Reference metadata describe statistical concepts and methodologies used for the collection and generation of data. They provide information on data quality and, since they are strongly content-oriented, assist users in interpreting the data. Reference metadata, unlike structural metadata, can be decoupled from the data.
Classification and coding systems have been developed for the spatial units and for the variables and indicators of the Subnational statistics project.
Classification system for the spatial units
The city code consists of a 2-digit country code, a 3-digit city code and final C for Central City - for FUA.
Classification system for the UA variables
A variable is the raw data collected by the national statistical offices of the countries. The variable data serves as the raw data for the calculation of the indicators. The variables serve as either the numerator or denominator of the indicator equation, depending on how this has been defined.
3.3. Coverage - sector
The indicators and variables cover several aspects of quality of life in selected cities:
- Demography
- Nationality
- Household structure
- Housing
- Crime
- Labour market
- Economic activity
- Education and training provision
- Educational qualifications
- Culture and recreation
3.4. Statistical concepts and definitions
For most indicators exisitng international standards have been followed as far as possible.
At Croatian Bureau of Statistics the compilation of the indicators has been based on the concepts and definitions described in the Urban Audit Methodology - wherever possible.
3.5. Statistical unit
In this grant data are collected for cities and functional urban areas.
3.6. Statistical population
There are seven cities from Croatia participating in this grant: Zagreb, Split, Rijeka, Pula, Zadar, Osijek and Slavonski Brod.
3.7. Reference area
Spatial units included in this grant are listed in the annex of the City Statistics manual:
All data supply of urban statistics is based on grant agreement.
6.2. Institutional Mandate - data sharing
Not applicable.
7.1. Confidentiality - policy
Regulation (EC) No 223/2009 on European statistics (recital 24 and Article 20(4)) of 11 March 2009 (OJ L 87, p. 164), stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society.
7.2. Confidentiality - data treatment
Not applicable.
8.1. Release calendar
There is a release calendar for the statistical output. This calendar is publicly accessible.
The definitions from the City statistics manual have been followed.
10.7. Quality management - documentation
The quality assurance procedures detailed in the City statisitcs manual have been applied.
11.1. Quality assurance
The quality management framework of the field of statisitcs is the European Statistics Code of Practice (CoP).
The quality criteria of Croatian Bureau of Statictics are compatible with the European Statistics Code of Practice. The principles of the European Foundation for Quality Management (EFQM principles) are employed by Croatian Bureau of Statistics.
11.2. Quality management - assessment
The quality of data from Croatian Bureau of Statistics is good.
12.1. Relevance - User Needs
Not available.
12.2. Relevance - User Satisfaction
Not available.
12.3. Completeness
For some variables no data are available for the levels included in City statistics manual.
13.1. Accuracy - overall
Not applicable.
13.2. Sampling error
Not applicable.
13.3. Non-sampling error
Not applicable.
14.1. Timeliness
Timeliness depends on individual indicator and on domain. Generally timeliness is about 24 months.
14.2. Punctuality
There was no time lag between the actual delivery of the data and the delivery target date.
All requested available data has been delivered to Eurostat.
15.1. Comparability - geographical
The approach of collecting data from existing sources makes it difficult and sometimes impossible to achieve comparability of variables over entire "population". National Urban Data Coordinators did their best to achieve comparability of urban data within their own country.
But the implementation of a fully comparable definitions of cities at European level has improved the comparability.
Due to sometimes deviating definitions and different data sources used in different countries the comparability of data is limited to some extent.
15.2. Comparability - over time
For 5 cities (Zagreb, Rijeka, Osijek, Slavonski Brod, Split) data can be compared for several years back in the past.
For 2 cities (Zadar, Pula) introduced from data collection 2015 - 2016, data can be compared for only few years in the past.
15.3. Coherence - cross domain
Data collected at sub-national level is coherent with the data collected on national level to a limited extent due to the different sources used.
15.4. Coherence - internal
Internal coherence is ensured through validaton controls.
The data collection is based on administrative data so the main burden is on the Statistical Offices.
The compilation of these urban statistics have been coordinated by Croatian Bureau of Statistics where the National Urban Audit Coordinator is located.
17.1. Data revision - policy
The Urban Audit data cover is very extensive, it cannot be excluded that some errors exist.
17.2. Data revision - practice
Detected errors will be corrected by National Coordinator after consultation with Eurostat.
18.1. Source data
Data is collected by Croatian Bureau of Statistics from different sources.
The main sources are:
Data was based on the Census,
Data was collected from registers,
Data was produced by the cities,
Data was estimated.
18.2. Frequency of data collection
The Urban Audit grant collects data on annual basis.
18.3. Data collection
Data have been collected by the National Urban Audit Coordinators in Croatia.
18.4. Data validation
All collected data has been checked by the National Urban Audit Coordinators.
18.5. Data compilation
The National Urban Audit Coordinators from Croatian Bureau of Statistics compile the data.
18.6. Adjustment
Not applicable.
None.
Data description file in annex.
30 April 2024
For most indicators exisitng international standards have been followed as far as possible.
At Croatian Bureau of Statistics the compilation of the indicators has been based on the concepts and definitions described in the Urban Audit Methodology - wherever possible.
In this grant data are collected for cities and functional urban areas.
There are seven cities from Croatia participating in this grant: Zagreb, Split, Rijeka, Pula, Zadar, Osijek and Slavonski Brod.
Spatial units included in this grant are listed in the annex of the City Statistics manual:
The unit of measurement varies from variable to variable and from indicator to indicator.
The National Urban Audit Coordinators from Croatian Bureau of Statistics compile the data.
Data is collected by Croatian Bureau of Statistics from different sources.
The main sources are:
Data was based on the Census,
Data was collected from registers,
Data was produced by the cities,
Data was estimated.
The project database of Eurostat is updated occasionally depending on the data availability of new and revised data.
Timeliness depends on individual indicator and on domain. Generally timeliness is about 24 months.
The approach of collecting data from existing sources makes it difficult and sometimes impossible to achieve comparability of variables over entire "population". National Urban Data Coordinators did their best to achieve comparability of urban data within their own country.
But the implementation of a fully comparable definitions of cities at European level has improved the comparability.
Due to sometimes deviating definitions and different data sources used in different countries the comparability of data is limited to some extent.
For 5 cities (Zagreb, Rijeka, Osijek, Slavonski Brod, Split) data can be compared for several years back in the past.
For 2 cities (Zadar, Pula) introduced from data collection 2015 - 2016, data can be compared for only few years in the past.
