Globalxplorer

Overview

Globalxplorer is a U.S. nonprofit organization categorized under Arts, Culture and Humanities, with a focus on Historical Societies and related activities. It is registered as a 501(c)(3) organization, allowing donations to be tax-deductible[3].

Mission and Activities

Globalxplorer aims to protect and preserve the world's cultural heritage through innovative technologies. It does this by engaging citizens worldwide in archaeological discovery using satellite imagery. The platform, developed by Dr. Sarah Parcak, involves users in identifying potential archaeological sites through a gamified process[1][2].

History

The organization was founded as a result of Dr. Sarah Parcak winning the 2016 TED Prize. The prize included a $1 million grant, which she used to create Globalxplorer. The platform officially launched on February 16, 2017[1]. Initially, it focused on Peru, partnering with the Sustainable Preservation Initiative (SPI) for on-ground activities[1].

Approach to Archaeology

Globalxplorer utilizes a citizen science approach, where users are trained through tutorials to identify archaeological features in satellite images. Users review "tiles" from these images, answering yes/no questions about potential sites. A consensus among multiple users triggers further investigation by professional archaeologists[2]. This method helps in rapid identification of sites and aids in preventing looting by staying ahead of potential thieves[2].

Financials and Structure

In its early years, Globalxplorer's revenue primarily came from contributions. For example, in the fiscal year ending December 2019, it received $452,519 in contributions, with no income from program services or other sources[3]. The organization is based in Birmingham, AL, and employs a small team[2].

Impact

Globalxplorer has garnered significant participation, with thousands of users contributing to the discovery of potential archaeological sites. The platform's approach has been successful, with users achieving an 80-85% success rate in identifying features in satellite images[2].