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About the Inclusive Data Charter
ONS are committed to improving the quality, quantity and availability of inclusive data. We signed up to the Inclusive Data Charter in 2018, partnering with the Global Partnership for Sustainable Development Data.
Since then, the National Statistician convened an independent taskforce in 2021 to identify initiatives to ensure that everyone counts and is counted in UK data and evidence. This includes activities to build trust with those participating in data supply, methodological work to improve inclusion and conceptual measurement of currently under-represented population groups, and improvements in the accessibility of data and analysis.
As a result, the Inclusive data charter action plan for the global Sustainable Development Goals (SDGs) published in 2018 has been replaced with the Inclusive Data Taskforce Implementation Plan. This summarises known initiatives - including those related to the SDGs - across the UK statistical system, joining up the work across analysts in the governments across the UK, and with initiatives happening outside government.
The golden thread of the Sustainable Development Goals (SDGs) agenda is the promise to leave no one behind. Without this commitment, history tells us that only pockets of our society will progress and often, the poorest and most disadvantaged will fall further behind. To realise this promise, we first need data that are timely, comprehensive and disaggregated – to better understand where these people are, their circumstances and how we can capture them in the data we collect. These data will then be made available to all, including decision-makers and civil society organisation so that they can prioritise their efforts and develop policies that reflect their needs.
The Office for National Statistics (ONS) has partnered with the Global Partnership for Sustainable Development Data (GPSDD) and its global network to reaffirm our commitment for improved and strengthened data disaggregation through this charter. Collectively, we will work to improve the quality, quantity and availability of inclusive data and share efforts so that progress is accelerated.
What does inclusive data mean?
Inclusive data means ensuring that data are collected for all people, regardless of their location, ethnicity, gender or age. It’s about closing the data gaps that inadvertently facilitate discrimination and bias in monitoring, evaluation and decision-making for all of society.
The Charter is underpinned by five principles:
Principle 1: All populations must be included in the data
Principle 2: All data should, wherever possible, be disaggregated in order to accurately describe all populations
Principle 3: Data should be drawn from all available sources
Principle 4: Those responsible for the collection of data and production of statistics must be accountable
Principle 5: Human and technical capacity to collect, analyse, and use disaggregated data must be improved, including through adequate and sustainable financing
The aspiration of this global network is that others will join us in signing up to the charter and share their Inclusive Data Action Plans, so that we are able to share existing learning, demonstrate at a country level how this work is being done – even in challenging contexts and accelerate the pace of efforts to improve data availability and analysis, enabling the SDG promise to “leave no one behind.”
SDG indicators “should be disaggregated, where relevant, by income, sex, age, race, ethnicity, migratory status, disability and geographic location, or other characteristics, in accordance with the UN Fundamental Principles of Official Statistics1”.
ONS and the strategy for UK statistics
ONS is the UK’s National Statistical Institute and largest producer of official statistics. UK official statistics are also produced by the Government Statistical Service (GSS), a cross-government network, spread across a whole range of public bodies, including components of the devolved administrations and UK government departments. Both are led by the National Statistician, John Pullinger.
Our work is directed by the strategy for UK Statistics: Better Statistics, Better Decisions2 which sets the collective mission to produce “high quality statistics, analysis and advice to help Britain make better decisions”.
The Better Statistics, Better Decisions strategy recognises that “Rapid changes in society and technology mean that more data, in richer and more complex forms, is available than ever before. In the commercial world the ability to mobilise the power of data is a key ingredient for success for many organisations. In this context it is more important than ever for official statistics to do the same for the most important decisions facing the country”. To support these new challenges, we launched the Data Science Campus in March 2017 which is using innovative new methods and data sources to produce new statistics and insights.
We have the responsibility to report on UK progress towards the 244 global SDG indicators3. We work in close collaboration with the Department for International Development (DFID) who have policy leadership for SDGs in the UK. Where possible, we work with DFID’s strategic partner countries to support capacity development and share knowledge and experience.
Notes about introduction
For more information, see paragraph 26 of the Report of the Inter-Agency and Expert Group on Sustainable Development Goal Indicators (PDF 930.06KB), published February 2016
Better Statistics, Better Decisions, Strategy for UK statistics, 2015 to 2020
The total number of indicators is 244. However, because nine indicators repeat under two or three different targets the actual total number of unique indicators in the list is 232.
2. Making data more inclusive
“Good data makes it intolerable to do nothing” John Pullinger, UK National Statistician
Making data more inclusive will ensure that the statistics we collect are for all people, regardless of their location, ethnicity, gender or age.
ONS and the GSS routinely collect and publish statistics related to the economy, population and society at national, regional and local levels. We have long established statistical systems that provide rigorous, comprehensive and independent statistics for the UK. Despite all this, and the new opportunities brought about by the data revolution, the challenge for the UK is very real. Some of these challenges are outlined in this article, although this is not an exhaustive list.
Data collection, quality and dissemination
When data are disaggregated to lower levels, they can become less robust and potentially more disclosive.
Existing survey data might not always be able to provide the information that we need at the levels required, or might only be able to provide it at a country rather than a UK headline level.
Creating new surveys or adding questions to existing surveys to gain more information regarding new indicators can be expensive and burdensome.
Administrative data might provide us with more granularities, but as it was not collected for statistical purposes in the first instance its quality will vary and it might not comply with statistical definitions or the concepts we are trying to measure.
Partnering with others, for example non-official data producers (for example Food and Agriculture Organisation (FAO) to agree how their data can be used by us to better report towards the global SDG indicators.
Classification and harmonisation – methods and definitions
Surveys are administered across government and by non-official data producers, often using different classifications and definitions; therefore, data across surveys are not always comparable.
While the SDGs are a global agenda, the methods we use in the UK do not always align with the methods suggested for the global indicators. For some Tier 3 indicators, there are no universally agreed methods at all.
Building new capabilities and use of new innovative techniques
This means looking for new data sources, linking existing ones, or modelling. For example, the mortality team in ONS is considering linking death registration data to 2011 Census or Hospital Episode Statistics data, so that we can report on deaths from suicide by ethnic group; this will provide disaggregated data for the suicide mortality rate indicator under Target 3.4, which is about ending premature mortality and promoting mental health and well-being.
We need to become smarter and employ new technologies, such as using earth observation data and satellite imagery to create new data sources.
Reporting data for the UK
- Reporting data for the whole of the UK can be challenging, as data are often not collected consistently across the four countries which means that the way devolved administrations (Wales, Scotland and Northern Ireland) measure things like health and education might differ to how data are collected for England.
One of the ways we will overcome some of these challenges is through the Digital Economy Act 2017, which is new legalisation that represents a unique opportunity to deliver the transformation of UK statistics. The existing legal framework governing access to data for official statistics is complex and time-consuming .
The Act gives us powers to make use of data already held across government and beyond. This should deliver better access to administrative data for the purposes of statistics and research, delivering significant efficiencies and savings for individuals, households and businesses. Decision-makers need accurate and timely data to make informed decisions, and for prioritising public resource. This Act will deliver better statistics and statistical research to help Britain make better decisions.
Priority data developments
Since January 2018, we have a dedicated team responsible for working with experts and data scientists to develop new methods, using new innovative techniques, to help us fill SDG data gaps. We are continuing to work with experts from government and beyond (such as charities, academia, business and international organisations) to identify new opportunities to collaborate and accelerate UK efforts to fill data gaps and fulfil the Leave No One Behind (LNOB) commitment.
Research and development work for three priority SDG indicator disaggregations (that is geography, disability and age) are underway. These have either been flagged as a priority by our stakeholders or where there is alignment to other programmes of work across government. More information on these developments can be found in our Inclusive Data Action Plan (section 5).Back to table of contents
3. What progress have we made?
Headline data gaps
In March 2018, we published our first report on UK data gaps: Inclusive Data Action Plan towards the global Sustainable Development Goal (SDG) indicators1 which included the first iteration of our Inclusive Data Charter Action Plan. Since then, we have sourced and reported 30% more data; meaning we are now reporting data for 148 of the 244 indicators on our National Reporting Platform (NRP).
Of the 96 unreported indicators, we have assessed that:
10 indicators (10%) are considered genuine data gaps, there are no known data sources that will fill these gaps
11 indicators (11%) are non-statistical indicators, these refer to a need for policy implementation, rather than quantitative data measuring progress
75 indicators (78%) are believed to have existing data sources available, suitable data proxies, developments in progress or that the indicators do not require measurement (non-statistical indicators)
As we continue to assess our data gaps and the data we have published on our NRP, our analysis of how these indicators are classified will change, for example, where we believe existing data already exists but it cannot be fully disaggregated, then it will become a disaggregation gap.
Of the 148 global SDG indicators being reported on our National Reporting Platform, 99 indicators (67%) are considered to have disaggregation gaps. When we assessed data coverage against the seven levels of disaggregation2, we found 459 disaggregation gaps. Figure 1 shows the number of gaps by the seven characteristics.
We have devised a three-staged approach up to March 2020 which will afford us the opportunity to: better understand the challenges for UK data gaps, engage users to understand their priorities and needs and consider the data needs across policy departments to ensure we get maximum benefit and use of these new developments. These developments align to our operational delivery roadmap and strategic priorities for informing public and policy debate.
We have commissioned data developments within ONS that not only support Government Statistical Service (GSS) strategic priorities, but also align to feedback we have received from users (see Section 5).
By the end of March 2019, we will expand our development portfolio by commissioning new developments across the GSS; and through the use of data science techniques and innovations. These developments will include: feasibility works; development of new methods; modelling existing datasets; and creating new data sources to fill data gaps; at headline level and by priority disaggregation.
By the end of March 2020, we have set ourselves a goal of reporting against 75% of the SDG Indicators, and filling 50% of disaggregation data gaps for the eight characteristics stipulated by the United Nations.
Figure 1: Number of disaggregation gaps for the reported indicators
Source: Office for National Statistics
Total disaggregation gaps: 459
These figures include disaggregation gaps that are currently being sourced (approximately 15%).
As we continue to assess our data gaps and the data we have published on our National Reporting Platform, our analysis of how these indicators are classified will change to reflect our findings.
Statistics on race are not regularly collected in the UK, but further assessment is required before we can report on this characteristic.
Disaggregation gaps by geography includes indicators where data are provided at country levels (England and Wales) but not at the UK level.
Download this chart Figure 1: Number of disaggregation gaps for the reported indicatorsImage .csv .xls
With our commitment to the Leave No One Behind (LNOB) we aspire to provide disaggregated data for all UK data sources, where relevant.
What is new or different?
We are committed to making our plans and priorities for filling UK data gaps towards the global SDG indicators open and transparent. We have shown this commitment by signing up to the Inclusive Data Charter. We are also hoping to share our experiences so that others can reuse our new methods and approaches, so that progress is accelerated across the statistical community.
Note about what progress have we made?
UK data gaps: Inclusive Data Action Plan towards the global Sustainable Development Goal indicators, ONS March 2018
Statistics on race are not regularly collected in the UK, but further assessment is required before we can report on this characteristic.
Through our data development work, we hope to be a leading example on open access data and data disaggregation for the 2030 Agenda. In this way, we aim to contribute both nationally and internationally to improved methods for those indicators without agreed methodologies and standards (Tier 3 indicators), and better data that reflect all in our society at both the national and local levels.Back to table of contents
5. UK Inclusive Data Action Plan for the 2030 Agenda
Table 1 is a high-level summary of our current portfolio of data developments which are supporting our efforts to fill data gaps and work towards the “leave no one behind” commitment by ensuring data can be disaggregated by the eight characteristics specified by the United Nations.
Table 1: Inclusive Data Action Plan: Data developments to fill UK data gaps for the Sustainable Development Goals (SDG) indicators
|Purpose||Project||Development||Timeframe||Link to SDG indicator(s)|
|1. Geography coverage (UK priority)|
|We held an open public consultation last summer where priority for our users is disaggregation by geographic levels.
It is our ambition to go down to small area statistical geographies, the Output Area hierarchy, as well as breaking down by geographic
classifications such as rural or urban or the local authority classification.
ONS is a member of the Geospatial Working Group of the United Nations Inter-Agency and Expert Group (UN IAEG), which is considering the
availability of global geospatial datasets and identifying spatial methodology that could be used to provide disaggregated data. ONS also worked on the
development of the Global Statistical Geospatial Framework – a set of principles developed by the UN Expert Group on the Integration of Statistics and
Geospatial Information (UN EG-ISGI) to support the use of geospatial data within the sustainable development agenda.
|ONS Esri geography
|The UK is part of a UN Statistics Division and ESRI project,
which aims to demonstrate how Esri applications can support countries report on SDGs and fill data gaps, using earth observations
and satellite imagery.
The outcomes from this project will be published in Summer 2018
and embedded in our National Reporting Platform.
|Short term.|| 9.3.1, 9.11, 11.3.1 and 11.6.2
|ONS SDGs funded geography post||This post holder will work to improve the geographic coverage of UK SDGs data, fill data gaps through the development of new data sources or methods and carry out spatial analysis to support our reporting on SDGs.
Future milestones to be agreed.
|Short to long term.
Provide data by March 2019.
|Work will start with: 3.5.2, 6.6.1 and 11.7.1.|
|ONS and Ordnance Survey project||This project is looking to fill data gaps at headline level for environment-related SDG indicators and to further disaggregate data by geography. A workshop was held in June to discuss workplan of projects and agree deliverables.||Short to long term.
Timelines to be agreed.
|9.1.1, 11.3.1, 11.7.1, and 15.1.1.|
|2. Ageing-related statistics and age-disaggregated data (UK priority)|
|As the proportion of the world’s population in the older ages continues to increase, the need for improved information and analysis of population ageing becomes pressing. Furthermore, implementation of the 2030 Agenda for Sustainable Development and the pledge to leave no one behind require timely and reliable data across all ages.
In March 2018, the UN Statistics Commission form a new city group, the Titchfield Group.
|Titchfield City group on ageing||This group will contribute to and build upon international standards and methods for the compilation of ageing-related statistics and age-disaggregated data, by reviewing and extending existing advances and by enlisting expertise from various countries as well as the international, academic and non-profit sectors concerned with ageing-related statistics and age-disaggregated data.||Long term work.
Timelines to be agreed.
|Disaggregation by age relates to most SDG indicators.|
|3. Disability status (UK priority)|
|The UK Department for International Development (DFID), along with co-hosts the International Disability Alliance and the Government of Kenya will host the first-ever Global Disability Summit in London 24 July 2018.
The purpose of the Forum is to leverage the opportunity to amplify the perspectives and participation of persons with disabilities, through their individual participation and that of representative organisations. It is also to highlight current issues relevant to the global disability movement.
|Project to improve disability data for SDG indicators.||We have begun to improve data coverage for disability status by publishing disaggregated data for four SDG indicators flagged by the Department for Work and Pensions (DWP) as a priority.
We are continuing to work with data experts to see if their microdata can be further broken down by disability status, for example for labour market statistics.
|Short to long term.
Work to disaggregate 4 indicators (as specified by DWP) is now complete and all the 4 indicators have been disaggregated by disability.
|Disaggregation by disability is relevant to most SDG indicators.
Four priority indicators: 8.5.1, 16.1.3, 16.1.4 and 16.7.2.
|4. Migratory status (UK priority)|
|The SDG team will work with the ONS Migration Statistics team who are looking to develop alternative data sources to improve the evidence base for international migration.
This work is part of an ambitious programme, across the UK Government Statistical Service (GSS), looking to improve international migration data, particularly around the impact of international migration on society and the economy, at national and local levels.
|Project to improve migration reporting for SDG indicators.||ONS Migration Statistics developments will assist us in reporting migratory disaggregation of some of the SDGs.||Data delivery to begin by March 2019.
Timelines to be agreed.
|Migratory status is specifically mentioned in indicators 8.8.1, 8.8.2 and 10.7.1.|
|5. Topic-related developments|
|ONS and the Department for Rural Affairs (Defra) have been developing methods to value these services, aiming to highlight the relative importance of services provided by the UK’s natural assets. Natural capital accounts offer a consistent way of looking at the significance of nature and can help identify drivers of ecosystem change. The development of monetary valuation allows economic and environmental data to be presented in a consistent unit, raising awareness of the economic and social significance of natural capital.||Natural Capital Project||In co-operation with the Department for Environment, Food and Rural Affairs (Defra), the developing of Natural Capital accounts will inform some of the SDG indicators. Natural assets provide a wide range of ecosystem services that make human life possible: the food we eat, the water we drink and less visible services such as climate regulation and the inspiration we take from wildlife and the natural environment.||Long term Project(s)
Natural Capital accounts have set out a 2020 Roadmap, which shows a workplan of the accounts
|Natural Capital work links to many SDG indicators such as 11.7.1 and 15.4.2|
|Housing Stock Analytical, Wales
Data developments to fill data gaps in Housing Conditions evidence. Priority areas to supplement in the Welsh Housing Conditions Survey and enhance the HSAR are:
• basic property characteristics (dwelling size, type, construction type and age)
• household characteristics (household structure, equalities characteristics, occupant status and income)
• energy use characteristics (energy efficiency installations, non-grid fuels, households in fuel poverty)
• disabled access
|The SDGs team is collaborating with the Welsh Government and ONS data experts to develop new methods and data sources for assessing the housing conditions of homes in Wales.||Long term
Delivered by July 2019
|We contacted government departments to find out what areas future gaps work should prioritise to align with strategic priorities.||Strategic priorities for the Government||We are undertaking scoping work to determine what data currently exist, where there may be gaps and possible new methods that can be used to fill data gaps and report data for the UK.||Not started
To be determined.
|2.1.2, 4.1.1., 4.2.1., 4.5.1 and 4.7.1.||6. ONS collaborations|
|We are working closely with the Data Science Campus (the campus). The Campus’ remit is to explore innovative new data sources, new tools and new technologies, to inform our understanding of the UK economy, people and society. It carries out short (six months or less) prototyping projects.||Collaborations with the Campus||The Campus is supporting the UK's work on SDGs by exploring the potential of new data sources and techniques to fill the data gaps in housing quality and access to services.||Short to long term.||2.1.2 and 11.1.1|
|ONS has recently undertaken an audit of sources across government and more widely which include data on the nine protected characteristics (age, disability, gender reassignment, race, religion or belief, sex, sexual orientation, marriage and civil partnership, and pregnancy and maternity) of the Equality Act 2010. This audit is intended to provide a more coherent picture of inequalities data and evidence for these groups and will be highlighting where there are gaps for characteristics and sections of the population, and in terms of the granularity of the data coverage (topics, geography, and so on) and its timeliness.||ONS Inequalities audit||We are working closely to ensure that data and evidence relating to the protected characteristics that align to SDG disaggregations, such as age, disability, race and sex are jointly developed so that new data sources and methods can benefit both work programmes and escalate efforts for disadvantaged or discriminated groups.||Medium to long term.||Disaggregations by the protected characteristics will be relevant to most of the SDG indicators.|
Notes about UK Inclusive Data Action Plan for the 2030 Agenda
- ONS experts include the Data Science Campus and Data as a Service; both of which use new technologies to develop new data sources.
6. Annex A
Criteria for the prioritisation of data developments
We are responsible for working with all users, including topic experts to develop new data sources and methods that can be used to report UK progress towards the global Sustainable Development Goals (SDGs). While all global goals, targets and indicators are to be treated with equal importance, we must start somewhere. So far, we have prioritised the collection of data at a headline level, from within government and international agencies reporting to the United Nations. We have then applied the following criteria to prioritise data developments:
do developments inform, or align to, strategic and policy priorities for government departments?
are developments considered a priority to our users?
is there scope to inform statistical capacity building?
for those indicators without agreed methodologies and standards (tier 3 indicators), is there scope to engage internationally on the development of new methods, standards or classifications?
will the development provide new data for the eight disaggregations stipulated by the United Nations?
is the new development considered sustainable, that is, will production of this measure continue for the duration of the 2030 Agenda?
is the financial cost of the development proportionate to the anticipated outcomes?
Contact details for this Methodology