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- Andrienko, Gennady, et al.
(författare)
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Space, time and visual analytics
- 2010
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Ingår i: INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE. - : Taylor and Francis. - 1365-8816 .- 1362-3087. ; 24:10, s. 1577-1600
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Tidskriftsartikel (refereegranskat)abstract
- Visual analytics aims to combine the strengths of human and electronic data processing. Visualisation, whereby humans and computers cooperate through graphics, is the means through which this is achieved. Seamless and sophisticated synergies are required for analysing spatio-temporal data and solving spatio-temporal problems. In modern society, spatio-temporal analysis is not solely the business of professional analysts. Many citizens need or would be interested in undertaking analysis of information in time and space. Researchers should find approaches to deal with the complexities of the current data and problems and find ways to make analytical tools accessible and usable for the broad community of potential users to support spatio-temporal thinking and contribute to solving a large range of problems.
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| 2. |
- Peca, Iulian, et al.
(författare)
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Scalable Cluster Analysis of Spatial Events
- 2012
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Ingår i: EuroVA 2012: International Workshop on Visual Analytics. - : Eurographics - European Association for Computer Graphics. ; , s. 19-23
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Konferensbidrag (refereegranskat)abstract
- Clustering of massive data is an important analysis tool but also challenging since the data often does not fit in RAM. Many clustering algorithms are thus severely memory-bound. This paper proposes a deterministic density clustering algorithm based on DBSCAN that allows to discover arbitrary shaped clusters of spatio-temporal events that (1) achieves scalability to very large datasets not fitting in RAM and (2) exhibits significant execution time improvements for processing the full dataset compared to plain DBSCAN. The proposed algorithm's integration with interactive visualization methods allows for visual inspection of clustering results in the context of the analysis task; several alternatives are discussed by means of an application example about traffic data analysis.
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| 3. |
- Vrotsou, Katerina, et al.
(författare)
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Exploring City Structure from Georeferenced Photos Using Graph Centrality Measures
- 2011
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Ingår i: Machine Learning and Knowledge Discovery in Databases. - Berlin, Heidelberg : Springer. - 9783642238079 - 9783642238086 ; , s. 654-657
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Bokkapitel (refereegranskat)abstract
- We explore the potential of applying graph theory measures of centrality to the network of movements extracted from sequences of georeferenced photo captures in order to identify interesting places and explore city structure. We adopt a systematic procedure composed of a series of stages involving the combination of computational methods and interactive visual analytics techniques. The approach is demonstrated using a collection of Flickr photos from the Seattle metropolitan area.
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| 4. |
- Vrotsou, Katerina, et al.
(författare)
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Interactive Exploration of Events and Presence of People in Space and Time through KD-Photomap
- 2012
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Ingår i: AVI '12 Proceedings of the International Working Conference on Advanced Visual Interfaces. - New York, NY, USA : ACM Press. - 9781450312875 ; , s. 804-805
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- We explore people's activities in space and time by analysing publicly available georefenced photographs. We do this using KD-photomap, a web-based visual analytics system for exploring collections of Flickr photographs and meta-data associated with them. The system provides an interface for flexible browsing of photographs in search of interesting pictures, and places, and also a framework for exploration of presence and identification of events in space and time.
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| 5. |
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| 6. |
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| 7. |
- Ho, Quan, 1975-
(författare)
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Architecture and Applications of a Geovisual Analytics Framework
- 2013
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The large and ever-increasing amounts of multi-dimensional, multivariate, multi-source, spatio-temporal data represent a major challenge for the future. The need to analyse and make decisions based on these data streams, often in time-critical situations, demands integrated, automatic and sophisticated interactive tools that aid the user to manage, process, visualize and interact with large data spaces. The rise of `Web 2.0', which is undisputedly linked with developments such as blogs, wikis and social networking, and the internet usage explosion in the last decade represent another challenge for adapting these tools to the Internet to reach a broader user community. In this context, the research presented in this thesis introduces an effective web-enabled geovisual analytics framework implemented, applied and verified in Adobe Flash ActionScript and HTML5/JavaScript. It has been developed based on the principles behind Visual Analytics and designed to significantly reduce the time and effort needed to develop customized web-enabled applications for geovisual analytics tasks and to bring the benefits of visual analytics to the public. The framework has been developed based on a component architecture and includes a wide range of visualization techniques enhanced with various interaction techniques and interactive features to support better data exploration and analysis. The importance of multiple coordinated and linked views is emphasized and a number of effective techniques for linking views are introduced.Research has so far focused more on tools that explore and present data while tools that support capturing and sharing gained insight have not received the same attention. Therefore, this is one of the focuses of the research presented in this thesis. A snapshot technique is introduced, which supports capturing discoveries made during the exploratory data analysis process and can be used for sharing gained knowledge.The thesis also presents a number of applications developed to verify the usability and the overall performance of the framework for the visualization, exploration and analysis of data in different domains. Four application scenarios are presented introducing (1) the synergies among information visualization methods, geovisualization methods and volume data visualization methods for the exploration and correlation of spatio-temporal ocean data, (2) effective techniques for the visualization, exploration and analysis of self-organizing network data, (3) effective flow visualization techniques applied to the analysis of time-varying spatial interaction data such as migration data, commuting data and trade flow data, and (4) effective techniques for the visualization, exploration and analysis of flood data.
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