14,050 research outputs found

    VisDB: Database Exploration

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    Visualizing and Interacting with Concept Hierarchies

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    Concept Hierarchies and Formal Concept Analysis are theoretically well grounded and largely experimented methods. They rely on line diagrams called Galois lattices for visualizing and analysing object-attribute sets. Galois lattices are visually seducing and conceptually rich for experts. However they present important drawbacks due to their concept oriented overall structure: analysing what they show is difficult for non experts, navigation is cumbersome, interaction is poor, and scalability is a deep bottleneck for visual interpretation even for experts. In this paper we introduce semantic probes as a means to overcome many of these problems and extend usability and application possibilities of traditional FCA visualization methods. Semantic probes are visual user centred objects which extract and organize reduced Galois sub-hierarchies. They are simpler, clearer, and they provide a better navigation support through a rich set of interaction possibilities. Since probe driven sub-hierarchies are limited to users focus, scalability is under control and interpretation is facilitated. After some successful experiments, several applications are being developed with the remaining problem of finding a compromise between simplicity and conceptual expressivity

    Possibilities and Limits in Visualizing Large Amounts of Multidimensional Data

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    In this paper, we describe our concepts to visualize very large amounts of multidimensional data. Our visualization technique which has been developed to support querying of large scientific databases is designed to visualize as many data items as possible on current display devices. Even if we are able to use each pixel of the display device to visualize one data item, the number of data items that can be visualized is quite limited. Therefore, in our system we introduce reference points (or regions) in multidimensional space and consider only those data items which are 'close' to the reference point. The data items are arranged according to their distance from the reference point. Multiple windows are used for the different dimensions of the data with the distance of each of the dimensions from the reference point (or region) being represented by color. In exploring the database, the reference point (or region) may be changed interactively, allowing different portions of the database to be visualized. To visualize larger portions of the database, sequences of visualizations may be generated automatically by moving the reference point along some path in multidimensional space. Besides describing our visualization technique and several alternatives, we discuss some of the perceptual issues that arise in connection with our visualization technique

    Exploring user and system requirements of linked data visualization through a visual dashboard approach

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    One of the open problems in SemanticWeb research is which tools should be provided to users to explore linked data. This is even more urgent now that massive amount of linked data is being released by governments worldwide. The development of single dedicated visualization applications is increasing, but the problem of exploring unknown linked data to gain a good understanding of what is contained is still open. An effective generic solution must take into account the user’s point of view, their tasks and interaction, as well as the system’s capabilities and the technical constraints the technology imposes. This paper is a first step in understanding the implications of both, user and system by evaluating our dashboard-based approach. Though we observe a high user acceptance of the dashboard approach, our paper also highlights technical challenges arising out of complexities involving current infrastructure that need to be addressed while visualising linked data. In light of the findings, guidelines for the development of linked data visualization (and manipulation) are provided

    Supporting Data mining of large databases by visual feedback queries

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    In this paper, we describe a query system that provides visual relevance feedback in querying large databases. Our goal is to support the process of data mining by representing as many data items as possible on the display. By arranging and coloring the data items as pixels according to their relevance for the query, the user gets a visual impression of the resulting data set. Using an interactive query interface, the user may change the query dynamically and receives immediate feedback by the visual representation of the resulting data set. Furthermore, by using multiple windows for different parts of a complex query, the user gets visual feedback for each part of the query and, therefore, may easier understand the overall result. Our system allows to represent the largest amount of data that can be visualized on current display technology, provides valuable feedback in querying the database, and allows the user to find results which, otherwise, would remain hidden in the database

    Interactive tag maps and tag clouds for the multiscale exploration of large spatio-temporal datasets

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    'Tag clouds' and 'tag maps' are introduced to represent geographically referenced text. In combination, these aspatial and spatial views are used to explore a large structured spatio-temporal data set by providing overviews and filtering by text and geography. Prototypes are implemented using freely available technologies including Google Earth and Yahoo! 's Tag Map applet. The interactive tag map and tag cloud techniques and the rapid prototyping method used are informally evaluated through successes and limitations encountered. Preliminary evaluation suggests that the techniques may be useful for generating insights when visualizing large data sets containing geo-referenced text strings. The rapid prototyping approach enabled the technique to be developed and evaluated, leading to geovisualization through which a number of ideas were generated. Limitations of this approach are reflected upon. Tag placement, generalisation and prominence at different scales are issues which have come to light in this study that warrant further work

    The State-of-the-Art of Set Visualization

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    Sets comprise a generic data model that has been used in a variety of data analysis problems. Such problems involve analysing and visualizing set relations between multiple sets defined over the same collection of elements. However, visualizing sets is a non-trivial problem due to the large number of possible relations between them. We provide a systematic overview of state-of-the-art techniques for visualizing different kinds of set relations. We classify these techniques into six main categories according to the visual representations they use and the tasks they support. We compare the categories to provide guidance for choosing an appropriate technique for a given problem. Finally, we identify challenges in this area that need further research and propose possible directions to address these challenges. Further resources on set visualization are available at http://www.setviz.net

    A Brief Study of Open Source Graph Databases

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    With the proliferation of large irregular sparse relational datasets, new storage and analysis platforms have arisen to fill gaps in performance and capability left by conventional approaches built on traditional database technologies and query languages. Many of these platforms apply graph structures and analysis techniques to enable users to ingest, update, query and compute on the topological structure of these relationships represented as set(s) of edges between set(s) of vertices. To store and process Facebook-scale datasets, they must be able to support data sources with billions of edges, update rates of millions of updates per second, and complex analysis kernels. These platforms must provide intuitive interfaces that enable graph experts and novice programmers to write implementations of common graph algorithms. In this paper, we explore a variety of graph analysis and storage platforms. We compare their capabil- ities, interfaces, and performance by implementing and computing a set of real-world graph algorithms on synthetic graphs with up to 256 million edges. In the spirit of full disclosure, several authors are affiliated with the development of STINGER.Comment: WSSSPE13, 4 Pages, 18 Pages with Appendix, 25 figure

    Planning Support Systems: Progress, Predictions, and Speculations on the Shape of Things to Come

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    In this paper, we review the brief history of planning support systems, sketching the way both the fields of planning and the software that supports and informs various planning tasks have fragmented and diversified. This is due to many forces which range from changing conceptions of what planning is for and who should be involved, to the rapid dissemination of computers and their software, set against the general quest to build ever more generalized software products applicable to as many activities as possible. We identify two main drivers – the move to visualization which dominates our very interaction with the computer and the move to disseminate and share software data and ideas across the web. We attempt a brief and somewhat unsatisfactory classification of tools for PSS in terms of the planning process and the software that has evolved, but this does serve to point up the state-ofthe- art and to focus our attention on the near and medium term future. We illustrate many of these issues with three exemplars: first a land usetransportation model (LUTM) as part of a concern for climate change, second a visualization of cities in their third dimension which is driving an interest in what places look like and in London, a concern for high buildings, and finally various web-based services we are developing to share spatial data which in turn suggests ways in which stakeholders can begin to define urban issues collaboratively. All these are elements in the larger scheme of things – in the development of online collaboratories for planning support. Our review far from comprehensive and our examples are simply indicative, not definitive. We conclude with some brief suggestions for the future
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