TY - GEN
T1 - Unveiling Knowledge Organization Systems’ Artifacts for Digital Agriculture with Lexical Network Analysis
AU - Miranda Soares, Filipi
AU - Bergier, Ivan
AU - Coradini, Maria Carolina
AU - Lüdtke Ferreira, Ana Paula
AU - Ambrosio Telles, Milena
AU - Moreira dos Santos Maculan, Benildes Coura
AU - Alencar, Maria de Cléofas Faggion
AU - Marques Simão, Victor Paulo
AU - Teixeira de Almeida, Bibiana
AU - Pignatari Drucker, Debora
AU - dos Santos Machado Vieira, Marcia
AU - Serra da Cruz , Sérgio Manuel
N1 - Funding Information:
This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-Brasil (CAPES)-Finance Code 001. FMS would like to thank São Paulo Research Foundation (FAPESP) for the research grants (process numbers 21/15125-0 and 22/08385-8). SMSC would like to thank Brazilian National Council for Scientific and Technological Development (CNPq) for the research grants (process numbers 400044/2023-4 and 306115/2021-2 ). MSMV thanks CNPq and FAPERJ (Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro/Carlos Chagas Filho Foundation for Research Support in the State of Rio de Janeiro) for the research support (409043/2021-4, 312423/2022-5, E-26/201.209/2022 (273339)).
Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023/10/26
Y1 - 2023/10/26
N2 - This article presents a bibliometric and terminological study of a corpus composed of abstracts and titles of 278 articles retrieved by a review protocol planned for surveying initiatives on building artifacts for modeling knowledge related to agricultural production systems. The original corpus comprised a 53,379-word linguistic extract filtered to 111 interconnected major terminologies by combining AntConc and VOSViewer tools. The reduced data were imported into the Gephi tool for analysis of lexical network graphs. Emergent clusters and their central terms underscore the thematic areas that prominently shape the landscape of agricultural Knowledge Organization Systems (KOS) and highlight the interplay between technological advancements, semantic enrichment, and domain-specific challenges. Our analysis of term occurrences and clusters contributes to a broader understanding of these concepts, inferring their significance, roles, and interconnections within the agricultural landscape. It also sheds light on the roles played by KOS in Digital Agriculture.
AB - This article presents a bibliometric and terminological study of a corpus composed of abstracts and titles of 278 articles retrieved by a review protocol planned for surveying initiatives on building artifacts for modeling knowledge related to agricultural production systems. The original corpus comprised a 53,379-word linguistic extract filtered to 111 interconnected major terminologies by combining AntConc and VOSViewer tools. The reduced data were imported into the Gephi tool for analysis of lexical network graphs. Emergent clusters and their central terms underscore the thematic areas that prominently shape the landscape of agricultural Knowledge Organization Systems (KOS) and highlight the interplay between technological advancements, semantic enrichment, and domain-specific challenges. Our analysis of term occurrences and clusters contributes to a broader understanding of these concepts, inferring their significance, roles, and interconnections within the agricultural landscape. It also sheds light on the roles played by KOS in Digital Agriculture.
KW - Corpus Linguistics
KW - KOS
KW - Semantic artifacts
KW - Ontologies
KW - Thesaurus
KW - Metadata
KW - Knowledge graph
KW - n/a OA procedure
U2 - 10.1007/978-3-031-47112-4_28
DO - 10.1007/978-3-031-47112-4_28
M3 - Conference contribution
SN - 978-3-031-47111-7
T3 - Lecture Notes in Computer Science
SP - 299
EP - 311
BT - Advances in Conceptual Modeling
A2 - Sales, Tiago Prince
A2 - Guizzardi, Giancarlo
A2 - Araújo, João
A2 - Borbinha, José
PB - Springer
CY - Cham
ER -