Dezesseis agências internacionais de apoio à pesquisa selecionam propostas na Chamada T-AP Digging into Data Challenge 2017

FAPESP e Trans-Atlantic Platform anunciam resultado de chamada
31 de março de 2017

Dezesseis agências internacionais de apoio à pesquisa selecionam propostas na Chamada T-AP Digging into Data Challenge 2017

FAPESP e Trans-Atlantic Platform anunciam resultado de chamada

Dezesseis agências internacionais de apoio à pesquisa selecionam propostas na Chamada T-AP Digging into Data Challenge 2017

31 de março de 2017

Dezesseis agências internacionais de apoio à pesquisa selecionam propostas na Chamada T-AP Digging into Data Challenge 2017

 

Agência FAPESP – A FAPESP divulgou o resultado da chamada de propostas Digging into Data Challenge, lançada em junho de 2016.

O objetivo da chamada foi selecionar projetos que visem investigar como técnicas computacionais avançadas aplicadas a big data podem ajudar a resolver questões de pesquisa em Ciências Humanas e Sociais. A análise de big data em Ciências Humanas e Sociais é uma das características marcantes da área denominada Humanidades Digitais, que vem crescendo em todo o mundo.

Os projetos submetidos foram propostos por equipes multinacionais de 11 países diferentes. De um total de 105 propostas, 14 foram selecionadas, com temas abrangendo um amplo leque de áreas, incluindo Musicologia, Linguística, História, Ciência Política e Economia.

Uma das propostas selecionadas é a da professora Maria Eunice Quilici Gonzalez, da Universidade Estadual Paulista (Unesp), "Compreendendo a dinâmica da opinião e da linguagem utilizando big data”. O projeto visa estudar a dinâmica de ações sociais a partir da análise de big data. A equipe do projeto é formada por pesquisadores em Linguística, Filosofia, Física, Ciência dos Dados (data Science) e Direito, ilustrando a interdisciplinaridade inerente a projetos em Humanidades Digitais. O projeto inclui, ainda, pesquisadores da Argentina e da França.

Por meio da chamada, a FAPESP e 15 agências de apoio à pesquisa de vários países apoiarão, com aproximadamente US$ 9,2 milhões, equipes internacionais que investigam como a pesquisa avançada em computação de larga escala pode responder questões nas áreas de Ciências Humanas e Sociais. Essas equipes estarão dedicadas a pesquisas nas mais diversas áreas, como Musicologia, Economia, Linguística, Ciência Política e História.

Cada uma das 14 equipes selecionadas é composta por pesquisadores de diversas disciplinas, colaborando para demonstrar como técnicas avançadas em análise de big data podem ser utilizadas para investigar uma ampla gama de questões das Ciências Humanas e Sociais.

T-AP Digging into Data Challenge é um programa apoiado por agências de fomento à pesquisa de 11 países, no âmbito da Plataforma Transatlântica para Ciências Humanas e Sociais (TA-P). A Plataforma constitui-se em uma colaboração sem precedentes para a área de humanidades, reunindo financiadores e facilitadores da América do Sul, América do Norte e Europa, visando reforçar a capacidade dos financiadores, organizações de pesquisa e pesquisadores para o diálogo e a cooperação transnacional.

Países e organizações financiadoras incluem: Argentina (MINCyT); Brasil (FAPESP); Canadá (SSHRC, NSERC, FRQ); Finlândia (AKA); França (ANR); Alemanha (DFG); México (CONACYT); Holanda (NWO); Portugal (FCT); Reino Unido (AHRC, ESRC) e Estados Unidos (NEH, NSF, IMLS).

Proposta selecionada no Estado de São Paulo:

Compreendendo a dinâmica da opinião e da linguagem utilizando big data

Pesquisadora Responsável (PI): Maria Eunice Quilici Gonzalez

PI no Exterior: Laura Hernandez

Instituição no exterior: Université de Cergy-Pontoise (ANR)

PI no Exterior: José Ignacio Alvarez Hamelin

Instituição-sede: Universidad de Buenos Aires (MINCyT)

Instituição-sede: Faculdade de Filosofia e Ciências Marília/Unesp

 

As demais propostas selecionadas na chamada:

Intelligent Search Engine for Belief Legends (ISEBEL)

Abstract: A collaboration among an international team of folklore scholars and computer scientists to develop analytical techniques for studying folkloric traditions across multiple national databases.

Funders: Germany (DFG); Netherlands (NWO); United States (NEH).

Principal Investigators: Theo Meder (Meertens Instituut); Christoph Schmitt (University of Rostock); Tim Tangherlini (University of California, Los Angeles).

 

Online Prices for Computing Standards of Living Across Countries (OPSLAC)

Abstract: A collaboration among an international group of economists using online prices, available from the Billion Prices project at MIT, to study standards of living across countries.

Funders: Canada (SSHRC); Netherlands (NWO); United States (NSF).

Principal Investigators: Walter Erwin Diewert (University of British Columbia); Robert Feenstra (University of California, Davis); Robert Inklaar (University of Groningen).

 

Analyzing Child Language Experiences Around the World (ACLEW)

Abstract: An international collaboration among linguists and speech experts to study child language development across nations and cultures to gain a better understanding of how an infant’s environment affects subsequent language ability.

Funders: Argentina (MINCyT); Canada (SSHRC); Finland (AKA); France (ANR); United Kingdom (ESRC/AHRC); United States (NEH).

Principal Investigators: Elika Bergelson (Duke University); Emmanuel Dupoux (École Normale Supérieure); Okko Rasanen (Aalto University); Celia Rosemberg (CONICET); Bjorn Schuller (Imperial College London); Melanie Soderstrom (University of Manitoba).

 

Responsible Terrorism Coverage (ResTeCo): A Global Comparative Analysis of News Coverage about Terrorism from 1945 to present

Abstract: A collaboration among scholars of media studies, communication, and political science to study the history of media coverage of terrorist attacks and to gain a better understanding of how such coverage can be done in a responsible manner that does not provide aid to terrorists.

Funders: Germany (DFG); Netherlands (NWO); United States (NEH).

Principal Investigators: Scott Althaus (University of Illinois); Wouter van Atteveldt (Vrije Universiteit Amsterdam); Hatmut Wessler (University of Mannheim).

 

THEMIS.COG: Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups

Abstract: An interdisciplinary research project on the motivations of self-organized collaborations and determinates of their success, through a large-scale study of the scholarly networks and open source software development projects housed on the GitHub repository. The project team includes scholars from sociology, cognitive science, computer science, and engineering.

Funders: Canada (SSHRC); Germany (DFG); United States (NSF).

Principal Investigators: Jesse Hoey (University of Waterloo); Tobias Schroeder (Potsdam University of Applied Sciences); Kimberly B. Rogers (Dartmouth College).

 

Mapping Manuscript Migrations: digging into data for the history and provenance of pre-modern European manuscripts

Abstract: An international collaboration mapping the movement of pre-modern European manuscripts. The project links disparate datasets from Europe and North America to provide a view of the history and provenance of these manuscripts.

Funders: Finland (AKA); France (ANR); United Kingdom (AHRC/ESRC); United States (IMLS).

Principal Investigators: Toby Burrows (University of Oxford); Eero Hyvönen (Aalto University); Lynn Ransom (University of Pennsylvania); Hanno Wijsman (Institut de recherche et d’histoire des textes).

 

Digging into Early Colonial México

Abstract: An innovative international collaboration to study Relaciones Geográficas, a 16th century compilation ordered by the Spanish crown that gathered vast amounts of information about the New World through multiple records, both in Spanish and indigenous languages. Using a Big-Data approach, this project applies novel computational methodologies to study this important source for the colonial history of America.

Funders: México (CONACYT); Portugal (FCT); United Kingdom (AHRC/ESRC). Principal Investigators: Diego Jiménez-Badillo (Museo del Templo Mayor, INAH); Bruno Emanuel da Graça Martins (Universidade de Lisboa); Patricia Murrieta-Flores (University of Chester).

 

SPeech Across Dialects of English (SPADE): large-scale digital analysis of a spoken language across space and time

Abstract: A research collaboration to develop and apply user-friendly software for large-scale speech analysis of 43 existing public and private speech datasets and to understand how English speech has changed over time and space. These diverse datasets are comprised of both Old World (British Isles) and New World (North American) English across an effective time span of over 100 years.

Funders: Canada (SSHRC/NSERC); United Kingdom (AHRC/ESRC); United States (NSF).

Principal Investigators: Jeffrey Mielke (North Carolina State University); Morgan Sonderegger (McGill University); Jane Stuart-Smith (University of Glasgow).

 

Digging into High Frequency Data: Present and Future Risks and Opportunities

Abstract: A project bringing together scholars from economics, business, and computer science to study the emergence of computerized high-frequency trading and its impact on global equity markets.

Funders: Finland (AKA); France (ANR); Germany (DFG); United Kingdom (AHRC/ESRC); United States (NSF).

Principal Investigators: Patrice Fontaine (EUROFIDAI); Loriana Pelizzon (Goethe University Frankfurt); Peter Sebastian Johan Sarlin (Hanken School of Economics); Mila Getmansky Sherman (University of Massachusetts, Amherst); Jean-Pierre Zigrand (London School of Economics and Political Science).

 

Digging into the Knowledge Graph

Abstract: An international collaboration of library and information scientists studying how Linked Open Data, a technique for publishing online data, can improve storage methods for humanities and social science data. Projects in musicology and economics will serve as use cases for this research.

Funders: Canada (SSHRC); Netherlands (NWO); United States (IMLS).

Principal Investigators : Andrea Scharnhorst (Data Archiving and Networked Services); Richard Smiraglia (University of Wisconsin-Milwaukee); Rick Szostak (University of Alberta).

 

Understanding opinion and language dynamics using massive data

Abstract: An international collaboration to explore the dynamics of social actions based on traces left by social media. Focusing on opinion diffusion and language evolution, this project brings together an interdisciplinary team with expertise in data science, physics, linguistics, philosophy and law.

Funders: Argentina (MINCyT); Brazil (FAPESP); France (ANR).

Principal Investigators: Maria Eunice Quilici Gonzalez (Universidade Estadual Paulista); José Ignacio Alvarez Hamelin (Universidad de Buenos Aires); Laura Hernandez (Université de Cergy-Pontoise).

 

Dig that lick: Analysing large-scale data for melodic patterns in jazz performances

Abstract: The study of influence and sharing among musicians through a computational analysis of jazz recordings and related resources.

Funders: France (ANR); Germany (DFG); United Kingdom (ESRC/AHRC); United States (NEH).

Principal Investigators: Simon Dixon (Queen Mary University of London); Hélène Papadopoulos (National Center for Scientific Research); Martin Pfleiderer (University of Music Franz Liszt Weimar); Gabriel Solis (University of Illinois).

 

Oceanic Exchanges: Tracing Global Information Networks in Historical Newspaper Repositories, 1840-1914 (OcEx)

Abstract: A collaborative research project that unites leading efforts in computational periodicals research to examine patterns of information flow across national and linguistic boundaries. The project draws upon large data collections of digitized 19th century newspapers to study the global culture of abundant, rapidly circulating information.

Funders: Finland (AKA); Germany (DFG); México (CONACYT); Netherlands (NWO); United Kingdom (AHRC/ESRC); United States (IMLS).

Principal Investigators: Ryan Cordell (Northeastern University); Mark Priewe (Universitaet Stuttgart); Isabela Galina Russell (Universidad Nacional Autónoma de México); Hannu Salmi (University of Turku); Ulrich Tiedau (University College of London); Jaap Verheul (University of Utrecht).

 

Machine Translation and Automated Analysis of Cuneiform Languages (MTAAC)

Abstract: A collaboration among ancient studies scholars, linguists, and computer scientists to develop computational techniques for translating ancient administrative records stored on cuneiform tablets.

Funders: Canada (SSHRC); Germany (DFG); United States (NEH).

Principal Investigators: Heather D. Baker (University of Toronto); Christian Chiarcos (University of Frankfurt); Robert K. Englund (University of California, Los Angeles).

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