Development of a Web-Based Geographical Information System for Interactive Visualization and Analysis of Container Itineraries

The paper describes an advanced prototype of a web-based geographical information system for user-friendly, interactive and efficient visualization of containers travelling over the world. The prototype uses ConTraffic Oracle Data Base (DB), where more than 300 000 container’s events are archived daily. The DB contains currently around one billion container movements. In addition, geographical data about the used locations/ports was collected and stored in the same DB on which the prototype is implemented. The prototype system provides users with container traffic information for specific date range, presented in interactive geographical and tabular mode. As a result, the prototype makes efficient visualization for easy visual analysis of container movements and status. The system used in this study gathers in quasi real-time online data from open sources, processes and stores it in DB. Using the proposed GIS application the user can access any time the DB and review on a map the itinerary of a specific container in specific date range, interact with the geographical presentation to receive specific details for the container for the used ports and review the itinerary details in interactive tabular presentation.JRC.G.4-Maritime affair

Los Angeles Metro Bus Data Analysis Using GPS Trajectory and Schedule Data (Demo Paper)

With the widespread installation of location-enabled devices on public transportation, public vehicles are generating massive amounts of trajectory data in real time. However, using these trajectory data for meaningful analysis requires careful considerations in storing, managing, processing, and visualizing the data. Using the location data of the Los Angeles Metro bus system, along with publicly available bus schedule data, we conduct a data processing and analyses study to measure the performance of the public transportation system in Los Angeles utilizing a number of metrics including travel-time reliability, on-time performance, bus bunching, and travel-time estimation. We demonstrate the visualization of the data analysis results through an interactive web-based application. The developed algorithms and system provide powerful tools to detect issues and improve the efficiency of public transportation systems.Comment: SIGSPATIAL'18, demo paper, 4 page

Web-Based Visualization of Very Large Scientific Astronomy Imagery

Visualizing and navigating through large astronomy images from a remote location with current astronomy display tools can be a frustrating experience in terms of speed and ergonomics, especially on mobile devices. In this paper, we present a high performance, versatile and robust client-server system for remote visualization and analysis of extremely large scientific images. Applications of this work include survey image quality control, interactive data query and exploration, citizen science, as well as public outreach. The proposed software is entirely open source and is designed to be generic and applicable to a variety of datasets. It provides access to floating point data at terabyte scales, with the ability to precisely adjust image settings in real-time. The proposed clients are light-weight, platform-independent web applications built on standard HTML5 web technologies and compatible with both touch and mouse-based devices. We put the system to the test and assess the performance of the system and show that a single server can comfortably handle more than a hundred simultaneous users accessing full precision 32 bit astronomy data.Comment: Published in Astronomy & Computing. IIPImage server available from http://iipimage.sourceforge.net . Visiomatic code and demos available from http://www.visiomatic.org

Triangulum City Dashboard: An Interactive Data Analytic Platform for Visualizing Smart City Performance

Cities are becoming smarter by incorporating hardware technology, software systems, and network infrastructure that provide Information Technology (IT) systems with real-time awareness of the real world. What makes a “smart city” functional is the combined use of advanced infrastructure technologies to deliver its core services to the public in a remarkably efficient manner. City dashboards have drawn increasing interest from both city operators and citizens. Dashboards can gather, visualize, analyze, and inform regional performance to support the sustainable development of smart cities. They provide useful tools for evaluating and facilitating urban infrastructure components and services. This work proposes an interactive web-based data visualization and data analytics toolkit supported by big data aggregation tools. The system proposed is a cloud-based prototype that supports visualization and real-time monitoring of city trends while processing and displaying large data sets on a standard web browser. However, it is capable of supporting online analysis processing by answering analytical queries and producing graphics from multiple resources. The aim of this platform is to improve communication between users and urban service providers and to give citizens an overall view of the city’s state. The conceptual framework and architecture of the proposed platform are explored, highlighting design challenges and providing insight into the development of smart cities. Moreover, results and the potential statistical analysis of important city services offered by the system are introduced. Finally, we present some challenges and opportunities identified through the development of the city data platform.publishedVersio

The Virtual-Spine Platform—Acquiring, visualizing, and analyzing individual sitting behavior

Back pain is a serious medical problem especially for those people sitting over long periods during their daily work. Here we present a system to help users monitoring and examining their sitting behavior. The Virtual-Spine Platform (VSP) is an integrated system consisting of a real-time body position monitoring module and a data visualization module to provide individualized, immediate, and accurate sitting behavior support. It provides a comprehensive spine movement analysis as well as accumulated data visualization to demonstrate behavior patterns within a certain period. The two modules are discussed in detail focusing on the design of the VSP system with adequate capacity for continuous monitoring and a web-based interactive data analysis method to visualize and compare the sitting behavior of different persons. The data was collected in an experiment with a small group of subjects. Using this method, the behavior of five subjects was evaluated over a working day, enabling inferences and suggestions for sitting improvements. The results from the accumulated data module were used to elucidate the basic function of body position recognition of the VSP. Finally, an expert user study was conducted to evaluate VSP and support future developments

Visualization of particle collisions in hadron colliders

In this work we present a visualization system for particle collisions in high- energy physics, which we developed in cooperation with CERN. During the experiments in particle physics a large amount of data is acquired, used for event reconstruction. For better understanding suitable visualization is needed. This poses a big challenge due to large amount of data, especially when we want to achieve real-time interactive functionality. For wider accessibility we decided to implement the visualization in web- based technologies. We developed a visualization system using WebGL, op- timized for fast and efficient use with GPUs. We focused on minimization of draw calls and minimization of data transfer to the the GPU. This proofs as an efficient solution confirmed by performance analysis of the developed system. The system was also tested using the Med3D system, which uses a hybrid rendering mode. This combines rendering through a browser with rendering on a dedicated server

Visualization of particle collisions in hadron colliders

In this work we present a visualization system for particle collisions in high- energy physics, which we developed in cooperation with CERN. During the experiments in particle physics a large amount of data is acquired, used for event reconstruction. For better understanding suitable visualization is needed. This poses a big challenge due to large amount of data, especially when we want to achieve real-time interactive functionality. For wider accessibility we decided to implement the visualization in web- based technologies. We developed a visualization system using WebGL, op- timized for fast and efficient use with GPUs. We focused on minimization of draw calls and minimization of data transfer to the the GPU. This proofs as an efficient solution confirmed by performance analysis of the developed system. The system was also tested using the Med3D system, which uses a hybrid rendering mode. This combines rendering through a browser with rendering on a dedicated server

twine a real time system for tweet analysis via information extraction

In the recent years, the amount of user generated contents shared on the Web has significantly increased, especially in social media environment, e.g. Twitter, Facebook, Google+. This large quantity of data has generated the need of reactive and sophisticated systems for capturing and understanding the underlying information enclosed in them. In this paper we present TWINE, a real-time system for the big data analysis and exploration of information extracted from Twitter streams. The proposed system based on a Named Entity Recognition and Linking pipeline and a multi-dimensional spatial geo-localization is managed by a scalable and flexible architecture for an interactive visualization of micropost streams insights. The demo is available at http://twine-mind.cloudapp.net/streamin

Integrating and Visualizing Tropical Cyclone Data Using the Real Time Mission Monitor

The Real Time Mission Monitor (RTMM) is a visualization and information system that fuses multiple Earth science data sources, to enable real time decision-making for airborne and ground validation experiments. Developed at the NASA Marshall Space Flight Center, RTMM is a situational awareness, decision-support system that integrates satellite imagery, radar, surface and airborne instrument data sets, model output parameters, lightning location observations, aircraft navigation data, soundings, and other applicable Earth science data sets. The integration and delivery of this information is made possible using data acquisition systems, network communication links, network server resources, and visualizations through the Google Earth virtual globe application. RTMM is extremely valuable for optimizing individual Earth science airborne field experiments. Flight planners, scientists, and managers appreciate the contributions that RTMM makes to their flight projects. A broad spectrum of interdisciplinary scientists used RTMM during field campaigns including the hurricane-focused 2006 NASA African Monsoon Multidisciplinary Analyses (NAMMA), 2007 NOAA-NASA Aerosonde Hurricane Noel flight, 2007 Tropical Composition, Cloud, and Climate Coupling (TC4), plus a soil moisture (SMAP-VEX) and two arctic research experiments (ARCTAS) in 2008. Improving and evolving RTMM is a continuous process. RTMM recently integrated the Waypoint Planning Tool, a Java-based application that enables aircraft mission scientists to easily develop a pre-mission flight plan through an interactive point-and-click interface. Individual flight legs are automatically calculated "on the fly". The resultant flight plan is then immediately posted to the Google Earth-based RTMM for interested scientists to view the planned flight track and subsequently compare it to the actual real time flight progress. We are planning additional capabilities to RTMM including collaborations with the Jet Propulsion Laboratory in the joint development of a Tropical Cyclone Integrated Data Exchange and Analysis System (TC IDEAS) which will serve as a web portal for access to tropical cyclone data, visualizations and model output

The Billion Object Platform (BOP): a system to lower barriers to support big, streaming, spatio-temporal data sources

With funding from the Sloan Foundation and Harvard Dataverse, the Harvard Center for Geographic Analysis (CGA) has developed a big spatio-temporal data visualization platform called the Billion Object Platform or BOP . The goal of the project is to lower barriers for scholars who wish to access large, streaming, spatio-temporal datasets. Since once archived, streaming data gets big fast, and since most GIS systems don\u27t support interactive visualization of millions of objects, a new platform was needed. The BOP is loaded with the latest billion geo-tweets and is fed a real-time stream of about 1 million tweets per day. The CGA has been harvesting and archiving geo-tweets since 2012. As tweets flow into the BOP, they are enriched with sentiment and census information to support further analysis. Incoming and intermediate data is streamed/stored in Apache Kafka. The core of the BOP is Apache Solr, which supports fast search. Some significant enhancements were done to Solr (and contributed back) -- notably 2D heatmap faceting to support spatial visualization. The BOP fronts Solr with a RESTful web service, which provides a friendly, and secure API that is accessed from a browser-based client. The client developed, dynamically displays temporal and spatial distributions of results for result sets containing hundreds of millions of features. The system is open source and runs on commodity hardware. It is hosted on Massachusetts Open Cloud (MOC), an OpenStack environment. All components are deployed in Docker orchestrated by Kontena