In exploratory visualization systems, interactions allow to manipulate a visual representation and thereby gain insight into its supporting data. The responsiveness of these interactions is crucial, but achieving it on common hardware becomes increasingly difficult with the ever-growing size of datasets. Moreover, the representation of a large dataset itself is challenging since screen space is limited and, past a certain size, the number of items exceeds the number of pixels available or may render the representation unhelpful. The focus of this paper is on multidimensional data and parallel coordinates. For the system to be scalable, we propose a multiscale representation based on hierarchical aggregation on the client-side and distributed computing on a horizontally scalable infrastructure on the server-side. Multiscale visualization builds on several levels of abstraction to provide interactive and incremental changes in the level of detail. Horizontal scalability refers to the ability to increase the resources of the computing infrastructure by connecting additional computers. This paper presents: (1) a graph-based formalism for describing multiscale representations of parallel coordinates and their interactions and (2) a client-server system with a focus+context representation for multiscale parallel coordinates and distributed computation on a remote data-intensive infrastructure. We leverage the proposed formalism to describe several design possibilities for usual interactions in parallel coordinates, hierarchical navigation, and edition. We illustrated the scalability and usage of the representation in a real-world case. Performance experiments demonstrate that on a 15-computer cluster, the prototype system can scale to billion-item datasets while preserving the interactivity for analysis.

在探索性可视化系统中，交互作用可以操纵视觉表示，从而深入了解其支持数据。这些交互的响应能力至关重要，但是随着数据集规模的不断扩大，在通用硬件上实现响应变得越来越困难。此外，大型数据集的表示本身具有挑战性，因为屏幕空间有限，并且超过一定大小后，项数超过了可用像素数，或者可能使表示无益。本文的重点是多维数据和平行坐标。为了使系统具有可伸缩性，我们提出了一种基于客户端侧的分层聚合以及服务器端的水平可伸缩基础结构上的分布式计算的多尺度表示。多尺度可视化建立在几个抽象级别上，以提供详细级别的交互式和增量更改。水平可伸缩性是指通过连接其他计算机来增加计算基础结构资源的能力。本文提出：（1）基于图的形式主义，用于描述并行坐标及其相互作用的多尺度表示；（2）具有焦点+上下文表示的客户端-服务器系统，用于多尺度并行坐标和远程数据密集型的分布式计算基础设施。我们利用提出的形式主义来描述平行坐标，层次导航和版本中常见交互的几种设计可能性。我们说明了在实际情况下表示的可伸缩性和用法。