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.
Data collection provides information and comparable measurements on different aspects of the quality of urban life in cities.
3.2. Classification system
A specific classification and coding systems have been developed for spatial units, variables and indicators. For description of the coding system and list of indicators and variables, see the City statistics manual. Statistics Lithuania uses the same spatial units. No delineation of new spatial units has been made.
3.3. Coverage - sector
Indicators and variables cover several aspects of quality of life, e. g. demography, nationality, household structure, housing, health, crime, labour market, economic activity, income disparities and poverty, education and training provision, educational qualifications, waste management, travel and transport, tourism, culture and recreation.
3.4. Statistical concepts and definitions
For most variables, definitions of the City statistics manual and existing international standards have been followed. Information on the deviating definitions used in the data collection is presented in the Annex “Deviating definitions_LT”.
3.5. Statistical unit
Statistical units are mostly persons. A few variables are collected on households, enterprises, dwellings, etc. For a comprehensive description of variables and statistical units, see the City statistics manual.
3.6. Statistical population
For most variables, the target statistical universe was the usual residents of a geographical area (city). For a detailed description of variables, see the City statistics manual.
3.7. Reference area
In Lithuania, data were prepared for the following spatial levels:
City level – data of six Lithuanian cities (Vilnius, Kaunas, Klaipėda, Panevėžys, Šiauliai, and Alytus);
Functional Urban Area level (FUA) – data of three Lithuanian cities (Vilnius, Kaunas, and Panevėžys).
3.8. Coverage - Time
Data collection is organised in data collection rounds. The current data collection on city statistics covers the reference years 2023.
3.9. Base period
Not applicable.
The unit of measurement varies from indicator to indicator and from variable. In most cases, the unit of measurement is included in the label.
2014, 2011, 2008, 2004 and 2001 are the reference years for the main data collection. 1996 and 1991 are the reference years for the “historical” data collection. A set of variables has been collected on an annual basis for the periods 2005–2012, 2015-2016, 2017-2018, 2019-2020, 2021-2022. The reference year for the current data collection exercise are 2023.
6.1. Institutional Mandate - legal acts and other agreements
All data supply for urban statistics is based on a voluntary agreement as there is no Community legislation on this topic yet.
6.2. Institutional Mandate - data sharing
Not applicable.
7.1. Confidentiality - policy
In the process of statistical data collection, processing and analysis and dissemination of statistical information, the State Data Agency fully guarantees confidentiality of the data submitted by respondents (households, enterprises, institutions, organisations and other statistical units), as defined in the Confidentiality Policy Guidelines of the State Data Agency.
7.2. Confidentiality - data treatment
Not applicable.
8.1. Release calendar
Statistical information is published on the Official Statistics Portal according to the Official Statistics Calendar.
The Eurostat database is updated continually, depending on the data availability of new and revised data.
10.1. Dissemination format - News release
Not applicable.
10.2. Dissemination format - Publications
Not applicable.
10.3. Dissemination format - online database
No special dataset or database is developed for city statistics. Most of the data can be found in the Database of Indicators on the Official Statistics Portal. All data on city statistics are also available in the Eurostat’s database.
Definitions of the City statistics manual have been followed for most variables. Information on the deviating definitions used in the data collection is available in the Annex “Deviating methodologies_LT”.
10.7. Quality management - documentation
The quality assurance procedures described in the City statistics manual have been applied. A complete set of validation rules has been observed. Information on quality documentation and additional quality measures is available in the Annex “Quality documentation _LT”.
11.1. Quality assurance
Quality of statistical information and its production process is ensured by the provisions of the European Statistics Code of Practice and ESS Quality Assurance Framework.
In 2007, a quality management system, conforming to the requirements of the international quality management system standard ISO 9001, was introduced at Statistics Lithuania. Main trends in activity of the State Data Agency aimed at quality management and continuous development in the institution are established in the Quality Policy.
Monitoring of the quality indicators of statistical processes and their results and self-evaluation of statistical survey managers is regularly carried out in order to identify areas which need improvement and to promptly eliminate shortcomings.
More information on assurance of quality of statistical information and its preparation is published in the Quality Management section on the State Data Agency website.
11.2. Quality management - assessment
Quality of data is fully assessed using internal validation procedures and Eurostat’s validation methods.
12.1. Relevance - User Needs
User needs and stakeholders’ requirements are collected at several forums. Main users of statistical information on cities are State and municipal authorities and agencies, the media, research and business communities, students, and others.
12.2. Relevance - User Satisfaction
At State Data Agency, user opinion surveys have been conducted on a regular basis since 2005. Official Statistics Portal traffic is monitored; website visitor opinion polls, general opinion poll on the products and services of State Data Agency, target user group opinion polls and other surveys are conducted. In 2007, the compilation of a user satisfaction index was launched. The said surveys are aimed at the assessment of the overall demand for and necessity of statistical information in general and specific statistical indicators in particular.
More information on user opinion surveys and their results is available on the website of State Data Agency, see Surveys of statistical user opinions (information is available only in Lithuanian).
12.3. Completeness
Data availability differs from domain to domain. The main reasons for missing data by variable code, spatial level are presented in the Annex “Missing variables_LT”.
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 the domain and individual variable. As a general rule, timeliness is about 9 months.
14.2. Punctuality
Data for the reference year 2023 were transmitted by 31 October 2024, and some data for the variables that are not available by that date will transmitted by the end of 2024.
15.1. Comparability - geographical
Due to some deviating definitions and different data sources used, the comparability of data is limited to some extent. Detailed information on data sources and deviating definitions is available in the annexes “Deviating definitions_LT” and “Basic information on data sources_LT”.
15.2. Comparability - over time
Most of the data are comparable over time. Breaks in the time series are flagged accordingly (Flag B) if applicable.
15.3. Coherence - cross domain
Data collected at the sub-national level are coherent with the data collected at the national level.
15.4. Coherence - internal
Internal coherence (e.g. between spatial levels, between indicators, such as total, male, female population) is ensured through application of multivariate and univariate validation controls.
Data collection is mostly based on the data available at State Data Agency. For the preparation of statistical information, data from statistical surveys, registers and administrative data sources are used. The main burden is on State Data Agency.
17.1. Data revision - policy
Not applicable.
17.2. Data revision - practice
Not applicable.
18.1. Source data
Detailed information about data sources is available in the Annex “Basic information on data sources_LT” and in the Annex "Type of statistics_LT".
18.2. Frequency of data collection
Data are collected annually, but many indicators are only available in the census year. The last census took place in 2021, these data were provided for the reporting year 2021 in 2022. The next census is planned for 2026.
18.3. Data collection
At State Data Agency , data are collected from different statistical surveys and administrative data sources. Detailed information about data sources is available in the Annex “Basic information on data sources_LT”.
18.4. Data validation
Data validation is carried out by specialists from the State Data Agency, which were responsible for data preparation, other data providers.
At the State Data Agency, different types of data checks for data validation were used.
Generally, at the State Data Agency, data validation contained structural and content validation checks, most of them are logical, arithmetical and qualitative checks. Aggregate data of the current year were compared with the results of the previous periods, other surveys (carried out by the State Data Agency), and administrative data. Review and identification of suspicious aggregates were performed. Data validation also covered the detection of divergent values and (if any) significant changes in the patterns, checking of correlation among possible interfaces. The missing values of statistical indicators were imputed, the wrong ones – edited.
18.5. Data compilation
State Data Agency collected the data requested. All available data were transmitted to Eurostat. No special estimations were made.
Data collection provides information and comparable measurements on different aspects of the quality of urban life in cities.
19 November 2024
For most variables, definitions of the City statistics manual and existing international standards have been followed. Information on the deviating definitions used in the data collection is presented in the Annex “Deviating definitions_LT”.
Statistical units are mostly persons. A few variables are collected on households, enterprises, dwellings, etc. For a comprehensive description of variables and statistical units, see the City statistics manual.
For most variables, the target statistical universe was the usual residents of a geographical area (city). For a detailed description of variables, see the City statistics manual.
In Lithuania, data were prepared for the following spatial levels:
City level – data of six Lithuanian cities (Vilnius, Kaunas, Klaipėda, Panevėžys, Šiauliai, and Alytus);
Functional Urban Area level (FUA) – data of three Lithuanian cities (Vilnius, Kaunas, and Panevėžys).
2014, 2011, 2008, 2004 and 2001 are the reference years for the main data collection. 1996 and 1991 are the reference years for the “historical” data collection. A set of variables has been collected on an annual basis for the periods 2005–2012, 2015-2016, 2017-2018, 2019-2020, 2021-2022. The reference year for the current data collection exercise are 2023.
Not applicable.
The unit of measurement varies from indicator to indicator and from variable. In most cases, the unit of measurement is included in the label.
State Data Agency collected the data requested. All available data were transmitted to Eurostat. No special estimations were made.
Detailed information about data sources is available in the Annex “Basic information on data sources_LT” and in the Annex "Type of statistics_LT".
The Eurostat database is updated continually, depending on the data availability of new and revised data.
Timeliness depends on the domain and individual variable. As a general rule, timeliness is about 9 months.
Due to some deviating definitions and different data sources used, the comparability of data is limited to some extent. Detailed information on data sources and deviating definitions is available in the annexes “Deviating definitions_LT” and “Basic information on data sources_LT”.
Most of the data are comparable over time. Breaks in the time series are flagged accordingly (Flag B) if applicable.
