Exploration and analysis of high-dimensional data are important tasks in many fields that produce large and complex data, like the financial sector, systems biology, or cultural heritage. Tailor-made visual analytics software is developed for each specific application, limiting their applicability in other fields. However, as diverse as these fields are, their characteristics and requirements for data analysis are conceptually similar. Many applications share abstract tasks and data types and are often constructed with similar building blocks. Developing such applications, even when based mostly on existing building blocks, requires significant engineering efforts. We developed ManiVault, a flexible and extensible open-source visual analytics framework for analyzing high-dimensional data. The primary objective of ManiVault is to facilitate rapid prototyping of visual analytics workflows for visualization software developers and practitioners alike. ManiVault is built using a plugin-based architecture that offers easy extensibility. While our architecture deliberately keeps plugins self-contained, to guarantee maximum flexibility and re-usability, we have designed and implemented a messaging API for tight integration and linking of modules to support common visual analytics design patterns. We provide several visualization and analytics plugins, and ManiVault's API makes the integration of new plugins easy for developers. ManiVault facilitates the distribution of visualization and analysis pipelines and results for practitioners through saving and reproducing complete application states. As such, ManiVault can be used as a communication tool among researchers to discuss workflows and results. A copy of this paper and all supplemental material is available at https://osf.io/9k6jw and source code at https://github.com/ManiVaultStudio.

翻译：高维数据的探索与分析是金融、系统生物学、文化遗产等众多产生大规模复杂数据领域的重要任务。人们针对特定应用开发定制化的可视化分析软件，这限制了其在其他领域的适用性。然而，尽管这些领域差异显著，其数据分析的特性与需求在概念上却具有相似性。许多应用共享抽象任务与数据类型，并常以相似的构建模块进行构建。开发此类应用，即使主要基于现有构建模块，仍需要大量的工程投入。我们研发了ManiVault——一个灵活、可扩展的高维数据分析开源可视化分析框架。ManiVault的主要目标是帮助可视化软件开发者和实践者快速构建可视化分析工作流原型。ManiVault采用基于插件的架构，提供便捷的可扩展性。在刻意保持插件模块独立性的同时，为确保最大灵活性和可重用性，我们设计并实现了一套消息传递API，用于模块间紧密集成与联动，以支持常见的可视化分析设计模式。我们提供了多个可视化与分析插件，ManiVault的API使开发者能够轻松集成新插件。通过保存并复现完整应用状态，ManiVault便于实践者分发可视化与分析流程及结果。因此，ManiVault可作为研究人员讨论工作流与结果的交流工具。本文及补充材料副本见https://osf.io/9k6jw，源代码见https://github.com/ManiVaultStudio。