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Other literature type . 2018
License: CC BY NC
Data sources: ZENODO
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Project deliverable . 2018
License: CC BY NC
Data sources: Datacite
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e rosa d1 1 bibliometric study results

Authors: Aubin, Sophie; Huber, Madeleine;

e rosa d1 1 bibliometric study results

Abstract

This document presents the identification of scientific networks & key partners, i.e. the researchers specialised in information technologies and computing and linked to agriculture. With this network analysis, we seek to understand how the research institutions in our domain (i.e. agriculture) tackle the data challenge. In particular, this study has allowed to: ● identify key researchers and research institutions that focus on this issue and analyse to what extend they collaborate; ● link these stakeholders to specific topics that relate to the data science issue in agricultural research in order to better interpret the landscape of identified stakeholders. This study is based on the analysis of selected publication records that are simultaneously related to the fields of data and agriculture in the broad sense of those terms. We make no claims on comprehensiveness as the study consists in a first scoping step. Also, we do not aim to qualify excellence through this analysis as we have rather focused on the understanding of “who does what” and the network of collaborations. The analysed publications cover the period of the past decade 2005-2015 at the world scale. This deliverable has been elaborated in the context of the e-ROSA project (Towards an e-infrastructure Roadmap for Open Science in Agriculture) under the overall Task 1.1 “Setting the stage”. The latter aims in particular at mapping key stakeholders, scientific communities, infrastructures and initiatives that can support the elaboration of and benefit from an e-infrastructure roadmap for open science in the field of agriculture. Thus, a main outcome of this deliverable is the understanding of the potential relevance of the used method (i.e. bibliometric analysis) to map the stakeholder community that we seek to engage within the context of the e-ROSA project.

Keywords

open data science; agriculture; e-infrastructure; information technologies

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