420 research outputs found
Geovisual analytics for spatial decision support: Setting the research agenda
This article summarizes the results of the workshop on Visualization, Analytics & Spatial Decision Support, which took place at the GIScience conference in September 2006. The discussions at the workshop and analysis of the state of the art have revealed a need in concerted crossâdisciplinary efforts to achieve substantial progress in supporting spaceârelated decision making. The size and complexity of realâlife problems together with their illâdefined nature call for a true synergy between the power of computational techniques and the human capabilities to analyze, envision, reason, and deliberate. Existing methods and tools are yet far from enabling this synergy. Appropriate methods can only appear as a result of a focused research based on the achievements in the fields of geovisualization and information visualization, humanâcomputer interaction, geographic information science, operations research, data mining and machine learning, decision science, cognitive science, and other disciplines. The name âGeovisual Analytics for Spatial Decision Supportâ suggested for this new research direction emphasizes the importance of visualization and interactive visual interfaces and the link with the emerging research discipline of Visual Analytics. This article, as well as the whole special issue, is meant to attract the attention of scientists with relevant expertise and interests to the major challenges requiring multidisciplinary efforts and to promote the establishment of a dedicated research community where an appropriate range of competences is combined with an appropriate breadth of thinking
Improving Big Data Visual Analytics with Interactive Virtual Reality
For decades, the growth and volume of digital data collection has made it
challenging to digest large volumes of information and extract underlying
structure. Coined 'Big Data', massive amounts of information has quite often
been gathered inconsistently (e.g from many sources, of various forms, at
different rates, etc.). These factors impede the practices of not only
processing data, but also analyzing and displaying it in an efficient manner to
the user. Many efforts have been completed in the data mining and visual
analytics community to create effective ways to further improve analysis and
achieve the knowledge desired for better understanding. Our approach for
improved big data visual analytics is two-fold, focusing on both visualization
and interaction. Given geo-tagged information, we are exploring the benefits of
visualizing datasets in the original geospatial domain by utilizing a virtual
reality platform. After running proven analytics on the data, we intend to
represent the information in a more realistic 3D setting, where analysts can
achieve an enhanced situational awareness and rely on familiar perceptions to
draw in-depth conclusions on the dataset. In addition, developing a
human-computer interface that responds to natural user actions and inputs
creates a more intuitive environment. Tasks can be performed to manipulate the
dataset and allow users to dive deeper upon request, adhering to desired
demands and intentions. Due to the volume and popularity of social media, we
developed a 3D tool visualizing Twitter on MIT's campus for analysis. Utilizing
emerging technologies of today to create a fully immersive tool that promotes
visualization and interaction can help ease the process of understanding and
representing big data.Comment: 6 pages, 8 figures, 2015 IEEE High Performance Extreme Computing
Conference (HPEC '15); corrected typo
A Geovisual Analytic Approach to Understanding Geo-Social Relationships in the International Trade Network
The world has become a complex set of geo-social systems interconnected by networks, including transportation networks, telecommunications, and the internet. Understanding the interactions between spatial and social relationships within such geo-social systems is a challenge. This research aims to address this challenge through the framework of geovisual analytics. We present the GeoSocialApp which implements traditional network analysis methods in the context of explicitly spatial and social representations. We then apply it to an exploration of international trade networks in terms of the complex interactions between spatial and social relationships. This exploration using the GeoSocialApp helps us develop a two-part hypothesis: international trade network clusters with structural equivalence are strongly âbalkanizedâ (fragmented) according to the geography of trading partners, and the geographical distance weighted by population within each network cluster has a positive relationship with the development level of countries. In addition to demonstrating the potential of visual analytics to provide insight concerning complex geo-social relationships at a global scale, the research also addresses the challenge of validating insights derived through interactive geovisual analytics. We develop two indicators to quantify the observed patterns, and then use a Monte-Carlo approach to support the hypothesis developed above
Geovisual Analytics Environment for Supporting the Resilience of Maritime Surveillance System
International audienceThis paper presents an original approach for supporting the resilience in Maritime Domain Awareness, based on geovisual analytics. While many research projects focus on developing rules for detecting anomalies at by automated means, there is no support to visual exploration led by human operators. We investigate the use of visual methods for analyzing mobility data of ships. Behaviors of interest can be known (modeled) or unknown, asking for various ways of visualizing and studying the information. We assume that supporting the use of geovisual analytics will make the exploration and the analysis process easier, reducing the cognitive load of the tasks led by the actors of maritime surveillance. The detection and the identification of threats at sea are improved by using adequate visualization methods, regarding the context of use. Our suggested framework is based on ontologies for maritime domain awareness and geovisual analytics environments, coupled to rules
A Geovisual Analytics Approach for Mouse Movement Analysis
The use of Web maps has created opportunities and challenges for map generation and delivery. While volunteered geographic information has led to the development of accurate and inexpensive Web maps, the sheer volume of data generated has created spatial information overload. This results in difficulties identifying relevant map features. Geopersonalisation, which adapts map content based on user interests offers a solution to this. The technique is especially powerful when implicit indicators of interest are used as a basis for personalisation. This article describes the design and features of VizAnalysisTools, a suite of tools to visualise and interpret usersâ implicit interactions with map content. While traditional data mining
techniques can be used to identify trends and preferences, visual analytics, in particular Geovisual Analytics, which assists the human cognition process, has proven useful in detecting interesting patterns. By identifying salient trends, areas of interest on the map become apparent. This knowledge can be used to strengthen the algorithms used for Geopersonalisation
Using Ontologies for Proposing Adequate Geovisual Analytics Solutions in the Analysis of Trajectories
International audienceThis paper presents an original approach for supporting the use of geovisual analytics solutions. Many models have been proposed to characterize information visualization methods, but few have been integrated to an intelligent process for supporting user in geo-information usage. Moreover, several new solutions are continuously proposed by research, but few of them are really used in operational world. For instance, the maritime surveillance systems could gain much more identification capabilities of ship behaviors with adequate geovisual analytics solutions. Therefore, we investigated the use of geovisual methods for the analysis of mobility data, such as ship trajectories. We propose a knowledge-based system using ontologies and rules. These allow modeling the domain of geovisual analytics solutions, and their capacities in the exploration and the analysis of trajectories. This system would be used to support users in geovisual analytics of movement, based on their context of use
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