics, spatial cognition, and spatial epidemiology.
We follow three research threads involving (1) spatio-temporal analytics of mobility and health, (2) the design and development of geographic information displays, and (3) their empirical evaluation, to support affective, effective, and efficient decision making and behavior.
«Spatio-temporal analytics of mobility and health»
WHY? With increasing mobility of the evolving digital society, supported by smart mobile information technology, exciting opportunities arise to study mobility and health in situ and in real-time.
WHAT? Approaches from the fields of health geography, spatial, and digital epidemiology allow us to deepen our understanding of geographic distributions of health outcomes at fine spatio-temporal resolutions, and their locally specific causes. This in turn facilitates potential interventions to prevent diseases, and to help promote the health of populations.
HOW? We apply spatial and spatio-temporal statistics to analyze social behavior and health outcomes. We base our research on novel data sources, such as unstructured and semi-structured texts (e.g., geo-referenced social media data) and link these to other data (e.g., official health and environmental statistics, land use and land cover data, etc.) that can be spatially integrated with disease mapping, exposure mapping, and spatial modeling approaches.
UZH Epidemiology, Biostatistics and Prevention Institute
UZH Competence Center for Mental Health
UZH Digital Society Initiative
CODE LAB, Prof. Arko Gosh, Leiden University, Leiden (NL)
GIVA Health Geography group
Boo, G., Leyk, S., Fabrikant, S.I., Graf, R., Pospischil, A., (2019). Exploring Uncertainty in Canine Cancer Data Sources Through Dasymetric Refinement. Frontiers in Veterinary Science, 10.3389/fvets.2019.00045.
Gruebner O, McCay L. Urban Design. In: Urban Health. Sandro Galea, Catherine K. Ettman, and David Vlahov (Editors). Oxford: Oxford University Press; 2019:456. https://global.oup.com/urban-health
Gruebner O, Lowe S, Sykora M, Shankardass K, Subramanian S, Galea S. Spatio-Temporal Distribution of Negative Emotions in New York City After a Natural Disaster as Seen in Social Media. Int J Environ Res Public Health. 2018;15(10):2275. doi:10.3390/ijerph15102275
Gruebner O, Sykora M, Lowe SR, Shankardass K, Galea S, Subramanian SV. Big data opportunities for social behavioral and mental health research. Soc Sci Med. 2017;2012:2016-2018. doi:10.1016/j.socscimed.2017.07.018
«Design and development of geographic information displays»
WHY? Urban spaces have always played an important role for societies. With the digital transformation, they increasingly transform into smart and powerful, sensor and data-driven cities (e.g., the Internet of Things).
WHAT? We aim to provide geographic information displays that guide users' attention towards context and decision-relevant geographic information, for affective, effective, and efficient decision making and space-time behavior. The main application is the support of intelligent mobility, building on smart digital infrastructures.
HOW? We study the appropriate selection and presentation of relevant geographic information for users with different backgrounds and varying needs, and develop human and user responsive geographic displays for varying use contexts. We devise solutions for integrating multisource, multivariate, real-time data streams into data-driven dashboards and mobile geographic information displays for informed decision making, and to guide space-time behavior. Specifically, we develop adaptive visualization methods for serving useful and usable context-dependent geographic information for everyday situations, tailored to the mobile, digital citizen.
Reichenbacher, T., De Sabbata, S., Purves, R., and Fabrikant, S.I. (2016). Assessing geographic relevance for mobile search: a computational model and its validation via crowdsourcing. Journal of the Association for Information Science and Technology. DOI: 10.1002/asi.23625
Schito, J. and Fabrikant, S.I. (2018). Exploring Maps by Sounds: Using Parameter Mapping Sonification to Make Digital Elevation Models Audible. International Journal of Geographic Information Science. DOI: 10.1080/13658816.2017.1420192
«Empirical evaluation of visuo-spatial displays»
WHY? Well-designed mobile, human responsive geographic information technology could improve the lives of millions mobile smart citizens who daily need to make time critical and societally relevant decisions on the go.
WHAT? Our objective is to create aesthetically pleasing, human, task, and context responsive geographic information displays that can be used indoors (i.e., large immersive VR, etc.) and outdoors (i.e., small mobile assistive displays, AR, etc.).
HOW? We empirically assess a broad range of geographic and non-geographic (i.e., spatialized) information displays to support space-time knowledge discovery, knowledge acquisition, decision making, and behavior. We capitalize on ambulatory, in-situ human behavior sensing methods (i.e., eye tracking, galvanic skin responses, EEG measurements, etc.) to support affective, effective, and efficient space-time decision making and behavior in real-time. Our empirical studies follow experimental design standards from the cognitive sciences including neuroscience, and are additionally grounded on state-of-the-art theories and solid design principles from cartography, information visualization, and computer vision.
Brügger, A., Richter, K.-F., Fabrikant, S. I. (2019). How does navigation system behavior influence human behavior? Cognitive Research: Principles and Implications, vol 4, no.5, DOI:10.1186/s41235-019-0156-5
Credé, S., Thrash, T., Hölscher, C., Fabrikant, S.I. (2019). The acquisition of survey knowledge for local and global landmark configurations under time pressure. Spatial Cognition and Computation, DOI: 10.1080/13875868.2019.1569016