scholarly journals Exploring descriptions of movement through geovisual analytics

2021 ◽  
Author(s):  
Scott Pezanowski ◽  
Prasenjit Mitra ◽  
Alan M. MacEachren
Keyword(s):  
Geovisual Analytics

Big Data in the Field of Civil Security Research

2016 ◽  
Vol 7 (1) ◽  
pp. 54-64 ◽  
Author(s):  
Julia Gonschorek ◽  
Anja Langer ◽  
Benjamin Bernhardt ◽  
Caroline Räbiger
Keyword(s):  
Big Data ◽  
Temporal Distribution ◽  
Tactical Planning ◽  
Fire Departments ◽  
Prevention Measures ◽  
Scientific Contribution ◽  
Security Research ◽  
Geovisual Analytics ◽  
The University ◽  
Selection Of

This article gives insight in a running dissertation at the University in Potsdam. Point of discussion is the spatial and temporal distribution of emergencies of German fire brigades that have not sufficiently been scientifically examined. The challenge is seen in Big Data: enormous amounts of data that exist now (or can be collected in the future) and whose variables are linked to one another. These analyses and visualizations can form a basis for strategic, operational and tactical planning, as well as prevention measures. The user-centered (geo-) visualization of fire brigade data accessible to the general public is a scientific contribution to the research topic 'geovisual analytics and geographical profiling'. It may supplement antiquated methods such as the so-called pinmaps as well as the areas of engagement that are freehand constructions in GIS. Considering police work, there are already numerous scientific projects, publications, and software solutions designed to meet the specific requirements of Crime Analysis and Crime Mapping. By adapting and extending these methods and techniques, civil security research can be tailored to the needs of fire departments. In this paper, a selection of appropriate visualization methods will be presented and discussed.

scholarly journals GeoVisual analytics: interactivity, dynamics, and scale

2015 ◽  
Vol 43 (1) ◽  
pp. 1-2 ◽  
Author(s):  
Gennady Andrienko ◽  
Natalia Andrienko ◽  
Jason Dykes ◽  
Menno Jan Kraak ◽  
Anthony Robinson ◽  
...  
Keyword(s):  
Geovisual Analytics

Interpreting rescue vehicle patterns using geovisual analytics for spatiotemporal resource allocation

2020 ◽  
Vol 13 (14) ◽  
Author(s):  
Usama Maqsood ◽  
Ali Tahir ◽  
Khunsa Fatima ◽  
Abdur Rahman
Keyword(s):  
Resource Allocation ◽  
Geovisual Analytics

scholarly journals A Framework Uniting Ontology-Based Geodata Integration and Geovisual Analytics

2020 ◽  
Vol 9 (8) ◽  
pp. 474
Author(s):  
Linfang Ding ◽  
Guohui Xiao ◽  
Diego Calvanese ◽  
Liqiu Meng
Keyword(s):  
Data Integration ◽  
Visual Analysis ◽  
Open Data ◽  
Data Access ◽  
Heterogeneous Data ◽  
Geospatial Data ◽  
Making Sense ◽  
Research Areas ◽  
Geovisual Analytics ◽  
Integration Techniques

In a variety of applications relying on geospatial data, getting insights into heterogeneous geodata sources is crucial for decision making, but often challenging. The reason is that it typically requires combining information coming from different sources via data integration techniques, and then making sense out of the combined data via sophisticated analysis methods. To address this challenge we rely on two well-established research areas: data integration and geovisual analytics, and propose to adopt an ontology-based approach to decouple the challenges of data access and analytics. Our framework consists of two modules centered around an ontology: (1) an ontology-based data integration (OBDI) module, in which mappings specify the relationship between the underlying data and a domain ontology; (2) a geovisual analytics (GeoVA) module, designed for the exploration of the integrated data, by explicitly making use of standard ontologies. In this framework, ontologies play a central role by providing a coherent view over the heterogeneous data, and by acting as a mediator for visual analysis tasks. We test our framework in a scenario for the investigation of the spatiotemporal patterns of meteorological and traffic data from several open data sources. Initial studies show that our approach is feasible for the exploration and understanding of heterogeneous geospatial data.

scholarly journals A web-enabled visualization toolkit for geovisual analytics

2011 ◽  
Vol 11 (1) ◽  
pp. 22-42 ◽  
Author(s):  
Q. Van Ho ◽  
P. Lundblad ◽  
T. Astrom ◽  
M. Jern
Keyword(s):  
Geovisual Analytics ◽  
Visualization Toolkit
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