Exploring Large Digital Library Collections Using a Map-Based Visualisation

In this paper we describe a novel approach for exploring large document collections using a map-based visualisation. We use hierarchically structured semantic concepts that are attached to the documents to create a visualisation of the semantic space that resembles a Google Map. The approach is novel in that we exploit the hierarchical structure to enable the approach to scale to large document collections and to create a map where the higher levels of spatial abstraction have semantic meaning. An informal evaluation is carried out to gather subjective feedback from users. Overall results are positive with users finding the visualisation enticing and easy to use

Geospatial Semantics: Why, of What, and How?

Abstract. Why are notions like semantics and ontologies suddenly getting so much attention, within and outside geospatial information communities? The main reason lies in the componentization of Geographic Information Systems (GIS) into services, which are supposed to interoperate within and across these communities. Consequently, I look at geospatial semantics in the context of semantic interoperability. The paper clarifies the relevant notion of semantics and shows what parts of geospatial information need to receive semantic speci-fications in order to achieve interoperability. No attempt at a survey of ap-proaches to provide semantics is made, but a framework for solving interopera-bility problems is proposed in the form of semantic reference systems. Particular emphasis is put on the need and possible ways to ground geospatial semantics in physical processes and measurements. 1. Introduction: Wh

Geovisualization and synergies from InfoVis and visual analytics

Geovisualization (GeoViz) is an intrinsically complex process. The analyst needs to look at data from various perspectives and at various scales, from "seeing the whole" to "attending to particulars" (Andrienko and Andrienko 2006). The analyst is also supposed to "see in relation", i.e. make numerous comparisons. This inherent complexity is multiplied by the complexity of the data that is explored and analyzed. The complex, multivariate data structure and heterogeneous components of most contemporary datasets necessitate a combined use of multiple techniques and approaches. There is no single visualization method capable to show "the whole". The analyst has to decompose this whole into views, examine these views and then try to synthesize the whole picture from the partial views. Also, because of large data volumes, we must use methods capable of simultaneously providing an overall view and exposing various "particulars". Looking for "particulars" requires therefore different techniques than "seeing the whole". Some existing visualization tools such as GeoVista and CommonGIS have successfully demonstrated the advantage of multiple-linked views and the use of information visualization (InfoViz) methods such as Parallel Coordinates and Heat maps to explore spatial multivariate data

3D Network spatialization: Does it add depth to 2D representations of semantic proximity?

Spatialized views use visuo-spatial metaphors to facilitate sense-making from complex non-spatial databases. Spatialization typically includes the projection of a high-dimensional (non-spatial) data space onto a lower dimensional display space for visual data exploration. In comparison to 2D spatialized displays, 3D displays could potentially convey more information, as they employ all three available spatial display dimensions. In this study, we evaluate if this advantage exists and whether it outweighs the added cognitive, perceptual, and technological costs of 3D displays. In a controlled human-subjects experiment, we investigated how viewers identify document similarity in 3D network spatializations that depict news articles as points connected by links. Our quantitative findings suggest that similarity ratings for 3D network displays are similar to those obtained in a prior 2D study we conducted. With both types of displays, viewers mostly judged document similarity on the basis of metric distances along network links, as opposed to node counts or distance across the network links. However, node counts do affect similarity assessments with 3D displays more than with 2D displays. We also find no significant differences in similarity judgments whether 3D displays are presented monoscopically or stereoscopically. We conclude that any advantage of 3D displays in conveying more information than 2D displays does not necessarily outweigh their additional demands on cognitive, perceptual, and technological resources

Testing the First Law of Cognitive Geography on Point-Display Spatializations

Spatializations are computer visualizations in which nonspatial information is depicted spatially. Spatializations of large databases commonly use distance as a metaphor to depict semantic (nonspatial) similarities among data items. By analogy to the "first law of geography", which states that closer things tend to be more similar, we propose a "first law of cognitive geography," which states that people believe closer things are more similar. In this paper, we present two experiments that investigate the validity of the first law of cognitive geography as applied to the interpretation of "point-display spatializations." Point displays depict documents (or other information-bearing entities) as 2- or 3-dimensional collections of points. Our results largely support the first law of cognitive geography and enrich it by identifying different types of distance that may be metaphorically related to similarity. We also identify characteristics of point displays other than distance relationships that influence similarity judgments

How do decision time and realism affect map-based decision making?

We commonly make decisions based on different kinds of maps, and under varying time constraints. The accuracy of these decisions often can decide even over life and death. In this study, we investigate how varying time constraints and different map types can influence people’s visuo-spatial decision making, specifically for a complex slope detection task involving three spatial dimensions. We find that participants’ response accuracy and response confidence do not decrease linearly, as hypothesized, when given less response time. Assessing collected responses within the signal detection theory framework, we find that different inference error types occur with different map types. Finally, we replicate previous findings suggesting that while people might prefer more realistic looking maps, they do not necessarily perform better with them

Similarity metrics for set of experience knowledge structure

When referring to knowledge forms, collecting formal decision events in a knowledge-explicit way becomes an important development. Set of experience knowledge structure can assist in accomplishing this purpose. However, to make set of experience knowledge structure useful, it must be classifiable and comparable. The purpose of this paper is to show similarity metrics for set of experience knowledge structure, and within, similarity metrics for its components: variables, functions, constraints, and rules. A comparable and classifiable set of experience would make explicit knowledge of formal decision events useful elements in multiple systems and technologies

Drawing Clustered Graphs as Topographic Maps

The visualization of clustered graphs is an essential tool for the analysis of networks, in particular, social networks, in which clustering techniques like community detection can reveal various structural properties. In this paper, we show how clustered graphs can be drawn as topographic maps, a type of map easily understandable by users not familiar with information visualization. Elevation levels of connected entities correspond to the nested structure of the cluster hierarchy. We present methods for initial node placement and describe a tree mapping based algorithm that produces an area efficient layout. Given this layout, a triangular irregular mesh is generated that is used to extract the elevation data for rendering the map. In addition, the mesh enables the routing of edges based on the topographic features of the map