User-centered Design and Evaluation of a Geovisualization Application Leveraging Aggregated QS Data

Individual movement traces recorded by users of activity tracking applications such as Strava provide opportunities that extend beyond delivering personal value or insight to the individual who engages in these “quantified-self” (QS) activities. The large volumes of data generated by these individuals, when aggregated and anonymized, can be used by city planners, Departments of Transportation, advocacy groups, and researchers to help make cities safer and more efficient. This opportunity, however, is constrained by the technical skills and resources available to those tasked with assessing bicycling behavior in urban centers. This paper aims to address the question of how to design cartographic interfaces to serve as mediated platforms for making large amounts of individual bicycling data more accessible, usable, and actionable. Principles of cartographic representation, geovisual analytics techniques, and best practices in user interface/experience design are employed to arrive at an effective visualization tool for a broad urban planning audience. We use scenario-based design methods to encapsulate knowledge of map use practice gleaned from the development process, and conduct a post-implementation two-part user study with seven domain experts to further assess the usability and utility of the interactive mapping tool.

A Framework Uniting Ontology-Based Geodata Integration and Geovisual Analytics

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.

Analitis Geovisual Okupansi Halte dan Pergerakan Penumpang Transjakarta

Public eagerness to use Transjakarta as a transport mode has been increasing over the past few years as the ridership growth consistently. To keep the growth up, stakeholders need to understand the passenger behavior by creating an effective operational system so that the passenger satisfaction maintained. An understanding of passenger behavior can be obtained by identifying its pattern and trend which recorded as passenger transaction data. This project uses passenger transaction data which contains information about time and space to produce interactive visualization as a means to identify passenger behavior. Interactive visualization created in this project depicts the trend of bus stop occupancy and passenger movement from one stop to another. The visualization consists of a map and diagrams which relate to each other as one integrated analytical dashboard system. The visualization design process combines Tableau 2019.2 and Mapbox GL JS to create powerful visualization supported by a 3D map view that facilitates analytical reasoning work. Geovisual analytics dashboard as a result of this project is intended for PT. Transportasi Jakarta staff to make decisions. Some staff was asked to examine the usability of the dashboard regarding its effectiveness, efficiency, and accessibility aspects. The usability test pointed out that the analytical dashboard can generate new information about the patterns and trends of Transjakarta passengers.

Exploring the Use of a Spatio-Temporal City Dashboard to Study Criminal Incidence: A Case Study for the Mexican State of Aguascalientes

By considering public safety as a relevant component of a smart city framework, the development and use of city dashboards that explore the spatio-temporal monitoring of crime incidence to help local governments base their decision-making process on evidence is becoming more relevant. This research deals with the case study of the state of Aguascalientes, Mexico, whose capital hosts the annual San Marcos Fair, considered the most important fair in the country. By developing an online dynamic platform consisting of several different modules that rely on the use of geovisual analytics for dynamic and interactive data display and exploration, authorities can gain insights about the times and locations of the impact of criminal incidence, detect patterns over space and time, and look into what actions could be put in place. This becomes useful in advancing a circular model of the smart city in which urban processes are observed, data is collected and analyzed, management and decision actions occur, and more data is collected to measure their effectiveness. By comparing statistics for the three year period of 2016–2018, it is found that the second year of the study had a significant decrease in pedestrian crime incidence during the Fair, supporting the use of city dashboards with geovisual analytics to help monitor urban processes and aid authorities in making decisions. Further research is needed to uncover more efficient practices to achieve inter-institutional collaboration and data sharing schemes that adhere to and boost the principles of the smart city.