This is a free online directory of resources devoted to humanitarian monitoring, evaluation, data and analytics. It includes links to a mix of publications, guidelines, websites and learning tools. It’s curated by Data Conscious. To add your own resource to the directory, just click on the button below.
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If you have a specific search-term you want to learn more about, use the search function to scan the whole directory for related resources. You can specific resource categories using the arrow on the right.
browse the curated list
If you want to browse the key resources in the directory, then scroll through the following lists of blog articles, publications, websites and learning resources below. All curation is done by Data Conscious.
blog articles
The following resources are all easy-read blog posts covering topics like big data, predictive analytics, AI and innovations in monitoring and evaluation of humanitarian action. Use these to learn more and stay up-to-date.
Big data or big hype: a MERL Tech debate
A MERLTech blog article on big data applications to M&E. Summarises a debate held at MERLTech London with experienced evaluators Michael Bamberger and Rick Davies.
Big data, big problems, big solutions
A MERLTech blog article on big data applications to M&E. Covers some of the traditional challenges of development data and proposes potential avenues for exploration.
big data, big responsibilities
A MERLTech blog article looking at the issues arising from the use of big data within M&E. Includes additional resources in appendix. Authored by Catherine
Building bridges between evaluators and big data analysts
A MERLTech blog article on the gaps and linkages between evaluation and big data specialists. Looks at the reasons why evaluators have, in the view
How I Learned to Stop Worrying and Love Big Data
A MERLTech blog article describing the ethical problems of using big data; contrasted with the costs of not using it. Authored by Zach Tilton, a Peacebuilding
Integrating Big Data into Evaluation: a conversation with Michael Bamberger and Rick Davies
A MERLTech blog article on big data applications to M&E. Summarises a debate held at MERLTech London with experienced evaluators Michael Bamberger and Rick Davies.
publications
The following resources include in-depth articles, published by academic journals, think-tanks, or humanitarian agencies. They include research articles, guidelines and toolkits covering the intersection between data science, M&E and humanitarian action. Use these to understand what leading thinkers and humanitarian agencies are thinking on this topic.
Back to the Drawing Board: How to improve monitoring of outcomes
This paper, published by the ALNAP Secretariat, aims to encourage humanitarian agencies to step back and reflect on what is currently being done to measure
Beyond the Numbers: How qualitative approaches can improve monitoring of humanitarian action
This paper looks at potential ways to improve the capture and uptake of qualitative data in monitoring of humanitarian programmes. The first section of the
Breaking the Mould: Alternative approaches to monitoring and evaluation
This paper, published by the ALNAP Secretariat, looks at a range of M&E innovations that are designed specifically to provide input to ongoing iterative decision-making
DSEG Ethical Framework
A framework for applying data science methods to humanitarian action. Compiled by the multi-agency Data Science and Ethics Group https://www.hum-dseg.org/ Provides a set of ethical
Information and Communication Technologies for Development Evaluation
This book gives an insight into the implications of new and emerging technologies in development evaluation. It looks at the potential applications of big data
Measuring results and impact in the age of big data
Measuring results and impact in the age of big data: The nexus of evaluation, analytics, and digital technology. This report explores how data science and
websites
The following resources include in-depth articles, published by academic journals, think-tanks, or humanitarian agencies. They include research articles, guidelines and toolkits covering the intersection between data science, M&E and humanitarian action. Use these to understand what leading thinkers and humanitarian agencies are thinking on this topic.
better evaluation
An online community of evaluation practitioners devoted to sharing learning, tools and frameworks for evaluation. Covers all aspects of evaluation practice including methods, tools, approaches
Towards data science
A Medium blog sharing all things data science: concept, ideas and code included. Great resource for widening your knowledge of data science and its potential
learning resources
The following sites include key courses and learning resources in the fields of data science, monitoring and evaluation methods. Use these to improve your knowledge of each area and find out how to get accredited expertise.
code academy
Online coding courses covering Python, SQL and more. Data science career path provides basics of coding, data science and analytics. Courses are interactive and focused
Datacamp
Online coding courses covering R, Python, SQL and more. Data analysis, visualisation and statistics included. Covers basics of data science, engineering and analytics. Courses are
Dataquest
Online coding courses covering R, Python, SQL and more. Data analysis, visualisation and statistics included. Covers basics of data science, engineering and analytics. Courses are
harvard university professional certificate in data science
Online certified course designed by Harvard and hosted by EdX. The course covers R, fundamentals of statistics, data wrangling, visualisation, wrangling, machine learning models and
Johns hopkins university Data science specialization
Online certified course designed by Johns Hopkins and hosted by Coursera. The course covers data science, R, GitHub, data cleansing, regression analysis, cluster analysis, debugging
MIT statistics and data science micromasters
Online coding courses covering R, Python, SQL and more. Data analysis, visualisation and statistics included. Covers basics of data science, engineering and analytics. Courses are