{"title":"A dataset of sandfly (Phlebotomus papatasi, Phlebotomus alexandri, and Phlebotomus sergenti) genital and pharyngeal images","authors":"Mohammad Fraiwan , Rami Mukbel , Dania Kanaan","doi":"10.1016/j.dib.2024.111031","DOIUrl":null,"url":null,"abstract":"<div><div>Sandflies serve as carriers for numerous tropical diseases, including leishmaniasis, bartonellosis, and sandfly fever. Furthermore, sandflies are species-specific when it comes to transmitting corresponding pathogen species. Hence, accurate classification and identification of sandfly species and gender are essential for various purposes such as disease monitoring and control, population management, research and development, and epidemiological investigations. Most of the sexing and taxonomy keys are based on internal morphological features, which may lead to errors due to some features being missed by the naked eye. In this paper, we describe the process we used to collect and prepare samples of three sandfly species (<em>Ph. alexandri, Ph. papatasi</em>, and <em>Ph. sergenti</em>). The dataset described in this article contains two images per sample, representing the pharynx in the head and the genitalia in the abdomen. The dataset is organized into male and female categories for each of the three species. The sex and species were determined manually by two specialists. This dataset can be used to develop automated methods for sex identification and taxonomy. Additionally, it can be used to train students in speciation and taxonomy. To the best of our knowledge, this is the first publicly available dataset of images of this kind.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"57 ","pages":"Article 111031"},"PeriodicalIF":1.0000,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data in Brief","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352340924009934","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Sandflies serve as carriers for numerous tropical diseases, including leishmaniasis, bartonellosis, and sandfly fever. Furthermore, sandflies are species-specific when it comes to transmitting corresponding pathogen species. Hence, accurate classification and identification of sandfly species and gender are essential for various purposes such as disease monitoring and control, population management, research and development, and epidemiological investigations. Most of the sexing and taxonomy keys are based on internal morphological features, which may lead to errors due to some features being missed by the naked eye. In this paper, we describe the process we used to collect and prepare samples of three sandfly species (Ph. alexandri, Ph. papatasi, and Ph. sergenti). The dataset described in this article contains two images per sample, representing the pharynx in the head and the genitalia in the abdomen. The dataset is organized into male and female categories for each of the three species. The sex and species were determined manually by two specialists. This dataset can be used to develop automated methods for sex identification and taxonomy. Additionally, it can be used to train students in speciation and taxonomy. To the best of our knowledge, this is the first publicly available dataset of images of this kind.
期刊介绍:
Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.