{"title":"整合能源数据集:MDIO格式","authors":"Altay Sansal, Ben Lasscock, Alejandro Valenciano","doi":"10.3997/1365-2397.fb2023084","DOIUrl":null,"url":null,"abstract":"MDIO offers a technical solution for storing and retrieving energy data in the cloud and on-premises. As an open-source framework, it incorporates high-resolution, multi-dimensional arrays that accurately represent wind resources and seismic data for multiple applications. By utilising the Zarr format, MDIO ensures efficient chunked storage and parallel I/O operations, facilitating easy data interaction in diverse infrastructures. This paper covers MDIO’s application in renewable energy (wind simulations), predictive analytics, and seismic imaging and interpretation, aiming to provide a robust technical platform for researchers navigating the evolving energy landscape.","PeriodicalId":35692,"journal":{"name":"First Break","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrating Energy Datasets: the MDIO Format\",\"authors\":\"Altay Sansal, Ben Lasscock, Alejandro Valenciano\",\"doi\":\"10.3997/1365-2397.fb2023084\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"MDIO offers a technical solution for storing and retrieving energy data in the cloud and on-premises. As an open-source framework, it incorporates high-resolution, multi-dimensional arrays that accurately represent wind resources and seismic data for multiple applications. By utilising the Zarr format, MDIO ensures efficient chunked storage and parallel I/O operations, facilitating easy data interaction in diverse infrastructures. This paper covers MDIO’s application in renewable energy (wind simulations), predictive analytics, and seismic imaging and interpretation, aiming to provide a robust technical platform for researchers navigating the evolving energy landscape.\",\"PeriodicalId\":35692,\"journal\":{\"name\":\"First Break\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"First Break\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3997/1365-2397.fb2023084\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Earth and Planetary Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"First Break","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3997/1365-2397.fb2023084","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
MDIO offers a technical solution for storing and retrieving energy data in the cloud and on-premises. As an open-source framework, it incorporates high-resolution, multi-dimensional arrays that accurately represent wind resources and seismic data for multiple applications. By utilising the Zarr format, MDIO ensures efficient chunked storage and parallel I/O operations, facilitating easy data interaction in diverse infrastructures. This paper covers MDIO’s application in renewable energy (wind simulations), predictive analytics, and seismic imaging and interpretation, aiming to provide a robust technical platform for researchers navigating the evolving energy landscape.
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