Skip to main navigation Skip to search Skip to main content

OMGMO: Original Multi-modal Dataset of Genetically Modified Organisms in African Agriculture

  • Daniel Grzenda
  • , Trevor Spreadbury
  • , Joeva Rock
  • , Brian Dowd-Uribe
  • , David Uminsky
  • The University of Chicago
  • University of San Francisco
  • Montpellier Advanced Knowledge Institute on Transitions

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Genetically modified (GM) crops can be a tool to address food security, climate change, and environmental sustainability in Africa. However, despite nearly three decades of developing GM crops for explicit use on the African continent, very little is known about this research, and very few crop varieties have moved from development to use by farmers. This paper introduces a collection of three multi-modal datasets to provide insight into the social, political, and economic actors shaping the future of GM crop development in Africa. Our interdisciplinary team compiled a dataset of GM crops in the research development pipeline, a collection of financial disclosures of funders supporting GM crop research, and a collection of over 2 million articles on agriculture and GM crop reporting from African media. We demonstrate the effectiveness of combining these pertinent datasets to aid in social science analysis of the social, political, and economic landscape of agricultural biotechnology in Africa.

Original languageEnglish
Title of host publicationSocial Informatics - 13th International Conference, SocInfo 2022, Proceedings
EditorsFrank Hopfgartner, Kokil Jaidka, Philipp Mayr, Joemon Jose, Jan Breitsohl
PublisherSpringer Science and Business Media Deutschland GmbH
Pages414-425
Number of pages12
ISBN (Print)9783031190964
DOIs
StatePublished - 2022
Event13th International Conference on Social Informatics, SocInfo 2022 - Glasgow, United Kingdom
Duration: Oct 19 2022Oct 21 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13618 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th International Conference on Social Informatics, SocInfo 2022
Country/TerritoryUnited Kingdom
CityGlasgow
Period10/19/2210/21/22

Keywords

  • Africa
  • Agriculture
  • Data science
  • Genetically modified crops
  • Genetically modified organisms
  • International development
  • Multi-modal data

Fingerprint

Dive into the research topics of 'OMGMO: Original Multi-modal Dataset of Genetically Modified Organisms in African Agriculture'. Together they form a unique fingerprint.

Cite this