Trans-Atlantic Platform Announces the 14 Winners of Round Four of the International Competition
March 29, 2017 — The Trans-Atlantic Platform for the Social Sciences and Humanities along with sixteen international research funders today jointly awarded approximately (US) $9.2 million to international teams investigating how large-scale computational techniques may be applied to answering research questions in the humanities and social sciences. These teams will be pursuing research in numerous areas, including musicology, economics, linguistics, political science, and history.
Each of the fourteen winning teams is composed of researchers from multiple scholarly and scientific disciplines, working collaboratively to demonstrate how cutting-edge big data techniques can be used to investigate a wide range of research questions across the humanities and social sciences. Since its inception in 2009, the Digging into Data Challenge program has helped to spark exciting new research avenues for the humanities and social sciences utilizing computational techniques.
The T-AP Digging into Data Challenge is sponsored by research funding organizations from eleven nations, organized under the auspices of the Trans-Atlantic Platform for the Social Sciences and Humanities. T-AP is an unprecedented collaboration between key humanities and social science funders and facilitators from South America, North America and Europe, and aims to enhance the ability of funders, research organizations and researchers to engage in transnational dialogue and collaboration. T-AP Digging is the Platform’s first funding program and will lay the groundwork for future collaborative activities.
Participating nations and funding organizations include: Argentina (MINCyT); Brazil (FAPESP); Canada (SSHRC, NSERC, FRQ); Finland (AKA); France (ANR); Germany (DFG); Mexico (CONACYT); Netherlands (NWO); Portugal (FCT); United Kingdom (AHRC, ESRC), and United States (NEH, NSF, IMLS).
The full list of projects may be found on the Round Four page of the Digging into Data website.