We are surrounded by overwhelming big data, which brings substantial advances but meanwhile poses many challenges. Geospatial big data comprises a big portion of big data, and is essential and powerful for decision-making if being utilized strategically. Volumes in size and high dimensions are two of the major challenges that prevent strategic decision-making from (geospatial) big data. Interactive map-based and geovisualization enabled web applications are intuitive and useful to construct knowledge and reveal insights from high-dimensional (geospatial) big data for actionable decision-making. We propose an interactive and data-driven web mapping framework, named idwMapper, for visualizing and sensing high dimensional geospatial (big) data in an interactive and scalable manner. To demonstrate the wide applicability and usefulness of our framework, we have applied our idwMapper framework to three real-world case studies and implemented three corresponding web map applications: iLit4GEE-AI, iWURanking, and iTRELISmap. We expect and hope the three web maps demonstrated in different domains, from literature big data analysis through world university ranking to scholar mapping, will provide a good start and inspire researchers and practitioners in various domains to apply our idwMapper to solve (or at least aid them in solving) their impactful problems.

翻译：我们被海量大数据所包围，这带来了显著进步的同时也引发诸多挑战。地理空间大数据作为大数据的重要组成部分，若能战略性地加以运用，将对决策制定至关重要且作用强大。数据规模庞大与维度高这两个主要障碍，制约了基于（地理空间）大数据的战略性决策制定。基于交互式地图并启用地理可视化的网络应用，能够直观有效地从高维（地理空间）大数据中构建知识并揭示洞察，从而支持可操作的决策制定。我们提出一种名为idwMapper的交互式数据驱动网络制图框架，用于以交互式且可扩展的方式可视化与感知高维地理空间（大）数据。为展示该框架的广泛适用性与实用性，我们将其应用于三个真实案例研究，并实现了相应的网络地图应用：iLit4GEE-AI、iWURanking和iTRELISmap。我们期望这三款分别应用于文献大数据分析、世界大学排名及学者地图绘制等不同领域的网络地图，能作为良好开端，激励各领域研究人员与实践者运用idwMapper解决（或至少辅助解决）其具有影响力的实际问题。