Ramadan New Crescent Moon Visibility Dataset for Machine Learning Prediction

OverviewThis dataset supports the research presented in the article “Predicting New Crescent Moon Visibility Applying Machine Learning Algorithms,” published in Scientific Reports in 2023. The dataset was developed for machine-learning-based prediction of the naked-eye visibility of the new crescent Moon, with particular emphasis on predicting crescent visibility associated with the beginning of the Islamic month of Ramadan. Dataset constructionThe underlying crescent observation information was collected from the International Crescent Observation Project (ICOP). The research team subsequently curated, cleaned, standardized and augmented the observational records with additional astronomical variables and observations. Data relevant to the month of Ramadan were retained for the study, and additional astronomical information was obtained using Accurate Times 5.6 software. The resulting dataset contains 358 observations from 43 countries. VariablesThe dataset includes variables related to date and geographical location, atmospheric conditions and astronomical characteristics, including country, city, state, latitude, longitude, sunset, moonset, Sun-Moon lag, age of the Moon, Moon altitude, Sun altitude, altitude difference, Moon azimuth, Sun azimuth, azimuth difference (DAZ), elongation/ARCL, illumination, and naked-eye crescent visibility (V_eye). Data provenanceThe underlying observational information was derived in part from records provided through the International Crescent Observation Project (ICOP). The deposited dataset represents a curated, processed and augmented research dataset prepared by the authors for the associated study. Associated publicationAl-Rajab, M., Loucif, S., & Al Risheh, Y. (2023). Predicting new crescent moon visibility applying machine learning algorithms. Scientific Reports, 13, 6674. DOI: 10.1038/s41598-023-32807-x. Conditions of useAccess is provided for legitimate academic and research purposes subject to the accompanying Data Use Agreement. Researchers using the dataset should cite the Zenodo dataset record using its DOI and appropriately cite the associated publication. The International Crescent Observation Project (ICOP) should also be acknowledged as a source of the underlying crescent observation information where applicable. Redistribution or public reposting of the restricted dataset without prior authorization is not permitted under the conditions of access. Users granted access to this dataset are required to acknowledge the source of the underlying observational data, cite this dataset using its Zenodo DOI, and appropriately cite the associated publication in scholarly outputs resulting from use of the dataset, subject to the accompanying Data Use Agreement.