<i>dciWebMapper</i> : A Data‐Driven and Coordinated View‐Enabled Interactive Web Mapping Framework for Visualizing and Sensing High‐Dimensional Geospatial (Big) Data

ABSTRACT We are surrounded by overwhelming big data, which brings substantial advances but meanwhile poses many challenges. A very large portion of big data contains geospatial information and hence geospatial big data, which is crucial for decision making if being utilized strategically. Among others, volumes in size and high dimensions are two 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. More importantly, such interactive web map applications are powerful to intuitively reveal insights from high‐dimensional geospatial big data for actionable decision making. We propose an interactive and data‐driven web mapping framework, named dciWebMapper , 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 dciWebMapper 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 to world university ranking to scholar mapping, will provide a good start and inspire researchers and practitioners in various domains to apply our dciWebMapper to solve and/or aid in solving impactful problems.