Information Visualization

Comparing data collected on the movement of an entity to data on the location where the entity was reported to have been can be useful in monitoring and enforcement situations. Anomalies between these datasets may be indicative of illegal activity, systematic reporting errors, data entry errors, or equipment failure. While finding obvious anomalies may be a simple task, the discovery of more subtle inconsistencies can be challenging when there is a mismatch in the temporal granularity between the datasets, or when they cover large temporal and geographic ranges. We have developed a geovisual analytics approach called Visual Exploration of Movement-Event Anomalies (VEMEA) that automatically extracts potential anomalies from the data, visually encodes these on a map, and provides interactive filtering and exploration tools to allow expert analysts to investigate and evaluate the anomalies. Using two case studies from the fisheries enforcement domain, the value of VEMEA is illustrated for both confirmatory and exploratory data analysis tasks. Field trial evaluations conducted with expert fisheries data analysts further support the benefits of the approach.

Polyline glyphs are minimized thumbnails of polylines from parallel coordinates. Since such glyphs may augment the usability of parallel coordinates, the authors investigate whether there are benefits to be derived from using polyline glyphs that are dynamically linked to parallel coordinates as opposed to the use of the latter visualization technique alone. They also identify user tasks that can be effectively solved if parallel coordinates dynamically linked to polyline glyphs are used. This study adds to the body of previous work a discussion on the features of the polyline glyphs that facilitate the exploration and understanding of multivariate data. Moreover, the authors conduct an empirical study in which parallel coordinates dynamically linked to polyline glyphs are used to solve four tasks. The main finding is that polyline glyphs can facilitate a better insight into the similarities between the multivariate signatures of data items and information acquisition if visual clutter hinders the use of parallel coordinates. The study also reveals that if visual clutter does not occur in parallel coordinates and the polylines from the latter can be differentiated, individuals tend not to use polyline glyphs to study multivariate signatures.

In geographic information systems, pictorial query languages are visual languages which make easier the user to express queries by free-hand drawing. In this perspective, this article proposes an approach to provide approximate answers to pictorial queries that do not match with the content of the database, that is, the results are null. It addresses the polyline–polyline topological relationships and is based on an algorithm, called Approximate Answer Computation algorithm, which exploits the notions of Operator Conceptual Neighborhood graph and 16-intersection matrix. The operator conceptual neighborhood graph represents the conceptual topological neighborhood between Symbolic Graphical Objects and is used for relaxing constraints of queries. The nodes of the operator conceptual neighborhood graph are labeled with geo-operators whose semantics has been formalized. The 16-intersection matrix provides enriched query details with respect to the well-known Dimensionally Extended 9-Intersection Model proposed in the literature. A set of minimal 16-intersection matrices associated with each node of the operator conceptual neighborhood graph, upon the external space connectivity condition, is defined and the proof of its minimality is provided. The main idea behind each introduced notion is illustrated using a running example throughout this article.

As an extension of classical sets, fuzzy sets allow their containing elements to have continuous membership, which broadens its applications in various domains. In order to visualize the uncertain owner–member relationship, we design an intuitive diagram to visualize fuzzy sets. The diagram has a freeform boundary, which allows a clear layout of the data. In addition, the opacity of the diagram reveals the uncertainty of the membership. Physical simulation and bi-harmonic interpolation are introduced to generate the proposed diagram. We test our method with different fuzzy sets. The results show that our method is efficient to generate intuitive visualization of fuzzy sets.

In this article, we describe a general purpose system that, given as input a segmented/classified image, automatically provides different visual outputs exploiting solid colors, color boundaries, and transparent colors. Moreover, if the names of the classes are given, the system automatically places a textual label in the less salient sub-region of the corresponding class. For color-class association and class label placement, we take into account the underlying image color and structure exploiting both saliency and superpixel representation. The color selection and the color-class association are formulated both as optimization problems and heuristically solved using a Local Search procedure. Results show the effectiveness of the proposed system on images having different content and different number of annotated regions.