Migrant Boat Mini Challenge Award: Simple and Effective Integrated Display Geo-Temporal Analysis of migrant boats

Miklin, R.; Lipić, Tomislav; Konyha, Z.; Beric, M.; Freiler, W.; Matković, Krešimir; Gračanin, Denis

doi:10.1109/vast.2008.4677387

Cited by 1 publication

(1 citation statement)

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“…Our entry in that challenge [11] describe the use our CMV system (ComVis tool [8]) that, in connection with some helper applications and Google Earth, allowed us to explore geo-temporal characteristics of the data set and answer the challenge questions. We build on these results in order to improve the visualization and analytical capabilities by adding new views to the CMV system…”

Section: Introductionmentioning

confidence: 99%

Event Line View: Interactive Visual Analysis of Irregular Time-Dependent Data

Matković¹,

Lež²,

Gračanin³

et al. 2010

Smart Graphics

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Abstract. In this paper we present a novel approach to visualize irregularly occurring events. We introduce the event line view designed specifically for such events data (a subset of time dependent data). The event line view is integrated in a coordinated multiple views (CMV) system and linked with other conventional views to support interactive visual analysis. The main idea is to analyze events relative to two categorical attributes from a multidimensional multivariate dataset. Since we are interested in the categorical dimension we have also integrated and linked the tag cloud view in the CMV system. To the best of our knowledge this is the first integration of the tag cloud view in a CMV system. The tag cloud view can depict a ratio of the selected items versus the non-selected items. The proposed approach is illustrated using the VAST Challenge 2008 Geo-Spatial data set that contains data on interdiction or landing of illegal immigrants in the USA. It is a multivariate multidimensional dataset with irregular events that illustrates the potential and capabilities of the proposed approach and the developed CMV system.

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Section: Introductionmentioning

confidence: 99%