NoSQL Data Model for Semi‐automatic Integration of Ethnomedicinal Plant Data from Multiple Sources

INTRODUCTION: Sharing traditional knowledge with the scientific community could refine scientific approaches to phytochemical investigation and conservation of ethnomedicinal plants. As such, integration of traditional knowledge with scientific data using a single platform for sharing is greatly nee...

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Vydané v:Phytochemical analysis Ročník 25; číslo 6; s. 495 - 507
Hlavní autori: Ningthoujam, Sanjoy Singh, Choudhury, Manabendra Dutta, Potsangbam, Kumar Singh, Chetia, Pankaj, Nahar, Lutfun, Sarker, Satyajit D, Basar, Norazah, Talukdar, Anupam Das
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: England Wiley 01.11.2014
Blackwell Publishing Ltd
Wiley Subscription Services, Inc
Predmet:
Bioassays
Data Interpretation, Statistical
Database Management Systems
Databases, Factual
ethnomedicinal plants
indigenous knowledge
Information Storage and Retrieval
Integrated Advanced Information Management Systems
Medicine, Traditional
Models, Statistical
MongoDB
NoSQL databases
Phytochemicals
Plants, Medicinal
Storage
surveys
NoSQL databases
ethnomedicinal plants
MongoDB
ISSN:0958-0344, 1099-1565, 1099-1565
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Shrnutí:INTRODUCTION: Sharing traditional knowledge with the scientific community could refine scientific approaches to phytochemical investigation and conservation of ethnomedicinal plants. As such, integration of traditional knowledge with scientific data using a single platform for sharing is greatly needed. However, ethnomedicinal data are available in heterogeneous formats, which depend on cultural aspects, survey methodology and focus of the study. Phytochemical and bioassay data are also available from many open sources in various standards and customised formats. OBJECTIVE: To design a flexible data model that could integrate both primary and curated ethnomedicinal plant data from multiple sources. MATERIALS AND METHODS: The current model is based on MongoDB, one of the Not only Structured Query Language (NoSQL) databases. Although it does not contain schema, modifications were made so that the model could incorporate both standard and customised ethnomedicinal plant data format from different sources. RESULTS: The model presented can integrate both primary and secondary data related to ethnomedicinal plants. Accommodation of disparate data was accomplished by a feature of this database that supported a different set of fields for each document. It also allowed storage of similar data having different properties. CONCLUSION: The model presented is scalable to a highly complex level with continuing maturation of the database, and is applicable for storing, retrieving and sharing ethnomedicinal plant data. It can also serve as a flexible alternative to a relational and normalised database. Copyright © 2014 John Wiley & Sons, Ltd.
Bibliografia:http://dx.doi.org/10.1002/pca.2520
ArticleID:PCA2520
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SourceType-Scholarly Journals-1
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ISSN:0958-0344
1099-1565
1099-1565
DOI:10.1002/pca.2520