Collection Space Navigator：面向多维数据集的交互式可视化界面
Collection Space Navigator: An Interactive Visualization Interface for Multidimensional Datasets
AI总结：
针对多维数据相关视觉数字工件集合探索分析的挑战，本文提出开源的Collection Space Navigator（CSN）交互式可视化工具，结合二维投影与多维过滤器，支持缩放、投影转换等操作，助力用户探索、整理集合并反馈见解。
摘要：
我们介绍了Collection Space Navigator（CSN），这是一款基于浏览器的可视化工具，用于探索、研究和整理与多维数据（如向量嵌入或元数据表）相关的大型视觉数字工件集合。图像等媒体对象通常被编码为数值向量，例如基于元数据或使用机器学习嵌入图像信息。然而，尽管此类过程在多种应用中广泛使用，但以更全面的方式探索、分析和理解生成的多维空间仍然是一个挑战。t-SNE或UMAP等降维技术常被用于将高维数据投影到低维可视化中，但由于剩余维度通常是抽象的，这些技术本身也需要解释。在此，Collection Space Navigator提供了一个可定制的界面，将二维投影与一组可配置的多维过滤器相结合。因此，用户能够通过缩放、在投影之间转换、通过范围滑块过滤维度以及使用高级文本过滤器来查看和研究集合。交互过程中获得的见解可以通过临时导出过滤后的元数据和投影反馈到原始数据中。本文附带了一个功能展示演示，使用了一个大型数字化西方古典艺术收藏。Collection Space Navigator是开源的。用户可以重新配置界面以适应自己的数据和研究需求，包括投影和过滤控件。CSN已准备好服务于广泛的社区。
英文摘要：
We introduce the Collection Space Navigator (CSN), a browser-based visualization tool to explore, research, and curate large collections of visual digital artifacts that are associated with multidimensional data, such as vector embeddings or tables of metadata. Media objects such as images are often encoded as numerical vectors, for e.g. based on metadata or using machine learning to embed image information. Yet, while such procedures are widespread for a range of applications, it remains a challenge to explore, analyze, and understand the resulting multidimensional spaces in a more comprehensive manner. Dimensionality reduction techniques such as t-SNE or UMAP often serve to project high-dimensional data into low dimensional visualizations, yet require interpretation themselves as the remaining dimensions are typically abstract. Here, the Collection Space Navigator provides a customizable interface that combines two-dimensional projections with a set of configurable multidimensional filters. As a result, the user is able to view and investigate collections, by zooming and scaling, by transforming between projections, by filtering dimensions via range sliders, and advanced text filters. Insights that are gained during the interaction can be fed back into the original data via ad hoc exports of filtered metadata and projections. This paper comes with a functional showcase demo using a large digitized collection of classical Western art. The Collection Space Navigator is open source. Users can reconfigure the interface to fit their own data and research needs, including projections and filter controls. The CSN is ready to serve a broad community.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
