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Satellite Earth observation (EO) data have already exceeded the petabyte scale and are increasingly freely and openly available from different data providers. This poses a number of issues in terms of volume (e.g., data volumes have increased 10× in the last 5 years); velocity (e.g., Sentinel-2 is capturing a new image of any given place every 5 days); and variety (e.g., different types of sensors, spatial/spectral resolutions). Traditional approaches to the acquisition, management, distribution, and analysis of EO data have limitations (e.g., data size, heterogeneity, and complexity) that impede their true information potential to be realized. Addressing these big data challenges requires a change of paradigm and a move away from local processing and data distribution methods to lower the barriers caused by data size and related complications in data management. To tackle these issues, EO data cubes (EODC) are a new paradigm revolutionizing the way users can store, organize, manage, and analyze EO data. This Special Issue is consequently aiming to cover the most recent advances in EODC developments and implementations to broaden the use of EO data to larger communities of users, support decision-makers with timely and actionable information converted into meaningful geophysical variables, and ultimately unlock the information power of EO data.

Data curation.

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Satellite Earth observation (EO) data have already exceeded the petabyte scale and are increasingly freely and openly available from different data providers. This poses a number of issues in terms of volume (e.g., data volumes have increased 10× in the last 5 years); velocity (e.g., Sentinel-2 is capturing a new image of any given place every 5 days); and variety (e.g., different types of sensors, spatial/spectral resolutions). Traditional approaches to the acquisition, management, distribution, and analysis of EO data have limitations (e.g., data size, heterogeneity, and complexity) that impede their true information potential to be realized. Addressing these big data challenges requires a change of paradigm and a move away from local processing and data distribution methods to lower the barriers caused by data size and related complications in data management. To tackle these issues, EO data cubes (EODC) are a new paradigm revolutionizing the way users can store, organize, manage, and analyze EO data. This Special Issue is consequently aiming to cover the most recent advances in EODC developments and implementations to broaden the use of EO data to larger communities of users, support decision-makers with timely and actionable information converted into meaningful geophysical variables, and ultimately unlock the information power of EO data.

Data curation.

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Good content is everywhere. In our digital world we are content rich, but quality poor. Good content surrounds us, but it begs to be collected, transformed, and shared. And who better to distill and dismantle it for the benefit of learning communities than today’s learning and development professional? Curation isn’t novel in itself, and there’s much to learn from the successes of others. News sites commonly curate stories adding their own analysis. Retailers and marketers crowdsource ideas from consumers. Businesses build curation strategies to leverage product reviews. Ready, Set, Curate shows you how to elevate the most important content from an endless sea of learning information and offers strategies to better connect with your audience. Using case studies and relevant examples, eight curation experts share tips and best practices for creating a curation strategy and collecting content that is relevant to your learning communities.

Data curation. --- Data curation services --- Data services (Data curation) --- Digital curation --- Services, Data curation --- Curatorship --- Electronic data processing

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Fiona Courage and Jessica Scantlebury describe their work with the Mass Observation Archive. They send out directives and collect the observations of ordinary people, as well as preserving and cataloging materials. They also explain how best to start a career in archives.

Data centers. --- Data curation. --- Mass Observation Archive.

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"Producers of official statistics face a complicated task in managing users' access to the data they collect, as they must maintain the confidentiality of the individuals or businesses who have provided their data to them, while being under pressure to release ever more detailed datasets in order to provide greater analytical insight to those who wish to use such data. Traditionally, national statistical offices have provided trusted users (such as academics) access to some micro-level data at the level of individuals or businesses, while publishing aggregate statistical tables to other users. This approach is not a perfect solution to managing access to data, as many users will not obtain the amount of detail they are seeking, while vetting and managing trusted users is time consuming, and does not guarantee that they will never misuse or lose the data they access. However, there is another way of providing users with analytical insight, by providing them with Synthetic Data, which may be advantageous for certain use case scenarios. Synthetic data can be simulated in such a way as to have many of the same properties as the original dataset, and to allow derivation of the same results and insights, but with a much lower risk of revealing information about individuals to which that data relate. If you are involved in managing users' access to official statistics, and would like to have another option for dealing with your data access dilemmas, this guide will give you what you need to get started."--

Confidential communications --- Data curation. --- Data protection. --- Data privacy. --- Statistical services.