World Spatiotemporal Analytics and Mapping Project (Wstamp): Discovering, Exploring, and Mapping Spatiotemporal Patterns Across the World’s Largest Open Soruce Data Sets

Abstract

ABSTRACT:The application of spatiotemporal (ST) analytics to integrated data from major sources such as the World Bank, United Nations, and dozens of others holds tremendous potential for shedding new light on the evolution of cultural, health, economic, and geopolitical landscapes on a global level. Realizing this potential first requires an ST data model that addresses challenges in properly merging data from multiple authors, with evolving ontological perspectives, semantical differences, and changing attributes, as well as content that is textual, numeric, categorical, and hierarchical. Equally challenging is the development of analytical and visualization approaches that provide a serious exploration of this integrated data while remaining accessible to practitioners with varied backgrounds. The WSTAMP project at Oak Ridge National Laboratory has yielded two major results in addressing these challenges: 1) development of the WSTAMP database, a significant advance in ST data modeling that integrates 10,000+ attributes covering over 200 nation states spanning over 50 years from over 30 major sources and 2) a novel online ST exploratory and analysis tool providing an array of modern statistical and visualization techniques for analyzing these data temporally, spatially, and spatiotemporally under a standard analytic workflow. We discuss the status of this work and report on major findings.

Spatio-Temporal Data Model for Integrating Evolving Nation-Level Datasets

“…In W-STAMP our framework is used as a foundation for the analytical system database to track updates in the incoming information, clean the data of erroneous records, and reconcile data sources (Stewart et al, 2015). The users can view country histories and event lists for select regions and time periods.…”

“…Proposed framework has been implemented in a practical datamining system called W-STAMP (World Spatiotemporal Analytics and Mapping Project). Currently W-STAMP contains 15,000+ attributes sourced from more than a dozen public global datasets (Stewart et al, 2015). These data consist of close to 18 million records that characterize more than 250 world entities over approximately 50 year period.…”

A survey of analytical methods for inclusion in a new energy-water nexus knowledge discovery framework

“…For example, two methods for examining the co-evolution of trends in water and energy use over time are those known as Dynamic Time Warping (DTW) and Find Signature Trends (Stewart et al, 2015). These techniques examine similarities among temporal patterns by developing a non-linear warped dimension from which similarities, or distances, are measured.…”

The World Spatiotemporal Analytics and Mapping Project (WSTAMP): Further Progress in Discovering, Exploring, and Mapping Spatiotemporal Patterns Across the World’s Largest Open Source Data Sets

“…In our introductory paper (Stewart et al, 2015) we present two primary challenges in developing a spatiotemporal capability that is tightly connected to long-horizon geographic histories. Briefly reviewing that work, we divide this challenge into two separate but interconnected endeavors: 1) how do we settle on, store, and represent the collection of geographic entities (e.g.…”