  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.
