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RGi CEO Stephen Gillotte to lead Open Mapping panel at FedGeoDay

Reinventing Geospatial®, Inc. (RGi®) is a proud sponsor of the 2020 FedGeoDay event being held online June 11-12, where RGi CEO Stephen Gillotte will lead an Open Mapping for Program Success panel at 9:45 am on day 1. During the panel, Steve will guide the panelists through a discussion on the benefits and challenges of an open ecosystem approach versus a proprietary or hybrid solution. He’ll also tackle some of the myths of both policy and technology, and offer perspectives on how the audience can get involved in supporting decision making.

To register: fedgeo.us

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RGi and ERDC-GRL present STRIDER at FedGeoDay; helping intel analysts connect the dots

RGi’s Michael Szaszy, along with the US Army Corp of Engineers ERDC-GRL’s Dr. Ray Dos Santos, presented the Spatio-temporal Retrieval and Introspection of Data and Embedded Relationships (STRIDER) system on October 13, 2016 at the FedGeoDay Conference in Washington, DC.

Data processing and visualization is a highly challenging aspect of modern intelligence systems. As data volumes grow, the system must not only maintain a visual appeal, but also implement high selectivity (i.e., display only the least amount of the most relevant information). In this manner, the end user can focus on the task at hand rather than on the sifting of unimportant data. Szaszy and Dos Santos discussed STRIDER, a system that performs document reasoning helpful on various domains. STRIDER features location-enabled text parsing, machine learning techniques, and storylines. Internally, STRIDER performs data ingestion on both structured and unstructured data sources, making it available for many purposes: plotting documents on a map, building associations among spatial entities, and displaying numerical analysis, such as event correlation. In the visual interface, STRIDER uses a variety of multiple coordinated views, including maps, networks, and charts, to support data exploration and hypothesis testing workflows. STRIDER allows the analysis of complex data to be substantially enhanced through automation and mapping, and facilitates inferences on the underlying data points.

For more information on STRIDER, please contact [email protected].