• Blog
  • 4 March 2016

Sustainable Development Goals, seen through the perspective of data standards

Standards help us understand the meaning & significance of data.The SDG framework is a standard of logically classified data.

Written by Beata Lisowska

I have just completed the first of a series of discussion papers for our Joined-up Data Standards project. Finding a way to talk about standards in a language that is accessible and relevant is an interesting challenge. Taking a broad overview of the new Sustainable Development Goals (SDG) seemed like a good place to start.

A data standard is a set of rules by which data is recorded and stored. Standards help us understand the meaning and the significance of the data stored on top of their format. Following this logic, the SDG framework – with its goals, targets, indicators and methodologies – is a standard of logically classified data with clear definitions to report it into. Due to its composite nature it is a perfect example of why joining data standards is not only important but also necessary.

The SDG framework is not new in its architecture or content. This framework depends heavily on the previous Millennium Development Goals (MDGs) in terms of its format, classification and even the elements making up the new goals and indicators. Our first port of call was therefore to compare the new with the old to understand similarities and differences. We also looked at the new standards in relation to other existing monitoring standards.

The Inter-agency and Expert Group on the SDGs (IAEG-SDGs) brought together a range of subject matter and statistical experts to design a set of priority indicators fit for the next 15 years, building out from the MDGs. They needed to take into account what had gone before, what data was and could be available and what the subject-matter experts believe are the most relevant indicators moving forward. This balance is not without challenges as we discovered when looking at child mortality.

For the past 15 years, child mortality has been monitored through the infant mortality rate (from birth to 1-year-old) and under-5 mortality rate. This timeframe and the importance of the MDGs gave the infant indicator consistent data points in developing countries and a methodology that was fine-tuned over two decades. In the new framework this indicator has been changed to measure the neonatal (0 to 28 days) mortality rate. There are good clinical reasons for this: neonatal rates where they have been recorded are dropping slower than infant rates. However, vital statistics on neonatal deaths from civil registration data are only available for 38 out of 139 developing countries. The lack of a comprehensive data set means it will need to be estimated for the majority of countries. The proposed methodology suggests that this estimation will be based on under-5 data; but the under-5 mortality rate is, in most of these countries, already estimated from the infant rate.

There is no one-size-fits-all solution to problems like this. This paper is only the beginning of a discussion on the SDGs in the light of other existing standards. We live in a linked world and a joined-up approach will hopefully provide us with a comprehensive and holistic framework for analysis.

This blog was written as a part of the Joined-up Data Standards project, a joint initiative between Development Initiatives and Publish What You Fund.