NoSQL data model for semi-automatic integration of Ethnomedicinal plant data from multiple sources
Ningthoujam, S.S.; Choudhury, M.D.; Potsangbam, K.S.; Chetia, P.; Nahar, L.; Sarker, S.D.; Basar, N.; Talukdar, A.D. (2014). NoSQL data model for semi-automatic integration of Ethnomedicinal plant data from multiple sources. Phytochemical Analysis 25(6): 495-507. https://dx.doi.org/10.1002/pca.2520
In: Phytochemical Analysis. Wiley-Blackwell: Hoboken. ISSN 0958-0344; e-ISSN 1099-1565, more
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| Author keywords |
MongoDB; NoSQL databases; ethnomedicinal plants |
| Authors | | Top |
- Ningthoujam, S.S.
- Choudhury, M.D.
- Potsangbam, K.S.
- Chetia, P.
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- Nahar, L.
- Sarker, S.D.
- Basar, N.
- Talukdar, A.D.
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| Abstract |
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. |
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