Data Disaggregation Resource Library
A central repository for policy, guidance, standards and materials on data disaggregation in a global development context
Why is data disaggregation important for global development?
The Global Goals focus on equity and universality in order to ensure that the furthest behind are reached and no one is left behind. In order to track progress at the national, regional and global level, a large amount of high quality, timely and disaggregated data is needed. To deliver on this the DFID Data Disaggregation Action Plan was published in January 2017. This blog post draws together the main resources, policy commitments and standards which have been developed to support with the step change which is needed on data disaggregation. Our understanding and practice is based on a common understanding on a Human Rights-Based Approach to Data (HRBAD), with a focus on issues of data collection and disaggregation.
This page will be updated when new resources become available so please check back if you don’t find what you are looking for and if there is something which you think I should include please get in touch or leave me a suggestion in the comments section under this post.
The WHO estimates that one in seven people have a disability, but in most countries there is little information around this. Data is not collected at all, or not collected appropriately. This makes it far too easy to ignore the needs of people with disabilities, who are already amongst the most marginalised in society. The Washington Group questions help us to address this gap.
The mandate for the Washington Group on Disability Measurement grew out of the initial work begun at the United Nations International Seminar on Measurement of Disability in New York on June 4–6, 2001.
Wider use of the Washington Group questions will enable delivery of disaggregated data. This will allow us to ensure that international development interventions are truly inclusive. Using the questions will support us in our efforts to leave no one behind.
The Washington Group questions have been rigorously tested in the field across continents in many languages to ensure that they deliver comparable data. The Washington Group questions are not perfect. The short questions do not currently measure mental health. It is not possible to address the complexity of mental health in a question set which is designed for embedding in national census and surveys.
- Washington Group short set of questions on disability infogrpahic.
- DFID’s guide to disaggregating programme data by disability.
- Our Experience of Using Disability Disaggregated Data: Sightsavers International Share Learning — This is an honest account of some of the benefits and challenges of gathering and using disability disaggregated data from Sightsavers.
- A Conversation on Data Disaggregation: An Inclusive Revolution
- DFID Guidance on Ageing and Disability Inclusive Humanitarian Response. This Guidance Note provides DFID staff with an overview of how to ensure the needs of older persons and people with disabilities, including people with injuries and chronic diseases are addressed in humanitarian response. The guidance note contains requirements on data disaggregation in humanitarian programming.
- Practice note on collecting and using data on disability to inform inclusive development. This paper by CBM UK and Plan International on the collection of disability data is a useful resource which contains information on the Washington Group short set of questions on impairment as well as a broader introduction to collecting data on disability and making data collection inclusive.
Training videos on the Washington Group methodology are now available online:
Currently much of the available data does not allow for an accurate story to be told about the lives of all people irrespective of their age. Much of the available household survey data in developing countries excludes people over the age of 49. This stops us from being able to track the impact of development programmes on older people. Similarly many surveys do not collect or routinely disaggregate data below the age of 15. This results in a failure to accurately describe the reality of day-to-day life of younger people. This stops us from being able to measure progress and prevents millions of people receiving the help they need.
- Open Policy Making to Improve Age Disaggregated Data
- Open Policy Making to Improve Age Disaggrgated Data: Aging
- Open Policy Making to Improve Age Disaggrgated Data: Youth
- Help Us Improve Disaggregated Data: Technical Discussion paper
- Using Age and Sex Disaggregated Data: HelpAge International Share Learning. This is an honest account of some of the benefits and challenges of gathering and using age and sex disaggregated data from HelpAge.
- DFID Guidance on Ageing and Disability Inclusive Humanitarian Response. This Guidance Note provides DFID staff with an overview of how to ensure the needs of older persons and people with disabilities, including people with injuries and chronic diseases are addressed in humanitarian response. The guidance note contains requirements on data disaggregation in humanitarian programming
Sex disaggregated data as defined by the 2008 DFID Gender Manual is quantitative statistical information on differences and inequalities between women and men. Sex disaggregated data might reveal, for example, quantitative differences between women and men in morbidity and mortality; differences between girls and boys in school attendance, retention and achievement; differences between men and women in access to and repayment of credit; or differences between men and women in voter registration, participation in elections and election to office.
USAID provide, what is in my view, a fantastic condensed suite of three documents on this subject which complement each other fantastically.
- Data Disaggregation by Geographic Location — This document has been designed by USAID to support programme staff and managers with decisions on indicators to use for geographical data disaggregation. The document goes on to discuss how the data can be used to inform good decision making in policy and programmes. It is comprehensive but refreshingly succinct.
- Country case study on how to analyse geographic data — This document has been designed by USAID to provide an example case scenario illustrating the guidance above.
- Checklist — This document has been designed by USAID to ensure that programme staff and managers can quickly check they are implementing best practice.
At a meeting of the UN Expert Group on Data Disaggregation in New York in June 2016 Dr. Robert S. Chen from Columbia University gave a presentation on data disaggregation by geographic location together with mapping population, settlements, and infrastructure. You can download the presentation here.
Further Information
