@incollection{fdi:010083662,
  title = {{A}gro{LD} : a knowledge graph for the plant sciences},
  author = {{L}armande, {P}ierre and {T}odorov, {K}.},
  editor = {},
  language = {{ENG}},
  abstract = {{R}ecent advances in sequencing technologies and high-throughput phenotyping have revolutionized the analysis in the field of the plant sciences. {H}owever, there is an urgent need to effectively integrate and assimilate complementary information to understand the biological system in its entirety. {W}e have developed {A}gro{LD}, a knowledge graph that exploits {S}emantic {W}eb technologies to integrate information on plant species and in this way facilitate the formulation and validation of new scientific hypotheses. {A}gro{LD} contains around 900{M} triples created by annotating and integrating more than 100 datasets coming from 15 data sources. {O}ur objective is to offer a domain specific knowledge platform to answer complex biological and plant sciences questions related to the implication of genes in, for instance, plant disease resistance or adaptative responses to climate change. {I}n this paper, we present results of the project, which focused on genomics, proteomics and phenomics. {W}e present the {A}gro{LD} pipeline for lifting the data, the open source tools developed for these purposes, as well as the web application allowing to explore the data.},
  keywords = {},
  booktitle = {{T}he semantic web - {ISWC} 2021},
  volume = {12922},
  numero = {},
  pages = {496--510},
  address = {{C}ham},
  publisher = {{S}pringer},
  series = {{L}ecture {N}otes in {C}omputer {S}cience},
  year = {2021},
  DOI = {10.1007/978-3-030-88361-4_29},
  ISBN = {978-3-030-88360-7},
  URL = {https://www.documentation.ird.fr/hor/fdi:010083662},
}