| Literature DB >> 27900356 |
Inayat Ur Rahman1, Farhana Ijaz1, Aftab Afzal1, Zafar Iqbal1, Niaz Ali1, Muhammad Azhar Khan1, Muhammad Afzal1, Said Muhammad1, Ghulam Qadir1, Muhammad Asif1.
Abstract
The graphical dataset in this paper is related to the research article entitled "A novel survey of the ethno medicinal knowledge of dental problems in Manoor Valley (Northern Himalaya), Pakistan" (I.U. Rahman, F. Ijaz, Z. Iqbal, A. Afzal, N. Ali, M. Afzal, M.A. Khan, S. Muhammad, G. Qadir, M. Asif, 2016) [1]. This article describes how the local community of Manoor Valley practices cultural / traditional knowledge for dental problems. For the recorded data of 25 medicinal plants, six quantitative ethnomedicinal statistical approaches / equations were used. Out of these indices, four were used to measure the most imported and cited medicinal plant species while two for the comparative analysis to evaluate the novelty of work.Keywords: Dental issues; Graphical dataset; Manoor Valley Pakistan; Quantitative ethnobotany
Year: 2016 PMID: 27900356 PMCID: PMC5123063 DOI: 10.1016/j.dib.2016.11.025
Source DB: PubMed Journal: Data Brief ISSN: 2352-3409
Fig. 1Number of informants interviewed during field work.
Fig. 3Life form of plants used for ethno medicinal practices.
Fig. 4Phyto parts used as traditional medicines for dental problems.
Fig. 5Use value and Relative frequency citations of medicinal plants cited by the informants for various dental problems.
Fig. 6No. of informants cited plant species used for various dental problems.
Fig. 7Fidelity Level (%) and Consensus index (%) of medicinal plants cited by the informants for various diseases.
Fig. 8Comparative analysis of the present work [1] with previous studies at regional, national and global level through Jaccard similarity index.
Fig. 9Comparative analysis of the present work [1] with previous studies at regional, national and global level through Sorensen similarity index.
Fig. 2Quantitative ethnomedicinal/statistical indices used to evaluate most cited medicinal plants (UVi, RFCs, CI and FL) and comparative analysis (JI and QS).
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