The ARchaeological Organic residues Literature Database (AROLD): Construction of a tool for reviewing and querying published lipid data in organic residue analysis - HAL Accéder directement au contenu
Article dans une revue Archaeometry Année : 2023

The ARchaeological Organic residues Literature Database (AROLD): Construction of a tool for reviewing and querying published lipid data in organic residue analysis

Résumé

Abstract The first attempts to identify amorphous organic substances in archaeology date to the end of the 19th century and the beginning of the 20th century. The 1960s saw the development of infrared spectrometry, and then separative and mass spectrometry analyses were implemented in the 1980s. But it is only since the 1990s that extended and systematic research programmes were devoted to these substances. The number of publications has not stopped growing and is becoming exponential. To get an overview of the lipid studies in archaeology, we conceived the ARchaeological Organic residues Literature Database (AROLD) as a first structured and collaborative research tool. This paper describes the challenges of setting up such a database, details its architecture, presents the choices involved in its implementation, and discusses the possibilities of sharing and evolving this tool.
Fichier principal
Vignette du fichier
2023_Prevost_etal_AROLD.pdf ( 8.01 Mo ) Télécharger
Origine : Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

halshs-04250411, version 1 (03-11-2023)

Identifiants

Citer

Camielsa Prévost, Léa Drieu, Antoine Pasqualini, Martine Regert. The ARchaeological Organic residues Literature Database (AROLD): Construction of a tool for reviewing and querying published lipid data in organic residue analysis. Archaeometry, 2023, 65 (5), pp.1125-1143. ⟨10.1111/arcm.12869⟩. ⟨halshs-04250411⟩
44 Consultations
8 Téléchargements
Dernière date de mise à jour le 28/04/2024
comment ces indicateurs sont-ils produits

Altmetric

Partager

Gmail Facebook Twitter LinkedIn Plus