{"title":"Emerging trends in big Earth data management and analysis","authors":"M. Sudmanns, G. Giuliani, D. Tiede, H. Augustin","doi":"10.1080/20964471.2023.2237829","DOIUrl":null,"url":null,"abstract":"Big Earth data are increasingly used in a variety of applications. At the same time, technological developments happen rapidly and include Earth observation data cubes, analysis-ready data (ARD), the need to access distributed systems and data to avoid replicating datasets, searching and finding datasets, or visualization of data and information in a comprehensive way. The current pace in which technology and methodology using big Earth data is developed is high, but this should be seen as an opportunity to strive for flexible and innovative solutions. Those solutions and approaches may even come from other domains and disciplines as remote sensing or Earth observation (EO) in general and they should be embraced as a facilitator of the multiand interdisciplinary nature that is inherent to big Earth data science and research. Although worthwhile to envision, it would be a challenging or even impossible task to get a full and comprehensive overview over the state-of-the-art, developments, and current research agendas of all disciplines that are contributing to big Earth data. In this special issue, we aimed to curate contributions that can be seen as a snapshot of “emerging trends” instead of providing a comprehensive overview, which is hardly possible in such a highly dynamic field. Seven papers illustrate the variety of topics, different available solutions, and challenges that lie ahead. The contributions are as varied as the topics and range from technical notes as a state-of-the-art report to very detailed, comprising articles. The contributions can be categorised into four sub-topics: data sources, data management, data analytics, and data visualization. However, the boundaries of these categories cannot be strictly drawn, and investigations of individual solutions provided in the articles can be put into their contexts within a bigger big Earth data workflow. Baraldi et al. (2022a, 2022b) investigate the concept of ARD in two papers (part 1 and part 2), and proposes a new workflow for generating ARD. These papers are technologically dense, but provide concepts and ideas for quality indicators, while also considering data storage and querying. Considering that the quality of subsequent analyses depends largely on the quality of input data, providing high-quality ARD is of interest for the entire community. Backeberg et al. (2022) describe technical solutions for federated big Earth data management and processing. With the objective to overcome limitations of requirements to keep all data within one system, different providers may share responsibilities and technical implementations of concepts within the overall system. For users, such a system is aimed to be transparent and usable without technical barriers. Such federated systems BIG EARTH DATA 2023, VOL. 7, NO. 3, 451–454 https://doi.org/10.1080/20964471.2023.2237829","PeriodicalId":8765,"journal":{"name":"Big Earth Data","volume":"229 1","pages":"451 - 454"},"PeriodicalIF":4.2000,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Big Earth Data","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/20964471.2023.2237829","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Big Earth data are increasingly used in a variety of applications. At the same time, technological developments happen rapidly and include Earth observation data cubes, analysis-ready data (ARD), the need to access distributed systems and data to avoid replicating datasets, searching and finding datasets, or visualization of data and information in a comprehensive way. The current pace in which technology and methodology using big Earth data is developed is high, but this should be seen as an opportunity to strive for flexible and innovative solutions. Those solutions and approaches may even come from other domains and disciplines as remote sensing or Earth observation (EO) in general and they should be embraced as a facilitator of the multiand interdisciplinary nature that is inherent to big Earth data science and research. Although worthwhile to envision, it would be a challenging or even impossible task to get a full and comprehensive overview over the state-of-the-art, developments, and current research agendas of all disciplines that are contributing to big Earth data. In this special issue, we aimed to curate contributions that can be seen as a snapshot of “emerging trends” instead of providing a comprehensive overview, which is hardly possible in such a highly dynamic field. Seven papers illustrate the variety of topics, different available solutions, and challenges that lie ahead. The contributions are as varied as the topics and range from technical notes as a state-of-the-art report to very detailed, comprising articles. The contributions can be categorised into four sub-topics: data sources, data management, data analytics, and data visualization. However, the boundaries of these categories cannot be strictly drawn, and investigations of individual solutions provided in the articles can be put into their contexts within a bigger big Earth data workflow. Baraldi et al. (2022a, 2022b) investigate the concept of ARD in two papers (part 1 and part 2), and proposes a new workflow for generating ARD. These papers are technologically dense, but provide concepts and ideas for quality indicators, while also considering data storage and querying. Considering that the quality of subsequent analyses depends largely on the quality of input data, providing high-quality ARD is of interest for the entire community. Backeberg et al. (2022) describe technical solutions for federated big Earth data management and processing. With the objective to overcome limitations of requirements to keep all data within one system, different providers may share responsibilities and technical implementations of concepts within the overall system. For users, such a system is aimed to be transparent and usable without technical barriers. Such federated systems BIG EARTH DATA 2023, VOL. 7, NO. 3, 451–454 https://doi.org/10.1080/20964471.2023.2237829