Scientific Data Repository

This project is the first to combine the notion of a data repository with real-time visual analytics for interactive data mining and exploratory analysis on the web. This large comprehensive collection of data is useful for making significant research findings as well as benchmark data sets for a wide variety of applications and domains and includes relational, attributed, heterogeneous, streaming, spatial, and time series data as well as non-relational machine learning data. All data sets are easily downloaded into a standard consistent format. We also have built a multi-level interactive visual analytics engine that allows users to visualize and interactively explore the data in a free-flowing manner.

本项目首次将数据存储库（data repository）的概念与面向网页端交互式数据挖掘及探索性分析的实时可视化分析技术相结合。这套规模庞大、内容全面的数据集集合，既可用于产出具有重要学术价值的研究成果，也可作为各类应用场景与研究领域的基准数据集，涵盖关系型数据（relational data）、属性型数据（attributed data）、异构型数据（heterogeneous data）、流数据（streaming data）、空间数据（spatial data）及时序数据（time series data），同时包含非关系型机器学习数据（non-relational machine learning data）。所有数据集均可便捷下载为统一标准格式。此外，本项目还搭建了多级交互式可视化分析引擎，支持用户以自由流畅的方式对数据进行可视化呈现与交互式探索。

搜集汇总

背景与挑战

背景概述

这是一个集成了实时可视化分析的科学数据仓库，首次在网络上实现了数据仓库与交互式数据挖掘及探索分析的结合。该仓库包含大量多类型科学数据集，支持标准格式下载，并提供了多级交互式可视化分析引擎供用户自由探索。