| 1. |
- 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. |
- van den Elzen, Stef, et al.
(författare)
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The Flow of Trust : A Visualization Framework to Externalize, Explore, and Explain Trust in ML Applications
- 2023
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Ingår i: IEEE Computer Graphics and Applications. - : IEEE Computer Society. - 0272-1716 .- 1558-1756. ; 43:2, s. 78-88
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Tidskriftsartikel (refereegranskat)abstract
- We present a conceptual framework for the development of visual interactive techniques to formalize and externalize trust in machine learning (ML) workflows. Currently, trust in ML applications is an implicit process that takes place in the user-s mind. As such, there is no method of feedback or communication of trust that can be acted upon. Our framework will be instrumental in developing interactive visualization approaches that will help users to efficiently and effectively build and communicate trust in ways that fit each of the ML process stages. We formulate several research questions and directions that include: 1) a typology/taxonomy of trust objects, trust issues, and possible reasons for (mis)trust; 2) formalisms to represent trust in machine-readable form; 3) means by which users can express their state of trust by interacting with a computer system (e.g., text, drawing, marking); 4) ways in which a system can facilitate users- expression and communication of the state of trust; and 5) creation of visual interactive techniques for representation and exploration of trust over all stages of an ML pipeline.
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| 4. |
- von Landesberger, Tatiana, et al.
(författare)
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MobilityGraphs : Visual Analysis of Mass Mobility Dynamics via Spatio-Temporal Graphs and Clustering
- 2016
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Ingår i: IEEE Transactions on Visualization and Computer Graphics. - : IEEE. - 1077-2626 .- 1941-0506. ; 22:1, s. 11-20
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Tidskriftsartikel (refereegranskat)abstract
- Learning more about people mobility is an important task for official decision makers and urban planners. Mobility data sets characterize the variation of the presence of people in different places over time as well as movements (or flows) of people between the places. The analysis of mobility data is challenging due to the need to analyze and compare spatial situations (i.e., presence and flows of people in certain time intervals) and to gain an understanding of the spatio-temporal changes (variations of situations over time). Traditional flow visualizations usually fail due to massive clutter. Modern approaches offer limited support for investigating the complex variation of the movements over longer time periods.We propose a visual analytics methodology that solves these issues by combined spatial and temporal simplifications. We have developed a graph-based method, called MobilityGraphs, which reveals movement patterns that were occluded in flow maps. Our method enables the visual representation of the spatio-temporal variation of movements for long time series of spatial situations originally containing a large number of intersecting flows. The interactive system supports data exploration from various perspectives and at various levels of detail by interactive setting of clustering parameters. The feasibility our approach was tested on aggregated mobility data derived from a set of geolocated Twitter posts within the Greater London city area and mobile phone call data records in Abidjan, Ivory Coast. We could show that MobilityGraphs support the identification of regular daily and weekly movement patterns of resident population.
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| 5. |
- Vrotsou, Katerina, 1980-, et al.
(författare)
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An Interactive Approach for Exploration of Flows Through Direction-Based Filtering
- 2017
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Ingår i: Journal of Geovisualization and Spatial Analysis. - : Springer. - 2509-8810 .- 2509-8829. ; 1:1-2
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Tidskriftsartikel (refereegranskat)abstract
- This paper is concerned with the representation and exploration of flows, defined as spatial interactions between geographic locations. Flows are challenging to display in a comprehensible manner due to the nature of the data, which are characterized by many crossings and overlaps leading to clutter. A number of different strategies have been suggested for addressing this problem, which commonly involve reducing the search space, aggregating the data or simplifying the representations often at the cost of information loss or distortion of spatial context. We propose an interactive approach for exploring large and highly connected networks of flows without distorting the geographical space and without losing the context overview in the process. The approach is based on a flow-specific interaction technique for filtering the data by direction, that enables an analyst to successively identify underlying spatial arrangement patterns. We illustrate our approach through exploring flows of tourists and locals in the Greater London area.
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| 6. |
- 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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| 7. |
- 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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| 8. |
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| 9. |
- Vrotsou, Katerina, et al.
(författare)
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SimpliFly: A Methodology for Simplification and Thematic Enhancement of Trajectories
- 2015
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Ingår i: IEEE Transactions on Visualization and Computer Graphics. - : Institute of Electrical and Electronics Engineers (IEEE). - 1077-2626 .- 1941-0506. ; 21:1, s. 107-121
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Tidskriftsartikel (refereegranskat)abstract
- Movement data sets collected using todays advanced tracking devices consist of complex trajectories in terms of length, shape, and number of recorded positions. Multiple additional attributes characterizing the movement and its environment are often also included making the level of complexity even higher. Simplification of trajectories can improve the visibility of relevant information by reducing less relevant details while maintaining important movement patterns. We propose a systematic stepwise methodology for simplifying and thematically enhancing trajectories in order to support their visual analysis. The methodology is applied iteratively and is composed of: (a) a simplification step applied to reduce the morphological complexity of the trajectories, (b) a thematic enhancement step which aims at accentuating patterns of movement, and (c) the representation and interactive exploration of the results in order to make interpretations of the findings and further refinement to the simplification and enhancement process. We illustrate our methodology through an analysis example of two different types of tracks, aircraft and pedestrian movement.
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| 10. |
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| 11. |
- 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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| 12. |
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| 13. |
- Milutinovic, Goran
(författare)
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Computational and Visual Tools for Geospatial Multi-Criteria Decision-Making
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Geospatial multi-criteria decision-making usually concerns quasi-continuous choice models, with the number of alternatives constrained only by the limits of the used representation model. This sets high demands on the decision-making methods used in the context. The most commonly used approach in geospatial decision-making is combining a method for assigning criteria weights with an aggregation method. As pairwise comparison of alternatives is not feasible when the number of alternatives is large, the weights are usually assigned to criteria without considering the values or the value ranges of the alternatives, an approach often criticized in the decision analysis literature. Apart from criteria weighting controversy, this approach does not allow for advanced use of interactive visualization in the choice phase of the decision-making process. In this thesis, two alternative methods for geospatial decision-making based on the even swaps method are developed. The first method relies on automation of swaps, which makes this method viable for decision problems with any number of alternatives. The second method emanates from the findings of behavioral decision theory, and combines even swaps with reduction of large data sets through quasi-satisficing, allowing for efficient use of interactive visualization in the choice phase of the decision process. Visualization frameworks for both methods are also developed in the thesis. They include both geo-specific representations, such as interactive maps, and infovis techniques such as graphs, diagrams, scatterplots and parallel coordinates. Two studies concerning the impact of interactive visualization on decision-making are presented in the thesis: a study concerning the impact of interactive visualization on geospatial decision-making, and a study concerning potential effects of visual saliency on decision-making. The results of the first study indicated positive effects of interactive visualization on coherency and consistency in performing trade-offs. The results of the second study show that visual saliency may help decision-makers make better decisions. The work presented in this thesis contributes to method development and the use of interactive visualization in the context of geospatial decision-making.
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| 14. |
- Nanni, Mirco, et al.
(författare)
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Give more data, awareness and control to individual citizens, and they will help COVID-19 containment
- 2020
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Ingår i: Transactions on Data Privacy. - : Institut d'Investigació en Intel·ligència Artificial. - 1888-5063 .- 2013-1631. ; 23, s. 1-6
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Tidskriftsartikel (refereegranskat)abstract
- The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the "phase 2" of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are being proposed for large scale adoption by many countries. A centralized approach, where data sensed by the app are all sent to a nation-wide server, raises concerns about citizens' privacy and needlessly strong digital surveillance, thus alerting us to the need to minimize personal data collection and avoiding location tracking. We advocate the conceptual advantage of a decentralized approach, where both contact and location data are collected exclusively in individual citizens' "personal data stores", to be shared separately and selectively (e.g., with a backend system, but possibly also with other citizens), voluntarily, only when the citizen has tested positive for COVID-19, and with a privacy preserving level of granularity. This approach better protects the personal sphere of citizens and affords multiple benefits: it allows for detailed information gathering for infected people in a privacy-preserving fashion; and, in turn this enables both contact tracing, and, the early detection of outbreak hotspots on more finely-granulated geographic scale. The decentralized approach is also scalable to large populations, in that only the data of positive patients need be handled at a central level. Our recommendation is two-fold. First to extend existing decentralized architectures with a light touch, in order to manage the collection of location data locally on the device, and allowthe user to share spatio-temporal aggregates - if and when they want and for specific aims - with health authorities, for instance. Second, we favour a longerterm pursuit of realizing a Personal Data Store vision, giving users the opportunity to contribute to collective good in the measure they want, enhancing self-awareness, and cultivating collective efforts for rebuilding society.
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