Guidelines on improving the collection and use of equality data.
Date: 2021-09-03
Institutions: Directorate-General for Justice and Consumers
Subjects: anti-discriminatory measure, data collection, data protection, equal treatment, gender equality, institutional cooperation, official statistics, user guide

High Level Group on Non-discrimination, Equality 
and Diversity 

2018 

Subgroup on Equality Data 

Guidelines on improving the collection and use of equality 
data 

Justice 
and 
Consumers 

 
 
 
 
 
 
                                                                                                                     
 
 
 
 
 
 
 
 
 
 
 
 
 
EUROPEAN COMMISSION 

Directorate-General for Justice and Consumers 
Directorate D – Equal Opportunities Equality and Union citizenship 
Unit D1 - Non-discrimination and Roma coordination 
European Commission 
B-1049 Brussels 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Guidelines on improving the collection 
and use of equality data 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Manuscript completed in July 2018 

PDF 

ISBN 978-92-76-40995-3 

doi:10.2838/9725 

DS-01-21-146-EN-N 

Luxembourg: Publications Office of the European Union, 2021 

© European Union, 2021 

The reuse policy of European Commission documents is implemented by the Commission Decision 2011/833/EU of 12 
December 2011 on the reuse of Commission documents (OJ L 330, 14.12.2011, p. 39). Except otherwise noted, the reuse 
of this document is authorised under a Creative Commons Attribution 4.0 International (CC-BY 4.0) licence 
(https://creativecommons.org/licenses/by/4.0/). This means that reuse is allowed provided appropriate credit is given and 
any changes are indicated. 

 
 
 
 
 
 
 
 
 
 
 
Contents 
Section I: Background and purpose of these guidelines ......................................................................... 3 

Identifying gaps in the collection and use of equality data ............................................................ 5 

How were these guidelines developed? ......................................................................................... 8 

Section II: Guidelines on improving the collection and use of equality data ....................................... 10 

A. 

Institutional and structural guidelines ...................................................................................... 10 

1.  Map existing sources of equality data and identify data gaps ............................................. 10 

2. 

3. 

Foster inter-institutional cooperation in the collection and use of equality data ................ 11 

Set up a data hub on equality and non-discrimination......................................................... 12 

4.  Build institutional capacity to collect robust and reliable equality data .............................. 12 

5. 

Facilitate effective use of equality data ................................................................................ 13 

B.  Operational guidelines .............................................................................................................. 14 

6. 

Ensure comprehensiveness of equality data ........................................................................ 14 

7.  Mainstream equality data into EU and national surveys ...................................................... 14 

8. 

9. 

10. 

11. 

Ensure regular and timely equality data collection .............................................................. 15 

Enhance validity and reliability of equality data ................................................................... 15 

Ensure representativeness of equality data ..................................................................... 17 

Improve comparability of equality data ........................................................................... 17 

This document is not legally binding and is intended for guidance 
only. It can, therefore, neither provide legal advice on issues of 
national law, nor an authoritative interpretation of EU law, which 
remains within the sole remit of the Court of Justice of the 
European Union. 

6 

 
 
 
 
 
 
 
 
 
 
 
 
Section I: Background and purpose of these guidelines 
The European Union (EU) has in place an advanced legal framework with which to promote equality 
and non-discrimination. All 28 EU Member States have transposed this legal framework into national 
law, often going beyond the  minimum standards included in the Racial Equality Directive1  and the 
Employment Equality Directive.2  

However,  significant  proportions  of  people  in  the  European  Union  experience  discrimination, 
inequality  and  social  exclusion  on  a  regular  basis.  This  can  be  based  on  their  gender,  ethnic  or 
minority  background,  skin  colour,  religious  belief,  age,  sexual  orientation,  gender  identity  or 
disability, or a combination of these, as findings from the EU Agency for Fundamental Rights (FRA) 
consistently show.3  

This  calls  for  a  reconsideration  of  how  legislation  and  policies  to  promote  equality  and  non-
discrimination are implemented and how progress on the ground can be monitored and measured. 
Equality  data  are  a crucial  element  of  this  reconsideration  and  powerful  tools to  support  the  fight 
against discrimination and exclusion.  

This  includes,  in  particular,  the  disbursement of  European  Union  Structural  and  Investment  Funds, 
where  horizontal  EU  principles  such  as  the  aim  to  combat  discrimination  based  on  sex,  racial  or 
ethnic origin, religion or belief, disability, age or sexual orientation laid down in article 10 TFEU need 
to  be  fully  respected.  This  requires  Member  States  to  have  arrangements  in  place,  including 
monitoring through the systematic collection of robust and objective data, that ensure the fulfilment 
of their fundamental rights obligations. 4 

For historical reasons, the collection of personal data disaggregated by protected characteristics such 
as  racial  or  ethnic  origin  is  a  particularly  sensitive  issue  in  many  European  countries.  EU 
antidiscrimination legislation forbids the use of any such data to the disadvantage of the groups they 
refer to. Furthermore, such sensitive personal data are severely protected by constitutional norms, 
the  applicable  European  Union  data  protection  law  and  the  Charter  of  Fundamental  Rights. 
However, if collected and processed in full respect of this legal framework and the safeguards it sets 
out,  such  data  are  essential  for  Member  States  to  assess  their  compliance  with  human  rights 
obligations and enables policy makers to design evidence-based measures to address discrimination, 
inequalities and exclusion.  

1   Council  Directive  2000/43/EC  of  29  June  2000  implementing  the  principle  of  equal  treatment  between 

persons irrespective of racial or ethnic origin.  

2   Council Directive 2000/78/EC of 27 November 2000 establishing a general framework for equal treatment 

in employment and occupation. 

3   See for example, FRA (2017a), Second European Union Minorities and Discrimination Survey (EU-MIDIS II) 
Muslims  –  Selected  findings;  FRA  (2017b),  Second  European  Union  Minorities  and  Discrimination  Survey  - 
Main results; FRA (2016), Second European Union Minorities and Discrimination Survey (EU-MIDIS II) Roma 
– Selected findings; FRA (2014),  EU LGBT survey  - European Union lesbian, gay, bisexual and transgender 
survey  -  Main  results;  FRA  (2013),  Discrimination  and  hate  crime  against  Jews  in  EU  Member  States: 
experiences and perceptions of antisemitism. 

4   See  Proposal  for  a  Regulation  of  the  European  Parliament  and  of  the  Council  laying  down  common 
provisions on the European Regional Development Fund, the European Social Fund Plus, the Cohesion Fund, 
and  the  European  Maritime  and  Fisheries  Fund  and  financial  rules  for  those  and  for  the  Asylum  and 
Migration Fund, the Internal Security Fund and the Border Management and Visa Instrument, COM(2018) 
375  final,  2018/0196  (COD),  in  particular  Recital  5  on  respect  for  horizontal  EU  princples,  article  67  on 
selection  of  operations  by  the  managing  authority  based  on  non-discriminatory  procedures  and  taking 
account of the Charter of Fundamental Rights of the EU, and Annex III on horizontal enabling conditions.  

7 

 
 
 
 
 
 
                                                           
In  the  same  vein,  the  United  Nations  High  Commissioner  for  Human  Rights  recently  published  a 
guidance note to data collection and disaggregation for monitoring progress in achieving the goals of 
the  2030  Agenda  for  Sustainable  Development.5  It  stresses  that  data  collection  activities  should 
always be conducted in accordance with the overriding human rights principle of doing no harm and 
not create or reinforce existing discrimination, bias or stereotypes; data on personal characteristics 
should be kept safe and used only for the benefit of the groups they describe and society as a whole. 
”Do no harm  also means that  nothing in the guidance  note should be  interpreted as an invitation, 
encouragement  or  endorsement  of  any  initiative  or  practice  that  seeks  to  discriminate  against 
population  groups  and  expose  them  to  risks  of  serious  human  rights  violations  (or  which  has  this 
effect)”.6 

What are equality data? 

The  European  Handbook  on  Equality  Data  –  2016  Revision  (European  Commission,  2016,  p.  15) 
defines  data  as  any  piece  of  information,  whether  in  numerical  or  in  some  other  form.  The 
function of data is that they reveal something about some aspect of reality and can therefore be 
used for analysis, reasoning or decision-making. 

Equality data is defined as any piece of information that is useful for the purposes of describing 
and analysing the state of equality. The information may be quantitative or qualitative in nature. It 
could  include  aggregate  data  that  reflect  inequalities  or  their  causes  or  effects  in  society. 
Sometimes data that are collected primarily for reasons other than equality-related purposes can 
be used for producing equality data.  

There are different types of data sources, based on different data collection mechanisms, that can 
be  used  to  compile  equality  statistics.  Sources  of  equality  data  include  population  censuses, 
administrative  registers,  household  and  individual  surveys,  victimisation  surveys,  attitudinal 
surveys  (self-report  surveys),  complaints  data,  discrimination  testing,  diversity  monitoring  by 
employers and service providers, as well as qualitative research strategies such as case studies, in-
depth and expert interviews. 

The collection and use of equality data are indispensable to Member States for a number of different 
purposes, including:7  

- 

enabling  proper  assessment  of  the  implementation  of  the  relevant  EU  equality  legislation 
and other relevant national legal and policy frameworks; 

-  monitoring  trends  in  equality  across  different  areas  of  life,  such  as  employment  rate, 
percentage  of  persons  in  tertiary  education,  or  percentage  of  early  school  leavers,  to 
enhance evidence-based policy making;  

-  monitoring  the  compliance  of  Member  States  with  relevant  international  human  rights 
standards, such as the UN Convention on the Rights of Persons with Disabilities and the UN 
Convention on the Elimination of All Forms of Racial Discrimination; 

5   Office of the UN High Commissioner for Human Rights (2018),  A Human Rights-based Approach to Data  - 
Leaving No One Behind in the 2030 Agenda for Sustainable Development, Guidance note to data collection 
and disaggregation. 

6   Office of the UN High Commissioner for Human Rights (2018),  A Human Rights-based Approach to Data  - 
Leaving No One Behind in the 2030 Agenda for Sustainable Development, Guidance note to data collection 
and disaggregation, p. 11-12. 

7   For a comprehensive list and broader discussion of the different needs, see European Commission (2016), 

European Handbook on Equality Data – 2016 Revision, p. 19-22.  

8 

 
 
 
 
 
 
                                                           
-  making  visible  the  hidden  figure  of  discrimination,  i.e.  unreported  discrimination,  for 
example,  by  conducting  victimisation  surveys  or  conducting  discrimination  testing 
experiments; 

-  providing  reliable  evidence  in  administrative  or  judicial  cases  regarding  discrimination 

through data that point to direct or indirect discrimination; 

-  populating  indicators  to  track  progress  in  the  implementation  of  strategies  relevant  to 
fostering equality and non-discrimination to which Member States  are committed, such as 
the  European  Pillar  of  Social  Rights,  the  Europe  2020  Strategy  or  the  2030  Agenda  for 
Sustainable Development; 
supporting advocacy and awareness raising in the field of equality and non-discrimination; 

- 
-  highlighting evidence gaps where further research is needed. 

Acknowledging  the  importance  of equality  data  for  these  purposes,  the  High  Level  Group  on  non-
discrimination, equality and diversity set up the Subgroup on Equality Data in February 2018,8 with a 
view to support Member States in their efforts to improve the collection and use of equality data.9 
The  FRA  was  invited  to  facilitate  the  work  of  the  subgroup,  in  line  with  the  agency’s  mandate  to 
develop methods and standards to improve the comparability,  objectivity  and reliability of data at 
the European level.10  

Identifying gaps in the collection and use of equality data 
The work of the subgroup revealed much variation in how Member States collect and use equality 
data.  However,  the  subgroup  also  agreed  that  there  are  common  gaps  and  challenges  in  current 
practice, the most important of which are summarised below:  

1.  Lack of a coordinated approach for equality data collection and use 
Member  States  tend  not  to  have  a  coherent  and  systematic  approach  to  equality  data  collection. 
This often leads to equality data collection being unevenly split between different sources and data 
collection bodies that are generally not coordinated or connected with each other. As a result, data 
collected  by  Member  States  may  not  be  used  to  best  effect  in  monitoring  the  outcomes  of 
implement  to  foster  equality  and  promote  non-
legislation,  policies  and  measures  they 
discrimination.  

2.  Lack of sufficient resources and of awareness of the importance of collecting equality data 

8   The  Subgroup  on  Equality  Data  is  composed  of  representatives  from  the  European  Commission,  FRA, 
Eurostat,  as  well  as  representatives  from  national  administrations,  national  statistical  institutions  or 
equality  bodies.  National  representatives  were  nominated  to  take  part  in  the  subgroup  by  Belgium, 
Bulgaria,  Croatia,  Hungary,  Estonia,  Finland,  Germany,  Greece,  Ireland,  Italy,  Lithuania,  Netherlands, 
Romania,  Spain,  the  United  Kingdom,  as  well  as  Norway.  The  participation  of  Eurostat  is  of  crucial 
importance to create sinergies between the work of this subgroup and the developments at the level of the 
European  Statistical  System (ESS).  The  ESS  is  the  partnership  between  the  statistical  authority (Eurostat), 
and the national statistical institutes (NSIs) and other national authorities responsible for the development, 
production and dissemination of European statistics in each Member State.  

9   The  High  Level  Group  on  non-discrimination,  equality  and  diversity  (HLG)  mandated  the  Subgroup  on 
Equality  Data  to  prepare  a  set  of  non-binding  guidelines  on  improving  the  collection  and  use  of  equality 
data;  develop  a  diagnostic  tool/checklist  that  EU  Member  States  can  use  to  assess  the  availability  of 
equality data collected at national level, and compile practices implemented at national level related to the 
proposed set of non-binding guidelines. The HLG works on the following grounds of discrimination: sexual 
orientation  and  gender  identity,  racial  or  ethnic  origin,  age,  religion  or  belief  and  disability,  with  gender 
being taken into consideration in its intersection with these grounds.  

10   Council  Regulation  (EC)  No.  168/2007  of  15  February  2007  establishing  a  European  Union  Agency  for 

Fundamental Rights. 

9 

 
 
 
 
 
 
 
                                                           
Member  States  tend  to  underestimate  the  need  to  ground  their  anti-discrimination  policies  on 
robust  and  reliable  equality  data,  through  which  the  effectiveness  of  the  relevant  legal  and  policy 
framework  could  be  assessed.  As  a  result,  insufficient  resources  are  invested  in  improving  the 
collection  of  such  data.  In  addition,  stakeholders  who  would  be  willing  and  competent  to  collect 
equality data, such as equality bodies, research institutes and civil society organisations, often do not 
have  the  necessary  resources  to  do  so,  or  to  do  so  with  the  continuity  required  to  allow  for 
consistent monitoring over time. 

Imbalance in equality data collection on different grounds of discrimination 

3. 
Where collected, equality data  tend to concern some  grounds of discrimination more than others. 
This can lead to imbalances in equality data collection and, therefore, to large knowledge gaps. On 
the  whole,  data  collection  which  covers  grounds  of discrimination  such  as  gender11  and  age  is  the 
most developed in Member States. Data collection on disability is gradually improving, partially due 
to obligations Member States have in that regard under Article 31 of the United Nations Convention 
on  the  Rights  of Persons with  Disabilities (CRPD).  Data  collection on  the  discrimination  grounds of 
racial or ethnic origin, religion or belief, sexual orientation and gender identity tends to be the least 
developed in Member States.12 Furthermore, such imbalances in equality data collection can lead to 
a  lack  of  evidence  on  the  extent  to  which  people  experience  multiple  and  intersectional 
discrimination. 

Imbalance in equality data collection across different areas of life 

4. 
The Racial Equality Directive prohibits ethnic discrimination in a number of key areas of life, such as 
employment,  social  protection,  social  advantages,  education  and  access  to  goods  and  services, 
including housing, while the Employment Equality Directive prohibits discrimination on the grounds 
of religion or belief, disability, age or sexual orientation in the fields of employment and occupation. 
There remains, however, an imbalance in the extent to which Member States collect equality data in 
those areas covered by the directives, with employment typically being the area where most data is 
collected.  On  the  whole,  this  contributes  to  limited  availability  of  comprehensive  data  at  national 
level that cover all areas of life where people might face discrimination. 

Insufficient comparability of equality data across different data sources 

5. 
Because  different  data  sources  often  rely  on  diverging  definitions  and  use  various  population 
categorisations, equality data are often not comparable, both within and across Member States. For 
example,  some  sources  collect  data  on  issues  relevant  to  disability  by  applying  a  medical  model. 
Others follow the human rights approach enshrined in the United Nations Convention on the Rights 
of  Persons  with  Disabilities,  which  focuses  on  the  interaction  between  impairments  and  existing 
social and environmental barriers. In the absence of a mechanism to coordinate decisions on how to 
conceptualise and measure different grounds of discrimination and on how to categorise potentially 
affected  persons  or  groups,  data  and  outcomes  will  therefore  most  certainly  suffer  from 
incomparability. 

6. 

Incomplete  identification  of  population  groups  at  risk  of  discrimination  due  to  over-reliance  on 
proxies  

11    For  sex/gender  related  statistics  see  the  European  Institute  for  Gender  Equality  (EIGE),  particularly  their 
Gender  Equality  Index  (GEI)  that  includes  the  domain  of  intersecting  inequalities.    The  GEI  is  a  composite 
indicator  that  measures  the  concept  of  gender  equality  and,  based  on  the  EU  policy  framework,  assists  in 
monitoring progress of gender equality across the EU over time.  
12   See  European  Commission  (2017),  Equality  data  indicators:  Methodological  approach.  Overview  per  EU 

Member State. 

10 

 
 
 
 
 
 
 
                                                           
Self-identification  is  a  key  principle  of  a  human  rights-based  approach  to  data  collection  as 
recommended  by  the  Office  of  the  United  Nation  High  Commissioner  for  Human  Rights.13  The 
subgroup also recognises the value of proxy information, which can help provide a consistent basis 
for  monitoring  of  change  over  time.  Wherever  possible,  the  subgroup  suggests  that  both  self-
identification  and  proxy  data  are  collected  and  analysed  to  provide  a  more  holistic  picture  of 
protected  groups.  Persons  or  groups  who  experience  unequal  treatment  are  often  captured  by 
means  of  proxies  that  might  not  cover  the  full  range  of  discrimination  experiences.  This  holds 
particularly  true  for  personal  characteristics  such  as  racial  or  ethnic  origin.  Only  few  data  sources 
enable  assignment  of  personal  identities  based  on  the  human  rights-based  principle  of  self-
identification. Instead, it is more common to use imputations or proxies such as citizenship, country 
of  birth,  language  or  place  of  residence  to  determine  identities  related  to  ethnicity.  While  proxies 
may  not  be  sufficient  for  comprehensively  identifying  all  potential  victims  of  racist  or  ethnic 
discrimination, they can provide a consistent picture to enable monitoring of change over time. For 
example, the variable ‘country of birth’ cannot reveal how descendants of immigrants who are born 
in the respective country experience discrimination on the grounds of ethnic origin or skin colour, or 
other  visible  characteristics,  such  as  religious  clothing.  It,  however,  allows  for  an  analysis  of 
disparities between different population groups. 

Insufficient consultation with relevant stakeholders 

7. 
Only  in  few  Member  States  attempts  are  made  to  involve  or  consult  with  persons,  groups  or 
communities  at  risk  of  discrimination  when  establishing  definitions  and  categories  for  data 
collection.  Yet,  participation  is  not  only  a  good  practice  from  the  perspective  of  a  human  rights-
based  approach  to  data  collection,  but  results  in  more  robust  data,  greater  trust  in  the  data 
collection process and more willingness to engage in data collection exercises. A lack of participation 
of  relevant  stakeholders  in  data  collection  exercises  may  adversely  impact  the  response  rate  and 
hence the validity, reliability and representativeness of the data collected. For example, if questions 
on  discrimination  experienced  on  the  grounds  of  sexual  orientation  or  gender  identity  are  not 
consulted with potentially affected population groups, this can lead to a lack of trust in the purpose 
of  data  collection  and  to  questioning  wordings  that  do  not  reflect  the  self-understanding  of  the 
persons under study, thus deterring responses. 
8. 
Sometimes data protection requirements are understood as prohibiting collection of personal data 
such as a person´s ethnic origin, religion or sexual orientation. However, as the  explanation below 
shows  the  EU  General  Data  Protection  Regulation  (GDPR),14  which  is  directly  applicable  in  all  EU 
Member States since 25 May 2018, establishes conditions under which collection and processing of 
such data is allowed.15 

Inaccurate interpretation of the data protection frameworks 

13   Office of the UN High Commissioner for Human Rights (2018),  A Human Rights-based Approach to Data  - 
Leaving No One Behind in the 2030 Agenda for Sustainable Development, Guidance note to data collection 
and disaggregation.  

14   Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection 
of natural persons with regard to the processing of personal data and on the free movement of such data, 
and repealing Directive 95/46/EC.  

15   In case of uncertainty, data collectors could seek the advice of their national data protection authorities in 
order to confirm that their procedures do comply with the GDPR. The European Commission has published 
general  guidance  under  the  following 
link:  https://ec.europa.eu/commission/priorities/justice-and-
fundamental-rights/data-protection/2018-reform-eu-data-protection-rules_en 

11 

 
 
 
 
 
                                                           
  
Processing of special categories of personal data under the General Data Protection Regulation 
Article 9 of the General Data Protection Regulation (EU) 2016/679 (GDPR) prohibits the processing of 
personal data revealing characteristics such as racial or ethnic origin, political opinions, religious or 
philosophical  beliefs,  or  trade  union  membership,  as  well  as  the  processing  of  genetic  data, 
biometric data for the purpose of uniquely identifying a natural person, data concerning health, or 
data  concerning  a  natural person’s  sex  life  or  sexual orientation.  However,  the GDPR clarifies  that 
this prohibition does not apply, among others,  when: 

 

the data subject has given explicit consent to the processing of those personal data for one 
or  more  specified  purposes,  except  where  Union  or  Member  State  law  provide  that  the 
prohibition may not be lifted by the data subject (Article 9.2 (a));  

  processing  is  necessary  for  reasons  of  substantial  public  interest,  statistical  purposes, 
scientific or historical research purposes, or for archiving purposes in the public interest, on 
the  basis of Union or Member State  law which shall be  proportionate to the aim  pursued, 
respect  the  essence  of  the  right  to  data  protection  and  provide  for  suitable  and  specific 
measures to safeguard the fundamental rights and the interests of the data subject (Article 
9.2 (g) and (j)).  

Recital  26  of  the  GDPR  further  states  the  principles  of  data  protection  should  not  apply  to 
anonymous  information, that  is,  information which  does  not  relate  to  an  identified  or  identifiable 
natural person, or which relates to personal data  rendered anonymous in such a manner that the 
data subject is not or no longer identifiable. Recital 26 further states that the GDPR does not concern 
the processing of such anonymous information, including for statistical or research purposes. 

Finally, the way personal data are processed has to comply with the GDPR and in particular with the 
general  principles  of  data  protection  as  set  out  in  Article  5:  lawfulness,  fairness,  transparency, 
purpose  limitation,  data  minimisation,  accuracy,  storage  limitation,  integrity,  confidentiality  and 
accountability.  

How were these guidelines developed? 
These guidelines were  developed by the Subgroup on Equality Data. They are  intended to provide 
practical guidance to Member States on how to gradually improve the collection and use of equality 
data,  with  a  view  to  assist  them  in  monitoring  the  implementation  of  relevant  legislation,  policies 
and measures they devise to that effect.  

The guidelines were finalised on the basis of systematic exchanges of practices and discussions held 
in the framework of both the High Level Group and the subgroup, including on how to address the 
gaps  and  shortcomings  identified  in  current  national  practices.  The  guidelines  further  build  on 
recommendations from the updated European Handbook on Equality Data.16 These include utilising 
multiple  sources  of  equality  data,  promoting  coherent  definitions  and  statistical  categories, 
improving the validity and reliability of existing data collection exercises, and ensuring that sufficient 
funding is available for equality data collection. 

They are divided into two groups: 

A. 

Institutional and structural guidelines provide guidance to Member States in setting up 
structures  that  enable  a  systematic,  long-term  and  cooperative  approach  to  collection 
and  use  of  equality  data;  they  mainly  target  policy-makers  and  public  administrations 
that have both a mandate and the potential to trigger change at institutional level.   

16   European Commission (2016), European Handbook on Equality Data – 2016 Revision. 

12 

 
 
 
 
 
 
 
                                                           
B. 

in  ensuring 
Operational  guidelines  provide  guidance 
comprehensiveness,  timeliness,  validity,  reliability  and  representativeness  of  equality 
data  and  in  enhancing  their  comparability;  they  target  in  particular  institutions/actors 
engaged in the collection, analysis and dissemination of equality data, such as national 
statistical  offices,  ministries  or  other  national  or  local  administrative  bodies,  research 
institutes, equality bodies and civil society organisations. 

to  Member  States 

All  institutional/structural  and  operational  guidelines  are  interconnected,  they  build  upon  one 
another, and in many ways complement and reinforce each other. The guidelines should be read and 
applied  as  a  whole.  Yet,  as  the  discussions  within  the  High  Level  Group  and  the  subgroup  have 
shown,  the  situation  concerning  the  scope  and  quality  of  collected  equality  data  varies  across 
Member States. Therefore, policy makers and other stakeholders may also choose or prioritise those 
actions  set  out  in  the  guidelines  which  best  fit  the  needs  identified  at  that  time  in  the  relevant 
Member State. It is possible to start by applying selected elements of the guidelines and then, with 
the  aim  of  building  up  a  comprehensive  system  of  high  quality  equality  data,  expand  by 
implementing further elements. In this sense, the implementation of these guidelines is seen as an 
ongoing process and the extent to which they are applied a matter of degree.  

EU  Member  States  are  encouraged  to  use  these  guidelines  to  inform  the  development  of  policies 
and the evaluation of their outcomes from an equality perspective. 

Section II: Guidelines on improving the collection and use of equality 
data 

A.  Institutional and structural guidelines 
1.  Map existing sources of equality data and identify data gaps 

A  national  mapping  exercise  should  be  conducted  to  identify  existing  sources  of  equality  data  in 
Member  States,  avoid  duplication  of  data  collection  efforts  and  establish  a  baseline  for  a  more 
systematic approach towards equality data collection.17 

Such  an  initiative  could  be  facilitated  or  coordinated  by  a  relevant  ministry  or  governmental 
department.  Alternatively,  a  specific  mandate  and  dedicated  resources  could  be  provided  to  the 
national statistical office, an equality body or a research institute to carry out such a mapping.  

In the first instance, the mapping should help Member States to: 

- 

- 
- 
- 

identify  the  different  sources  and  providers  of  equality  data,  taking  also  into  account 
data  sources  that  are  not  specifically  designed  to  gather  equality  data,  but  include 
variables that can be used to show and analyse existing inequalities;  
identify for which grounds of discrimination data are collected; 
take account of intersections between grounds of discrimination; 
identify for which areas of life data are collected (for example, (access to) employment, 
(access  to)  housing,  education,  health,  access  to  justice,  access  to  goods  and  services, 
etc.); 

17   For  an  overview  of  Member  States’  practices  in  this  regard,  see  European  Commission  (2017),  Legal 
framework  and  practice  in  the  EU  Member  States,  Analysis  and  comparative  review  of  equality  data 
collection practices in the European Union. 

13 

 
 
 
 
 
 
 
                                                           
- 

- 

- 

establish with which frequency and based on which definitions and categorisations data 
are collected; 
collect,  where  available,  information  on  sample  size,  representativeness  (including 
whether some groups are systematically under-represented or excluded), identification 
of  target  groups  via  self-identification  or  by  other  means,  mode  of  data  collection, 
geographical coverage, frequency of updates and existing time series (if any); 
include  reference  or  links  to  existing  outputs  of  the  data  sources,  such  as  reports  or 
latest publications, data visualisations, web pages and other relevant meta data. 

In the second instance, the mapping should serve to identify the needs for equality data  in Member 
States. The performance of such a needs assessment should be based on relevant EU, international 
and  national  normative  standards  to  which  Member  States  are  bound  such  as  the  Charter  of 
Fundamental  Rights  of  the  EU,  the  EU  equality  legislation,  international  human  rights  law  and 
national  legislation.  The  needs  assessment  should  also  respond  to  EU-level  policy  coordination 
processes such as the European Semester, as well as to relevant political commitments, including the 
European  Pillar  of  Social  Rights  or  the  UN  Agenda  for  Sustainable  Development.  As  a  whole,  the 
needs  assessment  should  serve  to  identify  what  type  of  equality  data  Member  States  require  for 
evidence-based policy making.  

Possible outcomes of the mapping would consist of: 

- 

- 
- 
- 

a comprehensive and systematic description of all available sources of equality data in a 
Member State; 
identification of all providers of equality data; 
an equality data needs assessment; 
suggestions  or  recommendations  for  possible  ways  or  instruments  to  address  the 
identified gaps or shortcomings in equality data collection. 

Taken together, these outcomes would allow for the identification of existing data gaps, and bring to 
light areas where improvements are needed. 

The mapping of equality data could be designed so that it is carried out periodically, dependent on 
the  regular  updates  of  the  mapped  data  sources,  for  example,  every  five  years,  taking  into 
consideration new potential data sources and providers. 

2.  Foster inter-institutional cooperation in the collection and use of equality data  

An  inter-institutional  working  group  should  be  established  to  ensure  coordination  and  monitor 
progress  in  addressing  the  gaps  and  shortcomings  identified  through  the  mapping  exercise.  The 
activities of the working group could be laid down in a multiannual action plan or roadmap, with an 
appropriate  budget  and  clearly  defined  priorities  and  allocation  of  tasks.  This  would  contribute  to 
attaining timely and fit-for-purpose data, relevant to the needs identified, and increase efficiency. 

The  working  group  should  be  composed  of  relevant  public  institutions  with  competencies  (and, 
where  relevant,  a  mandate)  in  the  field  of  equality  data  collection.  This  could  include  ministries, 
national  statistical  offices, equality  bodies,  national  human  rights  institutions,  research  institutions 
and  the  scientific  community,  as  well  as  other  relevant  actors  and  data  providers  such  as 
representatives of relevant  local authorities, the  judiciary, the  police, etc. One organisation should 
be mandated to coordinate  the working group and follow  up on its decisions. However, improving 
the  collection  and  use  of  equality  data  is  a  collective  endeavour  and  should  be  based  on  joint 
ownership and shared responsibilities. At its best, inter-institutional cooperation is a mutual learning 
process  that  gradually  builds  up  capacity,  expertise  and  trust  among  different  stakeholders,  and 
fosters an increasing awareness of the need for equality data. 

14 

 
 
 
 
 
 
 
 
The  work  of  the  inter-institutional  working  group  should  be  complemented  through  regular 
consultations  with  data  collectors  and  data  users  who  are  not  represented  in  the  working  group. 
These include representatives from other relevant national and local authorities, statisticians, survey 
research  experts  and  academics,  as  well  as  community  and  civil  society  organisations.  The 
involvement  of  these  organisations  would  ensure  that  the  perspective  of  those  most  at  risk  of 
experiencing unequal treatment and discrimination is duly taken into consideration.18 

Such  regular  consultations  would  enhance  transparency,  help  build  up  trust  in  equality  data 
collection initiatives and ensure that relevant expertise feeds into the activities of the working group. 
Overall, regular consultations with relevant stakeholders would ensure that the priorities set out in 
the  action  plan  or  roadmap  respond  to  the  most  important  needs  for  equality  data  in  Member 
States.  

3.  Set up a data hub on equality and non-discrimination 

A national data hub on equality and non-discrimination should be set up to collate and display the 
data  and  related  information  identified  in  the  mapping  exercise  and,  thereby,  enhance  the 
accessibility and use of equality data by different stakeholders. The inter-institutional working group 
could be tasked with setting up the data hub, for example, in the form of a dedicated webpage and 
coordinating its  further development. The hub could be  hosted by the institution coordinating the 
inter-institutional working group or another suitable institution with the capacity to guarantee the 
continuity and periodic update of the hub.  

In  the  first  instance,  the  data  hub  would  provide  an  overview  of  existing  sources of  equality  data, 
referencing  where  the  information  can  be  accessed.  The  hub  would  further  include  available 
publications  and  the  presentation  of  existing  indicators  that  relate  to  different  population  groups, 
grounds  of  discrimination  and  areas  of  life,  as  well  as  technical  information  on  the  different  data, 
including:  

source; 
responsible institution; 
type of data (administrative data, complaints data, survey data, etc.); 

- 
- 
- 
-  population group; 
-  definitions and systems of categorisation applied; 
- 
- 
-  mode of data collection (face-to-face, online, telephone, mixed mode etc.); 
- 
-  periodicity of data collection; 
- 
- 

ground(s) of discrimination/protected characteristics; 
areas of life/domains covered; 

geographical coverage and granularity; 
representativeness. 

sampling frame and sampling method (where applicable); 

To facilitate the proper understanding and interpretation of the equality data gathered in the data 
hub and the establishment of meaningful comparisons, the data hub should include, where possible, 

18   As stated in the guidance note to data collection and disaggregation prepared by the Office of the UN High 
Commissioner for Human Rights (2018), A Human Rights-based Approach to Data - Leaving No One Behind 
in  the  2030  Agenda  for  Sustainable  Development,  participation  is  central  to  a  human  rights-based 
approach.  Therefore,  “all  data  collection  exercises  should  include  means  for  free,  active  and  meaningful 
participation of relevant stakeholders, in particular the most marginalized population groups. Participation 
should  be  considered  in  relation  to  the  entire  data  collection  process:  from  strategic  planning  through 
identification of data  needs;  selecting and testing an appropriate collection methodology, data  collection 
(for  instance,  hiring  interviewers  from  particular  communities  to  improve  response  rates);  and  to  data 
storage, dissemination, analysis and interpretation”. 

15 

 
 
 
 
 
 
 
                                                           
information  notes  for  users,  synthesizing  the  basic  facts  about  the  data  on  display.19  These 
information notes should also make clear when comparisons between data cannot be drawn due to 
differences in definitions or other factors. 

In  the  second  instance,  the  data  hub  should  be  further  developed  and  refined,  following,  for 
example,  the  implementation  of  measures  foreseen  under  the  action  plan  to  address  gaps  and 
shortcomings  in  equality  data  collection.  Furthermore,  (new)  rights-based  indicators  relevant  to 
monitoring  equality  in  outcomes  and  non-discrimination  could  be  added  to  the  data  hub.  Such 
indicators  could  be  jointly  developed  to  this  end  at  the  initiative  of  the  inter-institutional  working 
group.  

4.  Build institutional capacity to collect robust and reliable equality data  

The capacity of relevant stakeholders to collect reliable and robust equality data should be enhanced 
to effectively address the areas for improvement identified by the inter-institutional working group. 
This  would  also require  providing  adequate  funding  to  those  bodies  and  organisations that  collect 
equality  data,  which  includes  national  statistical  offices  and  research  institutes  carrying  out  large 
scale surveys, as well as equality bodies, other public institutions and civil society organisations that 
carry  out  targeted  surveys  on  discrimination  experiences,  conduct  discrimination  testing 
experiments or collect complaints data. 

In  addition,  it  is  also  important  to  ensure  that  the  staff  from  different  stakeholders  regularly 
engaging  in  equality  data  collection  have  the  relevant  skills,  expertise  and  awareness  of  best 
practice, including the use of harmonised definitions, to adequately design the collection of equality 
data and to comply with safeguards set out in the relevant legislation and UN principles of human 
rights-based approaches to data collection and analysis. This is, for example, the case of employers 
and service providers who collect data to assess their compliance with specific equality duties set out 
in  legislation,  or  of  civil  society  organisations  working  with  groups  at  risk  of  discrimination. 
Therefore, tailored training should be developed, drawing on the expertise of different stakeholders 
and  covering  the  range  of  activities  relevant  to  equality  data  collection,  i.e.  design,  collection, 
processing,  analysis,  use  and  dissemination  as  well  as  the  provisions  of  the  data  protection 
legislation  governing  all  steps  of  the  life  cycle  of  personal  data.  More  generally,  inter-institutional 
cooperation,  as  foreseen  under  Guideline  2,  is  enhanced  when  representatives  of  the  different 
institutions engaging in equality data collection have the necessary statistical literacy and knowledge 
about equality issues and share a common language.  

Overall,  an  institutional  culture  acknowledging  the  need  for  robust  and  reliable  equality  data  to 
ensure evidence-based policy making should be promoted across public institutions and all relevant 
stakeholders.  

5.  Facilitate effective use of equality data  

To  facilitate  its  effective  use,  equality  data  should  be  disseminated  as  quickly  as  possible  after 
collection and be presented in an accessible language and format, taking into consideration that it 
should be understandable to the greater public.20 

19   This  would  be  in  line  with  Principle  15,  on  ‘Accessibility  and  Clarity’,  of  the  European  Statistics  Code  of 
Practice-revised  edition  2017,  adopted  on  16  November  2017  by  the  European  Statistical  System 
Committee. 

20   In line with the recommendations under the ‘Transparency’ section of the Guidance note to data collection 
and  disaggregation,  Office  of  the  United  Nations  High  Commissioner  for  Human  Rights  (2018),  A  Human 
Rights-based Approach to Data - Leaving No One Behind in the 2030 Agenda for Sustainable Development, 
p. 15. 

16 

 
 
 
 
 
 
 
 
                                                           
The  inter-institutional  working  group  could  promote  an  enhanced  use  of  equality  data  by 
contributing  to  the  dissemination  of  the  data  collected  and  by  providing  explanations  and 
interpretations  where  appropriate.  It  could  also  issue  policy  briefs  that  present  outcomes  from 
recent  surveys  or  research  and  provide  easy-to-use  equality  data  for  policy  makers,  experts  and 
media related to the relevant policy. These policy briefs could also be used for awareness raising and 
advocacy.  

The information displayed in the data hub foreseen under Guideline 3 could be used to inform public 
debate  on  equality  and  non-discrimination.  An  enhanced  use  of  equality  data  to  discuss  and  to 
justify  legislative  and  policy  measures  would  also,  as  a  by-product,  strengthen  public  support  for 
investing in the collection of robust and reliable equality data by showing its utility.  

Ultimately, equality data should feed into the policy cycle to enhance evidence-based policy making 
in all relevant policy areas, across different discrimination grounds and areas of life. Here, the term 
‘policy cycle’ is meant to include public debate, the initial design of measures and policies and the 
evaluation of their impact. Effectively incorporating equality data in the policy cycle will depend on 
three  inter-related  factors:  (1)  a  will  to  develop  evidence-based  policy  making;  (2)  the  timely 
availability of equality data for policy makers; and (3) the accessibility of equality data for the media 
and the general public.  

17 

 
 
 
 
 
 
 
B.  Operational guidelines 
6.  Ensure comprehensiveness of equality data  

Data collectors and data users need multiple and complementary sources of equality data to enable 
evidence-based  policy  making,  as  well  as  to  get  a  full  picture  of  the  reality  of  equality  and  non-
discrimination on the ground. In addition, an adequate impact assessment of policies in the field of 
equality  and  non-discrimination  requires  a  regular  data  collection  on  all  grounds  of  discrimination 
and  for  all  areas  of  life  covered  by  the  relevant  legislation.  To  ensure  the  comprehensiveness  of 
equality data, Member States should: 

-  use a broad set of equality data sources; this would include combining and linking different 
sources  of  data,  such  as  large  scale  surveys,  attitudinal  surveys,  victimisation  surveys, 
discrimination  testing,  administrative  data,  complaints  data  (and  their  outcomes),  robust 
and  reliable  data  from  civil  society  organisations,  data  collected  by  employers  and  service 
providers and other quantitative and qualitative research; 
ensure that the full range of key areas of life where discrimination can occur is captured by 
equality  data  sources;  these  areas  of  life  include  employment,  education,  access  to  goods 
and services, housing, health, poverty/social exclusion, political and civic participation, etc.; 
-  use  existing  data  to  their  full  potential,  including  data  collected  for  purposes  other  than 

- 

- 

equality and non-discrimination policies; 
establish  or  further  develop  an  efficient  system  for  collating  and  regularly  publishing 
statistical  data  on  reported  cases  of  discrimination  and  their  administrative  or  judicial 
outcomes;21 

-  mainstream  multiple  and  intersectional  discrimination  in  data  collection  and  analysis;  for 
example,  data  collected  in  the  area  of  disability  should  ideally  include  information  on 
gender,  ethnic or  racial origin,  age  and other  potential  characteristics  that might  lead to  a 
higher  risk  of  discrimination  based  on  multiple  factors  (this  type  of  analysis  generally 
requires larger sample sizes for robust analysis, and a range of different data sources could 
be considered including large surveys, administrative and linked data); 
foster where possible data linkage between different data sources; 
increase the amount of regional equality data, geo-referenced to the smallest possible grid. 

- 
- 

7.  Mainstream equality data into EU and national surveys  

Large-scale  surveys  are  a  powerful  tool,  which  enables  the  collection  of  a  comprehensive  set  of 
equality data. When developing such surveys or when collecting data within the  framework of  the 
European Statistical System (ESS) through the Labour Force Survey (LFS), the EU Statistics on Living 
Conditions (EU-SILC), or through other EU-wide surveys such as Eurobarometer and the FRA surveys, 
Member States should, where relevant, systematically incorporate information referring to equality 
and non-discrimination through, among others:  

21   This  could  be  linked  to  the  implementation  of  the  Recommendation  on  standards  for  equality  bodies 
adopted by the European Commission in June 2018 to set out measures that Member States may apply to 
improve  the  equality  bodies’  independence  and  effectiveness.  See  European  Commission  (2018), 
Commission  Recommendation  of  22  June  2018  on  standards  for  equality  bodies,  C(2018)  3850  final.  In 
particular,  its  recommended  measure  No.  9,  on  independent  reports,  states  that  “for  the  purpose  of 
obtaining  independent  reports  of  high  quality,  Member  States  should  enable  equality  bodies  to  conduct 
independent  research.  This  could  include  collecting  data  in  particular  on  the  number  of  complaints  per 
discrimination ground; the duration of administrative proceedings from submission of the complaint to the 
closure of the case; the outcome of administrative proceedings; and the number, duration and outcome of 
judicial cases in which the equality bodies are involved”. 

18 

 
 
 
 
                                                           
 
- 

introducing  individual  variables  and  survey  questions  that  specifically  relate  to  measuring 
inequalities and perceived discrimination on a number of grounds; 

-  developing and running additional thematic survey modules on a regular basis to cover the 
range  of  issues  of  relevance  to  equality  and  non-discrimination  (for  example,  rights 
awareness,  rates  of  reporting  experiences  of  discrimination,  experiences  of  victimisation, 
etc.); 

-  disaggregating  the  collected  data  as  much  as,  and  where  possible,  on  the  basis  of  age, 
gender,  ethnic  or  racial  origin,  religion,  migration  background,  sexual  orientation  and 
disability; 
increasing the number of people who otherwise wouldn’t be adequately represented in the 
survey samples due to small numbers in general population (booster samples); 

- 

- 

- 

-  undertaking  efforts  to  develop,  test  and  apply  precise  and  sensitive  categories  for 
identification of persons with a high risk of discrimination (for example, variables for racial or 
ethnic origin, sexual orientation or gender identity); 
increasing  the  number  of  proxy  variables/categories  in  existing  data  sources  where  the 
human rights-based principle of self-identification cannot not be applied; 
increasing the number of variables measuring perceived discrimination on different grounds 
and in different areas of life; 
supporting  the  development  and  implementation  of  innovative  survey  methodologies  that 
can  capture  highly  dispersed  or  hard-to-reach  population  groups  or  persons  at  risk  of 
discrimination; 
identifying geographical areas where inequalities are more often observed and where data 
should be collected on regular basis to allow monitoring of trends over time.  

- 

- 

8.  Ensure regular and timely equality data collection 

Equality data should be collected, analysed and reported on on a regular basis. The data therefore 
need to be made available for the intended use within a reasonable time frame and with a regular 
frequency, if they are to meet information needs and feed into the policy cycle.  

To ensure regular and timely equality data collection, Members States should: 

- 

- 

systematically and on a regular basis, collect data on all grounds of discrimination and for all 
areas  of  life/domains  covered  by  equality  and  non-discrimination  legislation  (for  example, 
every three to five years); 
systematically  and  on  a  regular  basis,  update  the  data  hub  on  equality  and  non-
discrimination; 

-  promote the inclusion of equality data in longitudinal surveys, i.e panels, to monitor impact 

on individuals; 
systematically identify and monitor trends when collecting equality data; 

- 
-  use  information  from  existing  equality  data  sources  available  at  regular  intervals  to  avoid 
costly duplications, particularly when no targeted data collection exercises are taking place; 
-  develop a methodological guidance for the systematic collection of equality data over time, 

to be used by the different data collectors. 

9.  Enhance validity and reliability of equality data 

Validity  and  reliability  need  to  be  built  in  the  design  of  any  equality  data  collection  exercise. 
Validity22 relates to the correct measurement of a variable of interest, which is itself observable in 

22   An  indicator,  a  test,  a  survey  question  or  a  system  of  categorisations  used  to  classify  person’s 
characteristics  in  administrative  or  in  other  data  sources  is  valid:  (1)  if  it  correctly  measures  what  it  is 
supposed  to  measure,  and  (2)  if  it  renders  phenomena  or  characteristics  that  are  directly  observable  or 
have at least been perceived to exist in the ‘real world’. Validity is for example linked to the extent to which 

19 

 
 
 
 
                                                           
the ‘real world’. Reliability23 relates to the stability or consistency of the measurement applied to the 
variable.  

To enhance the validity and reliability of equality data, Member States should:  

- 

- 

- 

- 

- 

apply  the  human  rights-based  principles  of  participation,  self-identification,  transparency, 
privacy  and  accountability  in  the  design,  collection  and  use  of  equality  data  to  retain  or 
boost the trust of relevant stakeholders;24  
apply a participatory approach to the data collection design and process, for example, when 
developing definitions, systems of classification or categorisation, or when making decisions 
on  the  use  of  proxies;  such  an  approach  could  include  hiring  interviewers  or  mediators 
drawn from particular population groups to increase response rates; 
carry out  community  consultations with representatives of the targeted population groups 
with a view to reaching a consensus on the definitions and categories to be used in equality 
data collection; 
encourage cooperation with the targeted population groups and stakeholders by informing 
them that data are collected and used to support programmes designed to promote equal 
opportunities or fight discrimination, with a view to ensuring a higher response rate; 
improve response rates by adapting and redrafting (ambiguous) questions/categories where 
necessary; this could be based on insights from the community consultations; 

- 

-  where  possible,  enable  self-identification  by  individuals  who  are  the  subject  of  data 
collection on the basis of characteristics such as racial and ethnic origin, religion, disability, 
sexual  orientation  or  gender  identity;  such  categorisation  systems  should  allow  for  the 
selection  of  more  than  one  identification  category,  as  well  as  allow  respondents  not  to 
declare or declare ‘none’; 
refine and/or increase the number of proxies applied to ensure comprehensive coverage of 
different population groups for which direct (self-) identification is not possible; 
thoroughly test any categories, variables and questions developed for data collection;  
ensure the use of consistent procedures and definitions over time; 
apply  the  ESS  statistical  code  of  practice25  and  the  quality  reports  produced  by  the  data 
producers where relevant; 

- 
- 
- 

-  where relevant, apply the following general quality criteria to available indicators and those 
to  be  developed  in  the  future:  consistency,  clarity,  timeliness,  punctuality,  accuracy, 
continuity, objectivity, relevance, comparability and transparency; 

-  develop  a  protocol  summarising  explanations  for  continuing  differences  in  definitions  and 
categorisations  across  different  data  sources  in  cases  where  no  development  of  new  or 

respondents misinterpret survey questions or response categories and to the extent that they deliberately 
do not reveal the truth (often the case when the personal information asked is perceived as sensitive). A 
lack of validity can also be observed if, for example, the extent of discrimination is only measured through 
the  number  of  incidents  reported  to  the  competent  bodies  as  there  might  be  a  high  number  of  non-
reporting. There are no perfectly valid measures, but some measures are more valid than others. 

23   Reliability implies stability or consistency of the measurement/test applied. A measure of discrimination for 
example  is  reliable  to  the  extent  to  which  the  measuring  procedure  yields  the  same  results  in  repeated 
trials.  For  example,  if  we  measure  the  number  of  reported  incidents  per  year,  but  the  number  of 
competent  (equality)  bodies  changes  over  time,  this  will  have  a  negative  effect  on  the  reliability  of  this 
measure and will also impact on its comparability over time. No measure is absolutely reliable; reliability is 
therefore always a  matter of degree. There is a direct relation between validity and reliability in the way 
that tests that are valid are also reliable (repeatable). Tests that are reliable, however, are not always valid. 
24   See  Office  of  the  United  Nations  High  Commissioner  for  Human  Rights  (2018),  A  Human  Rights-based 
Approach  to  Data  -  Leaving  No  One  Behind  in  the  2030  Agenda  for  Sustainable  Development,  Guidance 
note to data collection and disaggregation, 2018.  

25   European Statistical System Committee (2017), European Statistics Code of Practice - revised edition 2017. 

20 

 
 
 
                                                                                                                                                                                     
adaptation  of  existing  categories  is  possible  (for  example,  when  the  main  objective  of 
existing data collection is the monitoring of trends). 

10.  Ensure representativeness of equality data 

Representativeness shows the extent to which characteristics of a sample, such as composition along 
gender, age, ethnic and racial origin, etc., correspond to the characteristics of the population from 
which it has been taken, in accordance with established rules. The term ‘representativeness’ is often 
used to indicate that a sample mirrors a population group, reflecting all its essential properties in a 
correct way.  

Representativeness  can  be  negatively  affected  if  the  sample  size  is  too  small,  when  it  does  not 
include  a  sufficient  number  of  persons  belonging  to  a  targeted  population  group,  or  if  specific 
subgroups  of  the  population  are  systematically  excluded  from  data  collection  in  the  first  place 
(because  of  language  difficulties,  impairments  etc.).  These  challenges  apply  for  many  different 
surveys and are especially problematic when it  comes to the collection of equality data, as groups 
with a high risk of discrimination are disregarded and cannot be considered while analysing the data. 
Representativeness can also be affected if the sample is large enough, but biased, for example, when 
those persons belonging to a target population who experience more discrimination are less or more 
inclined  to  take  part  in  a  survey.  To  address  such  difficulties,  Member  States  should  apply  an 
inclusive data collection approach, undertaking efforts to: 

- 

- 
- 

- 

- 

- 

reach  out  to  under-represented  groups  and  achieve  robust  samples  and  effective  sample 
sizes to the extent possible; 
conduct targeted surveys;  
include  members  of  minority  groups  and  hard-to-reach  groups  in  existing  surveys,  such  as 
LFS and EU-SILC, through boosting samples where relevant; 
include persons living in institutional settings such as care homes, prisons, asylum reception 
centres, nomadic people, homeless people and  people living in temporary accommodation 
in equality data collection, where possible; 
foster qualitative and mixed-methods research especially when target groups are too small 
or highly dispersed; 
ensure  effective  insights  into  a  full  range  of  protected  characteristics  or  groups  at  risk  of 
discrimination  who  might  be  left  out  from  existing  sampling  frames  through  conducting 
qualitative  research;  qualitative  methods  can  be  used  throughout  the  research  process  to 
complement statistical insights and to enhance representativeness and validity. 

11. Improve comparability of equality data  

Comparability is defined as the extent to which differences between findings, statistics or outcomes 
from different equality data sources, countries, regions, cultures, life domains or time periods can be 
attributable to differences in target population’s true values. Comparability is strongly affected when 
concepts,  definitions  or  categories  of  study  design  vary  across  data  sources,  points  in  time  or 
countries. Improving comparability implies that error due to sample or questionnaire design, mode 
of  data  collection,  translation  etc.  is  minimised.  To  help  determine  comparability,  the  decisions 
involving the design, definitions and categories to be applied should be well-documented. 

To improve comparability of equality data, Member States should: 

- 

identify  differences  in  definitions,  systems  of  classification  and  categorisation  across 
different  data  sources  and  across  time;  this  could  be  done  through  the  mapping  exercise 

21 

 
 
 
 
 
(Guideline  No.  1)  and  during  the  consultation  processes  with  relevant  stakeholders 
(Guidelines No. 2 and 9); 
to the extent possible, harmonise definitions, categorisations and the data collection design; 

- 
-  develop and issue guidance for a harmonised administration of data collection; 
-  where comparability cannot be achieved (for example, when data are gathered for different 
purposes), develop and issue guidance for the interpretation of existing differences between 
data  sources,  languages  or  time  points  regarding  definitions,  design  and  systems  of 
classification  and  categorisation;  this  guidance  should  make  clear  that  while  results  might 
differ  due  to  lack  of  comparability,  they  are  still  valuable  and  feed  into  the  overall 
assessment of the state of equality and non-discrimination in a country; 

-  where  relevant,  make  efforts  to  improve  comparability  of  equality  data  on  the  EU  level, 
namely  of  the  comparability  of  data  collected  through  the  standard  EU  data  collection 
systems (comparative-by-design); 

-  where  relevant,  and  to  the  extent  possible,  improve  comparability  of  equality  data  with 
regard  to  available  OECD,  UN  and  World  Bank  data  in  the  area  of  equality  and  non-
discrimination;  in  this  regard,  Member  States  could  make  efforts  to  utilise  existing 
national/local equality data for comparative purposes by using rights-based indicators as the 
basis for comparison;  

-  promote exchange of information among countries relating to good practices to enhance the 

comparability and compatibility of equality data at national level. 

22 

 
 
 
 
 
 
GETTING IN TOUCH WITH THE EU 

In person 

All over the European Union there are hundreds of Europe Direct information centres. You can find 
the address of the centre nearest you at: https://europa.eu/european-union/contact_en 

On the phone or by email 

Europe Direct is a service that answers your questions about the European Union. You can contact 
this service: 

– by freephone: 00 800 6 7 8 9 10 11 (certain operators may charge for these calls), 

– at the following standard number: +32 22999696, or  

– by email via: https://europa.eu/european-union/contact_en 

FINDING INFORMATION ABOUT THE EU 

Online 

Information about the European Union in all the official languages of the EU is available on the Europa 
website at: https://europa.eu/european-union/index_en 

EU publications  

You can download or order free and priced EU publications from: https://op.europa.eu/en/publications. 
Multiple copies of free publications may be obtained by contacting Europe Direct or your local 
information centre (see https://europa.eu/european-union/contact_en). 

EU law and related documents 

For access to legal information from the EU, including all EU law since 1952 in all the official language 
versions, go to EUR-Lex at: http://eur-lex.europa.eu 

Open data from the EU 

The EU Open Data Portal (http://data.europa.eu/euodp/en) provides access to datasets from the EU. 
Data can be downloaded and reused for free, for both commercial and non-commercial purposes. 

23