Panse Christian, Sips Mike, Keim Daniel A, North Stephen C
Functional Genomics Center, Uni/ETH, Zurich, Switzerland.
IEEE Trans Vis Comput Graph. 2006 Sep-Oct;12(5):749-56. doi: 10.1109/TVCG.2006.198.
In many applications, data is collected and indexed by geo-spatial location. Discovering interesting patterns through visualization is an important way of gaining insight about such data. A previously proposed approach is to apply local placement functions such as PixelMaps that transform the input data set into a solution set that preserves certain constraints while making interesting patterns more obvious and avoid data loss from overplotting. In experience, this family of spatial transformations can reveal fine structures in large point sets, but it is sometimes difficult to relate those structures to basic geographic features such as cities and regional boundaries. Recent information visualization research has addressed other types of transformation functions that make spatially-transformed maps with recognizable shapes. These types of spatial-transformation are called global shape functions. In particular, cartogram-based map distortion has been studied. On the other hand, cartogram-based distortion does not handle point sets readily. In this study, we present a framework that allows the user to specify a global shape function and a local placement function. We combine cartogram-based layout (global shape) with PixelMaps (local placement), obtaining some of the benefits of each toward improved exploration of dense geo-spatial data sets.
在许多应用中，数据是按地理空间位置进行收集和索引的。通过可视化发现有趣的模式是深入了解此类数据的重要途径。一种先前提出的方法是应用诸如像素图之类的局部布局函数，将输入数据集转换为一个解集，该解集在保留某些约束条件的同时，使有趣的模式更加明显，并避免因重叠而导致的数据丢失。根据经验，这类空间变换可以揭示大的点集中的精细结构，但有时很难将这些结构与诸如城市和区域边界等基本地理特征联系起来。最近的信息可视化研究涉及了其他类型的变换函数，这些函数能生成具有可识别形状的空间变换地图。这类空间变换被称为全局形状函数。特别是，基于变形地图的地图变形已经得到了研究。另一方面，基于变形地图的变形不易处理点集。在本研究中，我们提出了一个框架，允许用户指定一个全局形状函数和一个局部布局函数。我们将基于变形地图的布局（全局形状）与像素图（局部布局）相结合，从这两者中各获得一些益处，以改进对密集地理空间数据集的探索。
