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Data harvesting: what is it, and how can you benefit?
https://blogs.worldbank.org/opendata/data-harvesting-what-it-and-how-can-you-benefitWhat is data harvesting? Data harvesting is a process that copies datasets and their metadata between two or more data catalogs—a critical step in making data useful. It’s similar to the techniques that search engines use to look for, catalog, and index content from different websites to make it searchable in a single location.
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How-to guide for data.worldbank.org
https://blogs.worldbank.org/opendata/how-guide-dataworldbankorgdata.worldbank.org opens World Bank databases to all users and includes World Development Indicators (WDI) -- one of the world’s most reliable and comprehensive databases on developing economies--, Doing Business, and many others.
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Accessing World Bank Open Data in Stata
https://blogs.worldbank.org/opendata/accessing-world-bank-open-data-stata1 Stata is a statistical computing package widely used in the business and academic worlds. We use it at the World Bank and it’s great to see a new version of the wbopendata module that gives Stata users direct access to much of the data on data.worldbank.org.
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Electronic versus paper-based data collection: reviewing the debate
https://blogs.worldbank.org/impactevaluations/electronic-versus-paper-based-data-collection-reviewing-debateelectronic data collection. These are based on some of the things we have found to be most useful in various surveys carried out as part of DIME impact evaluations. 1. Avoid mistakes before they happen. Did you hear the one about the 6-year-old with two children who was also his own grandmother?
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The Top 5 Ways to Access World Bank Data
https://blogs.worldbank.org/opendata/the-top-5-ways-to-access-world-bank-dataEnglish 5 So. You're looking for the World Bank's data. Here are the top 5 ways I access it, what are yours? 1) data.worldbank.org Our most popular open data destination - the main World Bank Data site gives you an overview of the data we have on a country, region or topic.
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Five tools for capturing, manipulating, and visualizing data
https://blogs.worldbank.org/governance/five-tools-capturing-manipulating-and-visualizing-dataOpenRefine: Explores, cleans, and reformats data. The tool transforms your database’s cells in bulk to spot errors, edit data, and specify patterns. DataWrapper – Visualizes data.
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Introducing WBGAPI: A new python package for accessing World Bank data
https://blogs.worldbank.org/opendata/introducing-wbgapi-new-python-package-accessing-world-bank-dataVersion 1.0.4 of the wbgapi python package is now available. This package has been in the Python Package Index for almost a year, and the latest version adds several new features to make exploring and searching databases easier and more interactive.
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Leveraging big data and machine learning in credit reporting
https://blogs.worldbank.org/developmenttalk/leveraging-big-data-and-machine-learning-credit-reportingSource: Doing Business database. In this digital era, new data and technology are shaping the credit reporting sector. Big data and machine learning, for example, allow for faster, more sophisticated, and more cost-effective data mining and processing while lowering the risks associated with human interventions.
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Light Every Night – New nighttime light data set and tools for development
https://blogs.worldbank.org/opendata/light-every-night-new-nighttime-light-data-set-and-tools-developmentAWS is proud to make the Light Every Night data available through our Registry of Open Data on AWS. Making global nighttime imagery more widely accessible will allow researchers to process data in-place on the cloud, enabling new large-scale, long-term analyses that can help inform insights into historical trends like population change, economic development, and energy consumption.