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  • Australian Data Archive

    The Australian Data Archive provides facilities for collecting and archiving digital research data, which are then made available to secondary users and researchers.
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  • UK Data Archive

    The UK Data Archive is the UK's largest collection of digital research data in the social sciences and humanities.
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  • Scaling impact: Innovation for the public good

    This book, written by Robert McLean (IDRC) and John Gargani (Gargani + Company), presents actionable principles that can help organizations and innovators design, manage, and evaluate scaling strat­egies.
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  • Considerations for using data responsibly at USAID

    The aim of this resource is to provide a framework for identifying and understanding risks associated with the collection and use of data.
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  • Data value map

    The purpose of the Data Value Map is to spark new conversations and new thinking about how data initiatives can add value to an organisation. 
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  • Announcing the IDRC program managers' guide to evaluation and the GeneraTOR

    We’re excited to announce the launch of the BetterEvaluation and IDRC (International Development Research Centre) Program Managers’ Guide to Evaluation and GeneraTOR.
    Blog
  • IDRC strategic evaluation of capacity development: Doing things better?

    The paper from the International Development Research Centre (IDRC) analyses whether the results from capacity building projects have supported the organisation to achieve its mission.
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  • Como elaborar modelo lógico:roteiro para formular programas e organizar avaliação

    Este documento apresenta uma descrição do modelo logico, sua aplicabilidade, e como desenvolver um modelo logico com a finalidade de aperfeiçoar programas e projetos.
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  • Responsible data stewardship

    This report from the Open Data Institute discusses key concepts including ‘data stewardship’, ‘data ethics’, ‘data justice’ ‘data for good’ ‘responsible data’, ‘data sovereignty’, ‘Indigenous data sovereignty’, and ‘data feminism’.
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  • Data cleaning 101

    This paper from the Robert Wood Johnson Medical School outlines a step-by-step process for verifying that data values are correct or, at the very least, conform to a set of rules through the use of a data cleaning process.
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