Page 82 - Special Topic Session (STS) - Volume 2
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STS461 Maciej T.
                  5.  Annex: Other aspects of work on the follow up on the Global Goals
                      Disaggregation of data. In the context of the SDGs, disaggregation of
                  data can have many dimensions. Due to the wide use of administrative data in
                  Danish statistical production, disaggregation by sex, age, income, education
                  etc. does not pose difficulties. Disaggregation by religion on the other hand is
                  more challenging, as it is not legal to ask persons about their religious beliefs.
                  Disaggregation by people with disabilities is also a challenging aspect as data
                  availability is limited and only in few cases we can achieve a fragmentary follow
                  up on the global goals. Finally, geographical disaggregation. Here again, with
                  data based on administrative registers, the challenges, at least relating to the
                  social  statistics,  aren’t  substantial.  However,  due  the  size  of  population  in
                  Denmark, many of the indicators cannot be disaggregated by geographical
                  levels, as this would interfere with statistical confidentiality.
                      Data from non-official sources – this is a heavily discussed topic in the
                  statistical community. The first issue to be addressed in this context is what
                  types of data we talk about. Generally, it could be dis-cussed whether it is data
                  showing a ‘section’ of a bigger picture, such as Big Data, but also data from
                  civil  society  could  fall  under  this  term.  There  is  willingness  from  Statistics
                  Denmark to receive and publish data from civil society, and there is willingness
                  from civil society to deliver data. However, in the Danish case, data provided
                  by civil society seldom fully corresponds to the requirements to the indicators
                  and in consequence the indicator is only partially covered. The challenge is
                  then not only to explain the figures that are not fully covering the indicator
                  but  also  to  complement  them  with  additional  data.  Which  again  poses  a
                  question of comparability of data covering the indicator.
                      Coordinating  data  streams  from  the  national  statistical  system  –
                  Statistics Denmark is coordinating national reporting on the global goals. Due
                  to its complexity, the reporting is a challenging task. Firstly, the complex nature
                  of many questionnaires makes it difficult to find relevant contributors. This
                  implies  a  time  consuming  follow  up  with  various  governmental  agencies.
                  Furthermore, the coordination easily gets multi-layered – first a questionnaire
                  comes in, then it is considered in Statistics Denmark, then it gets sent to a
                  presumably right ministry. A frequent reply from the ministries is that it is not
                  the right one or that it can only answer parts of the questionnaire. In such
                  cases,  the  work  starts  from  the  beginning  and  the  questionnaire  can  be
                  repeatedly circulated among ministries, which requires some goodwill from
                  the  involved  staff.  From  the  NSO  side,  the  challenge  is  to  balance  the
                  perceivably  ‘over  dimensioned’  questionnaires  with  the  integrity  of  the
                  coordination process.
                      Finally, compilation of national indicators for the national follow up
                  on  the  SDG.  In  this  case,  Statistics  Denmark  will  coordinate  a  project  on
                  selection  of  national  indicators.  The  first  step  will  be  a  ‘nationwide’

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