🏷 Project Template¢

The Data Partnership Project Template creates a project structure inspired by the Cookiecutter Data Science with an out-of-box Jupyter Book published automatically on GitHub Pages.

Here are some of the practices that project template aims to encourage:

  • Reproducibility

  • Transparency

  • Credibility

Project ChecklistΒΆ

Important

Coming Soon

Additional ResourcesΒΆ

  • Development Data Partnership

    A partnership between international organizations and companies, created to facilitate the use of third-party data in research and international development.

  • Awesome Data Partnership

    A curated list of projects, data goods and derivative works associated with the Development Data Partnership

  • The DIME Wiki

    The DIME Wiki is a public good developed and maintained by DIME Analytics, a team which creates tools that improve the quality of impact evaluation research at DIME. The DIME Wiki is targeted to all researchers and M&E specialists at the World Bank, clients who are managing data collection efforts in the field, donor institutions, universities, NGOs, and governments. While there are many existing impact evaluation resources, none meet the specific gap the DIME Wiki aims to fulfill: a resource focused on practical implementation guidelines rather than theory, open to the public, easily searchable, suitable for users of varying levels of expertise, up-to-date with the latest technological advances in electronic data collection, with a vibrant network of editors who are experts in this field.

  • The DIME Analytics Data Handbook

    This book is intended to serve as an introduction to the primary tasks required in development research, from experimental design to data collection to data analysis to publication. It serves as a companion to the DIME Wiki and is produced by DIME Analytics.

  • GitHub Pages

    GitHub Pages are public webpages hosted and easily published through GitHub.

  • Jupyter Book

    Jupyter Book is an open source project for building beautiful, publication-quality books and documents from computational material.