City statistics
Sector: Government • Location: Norway
Source: EU Funding & Tenders Portal
This main purpose of the project is to enable Statistics Norway (SN) to provide city statistics according to definitions compliant with ESS standards. To make sure we can provide statistics compliant with the ESS standards, an analysis of requested list of variables must be made. Furthermore, to do this in a well documented. transparent and open way, to make guidelines for other NSIs. A good docum
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | ended |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | This main purpose of the project is to enable Statistics Norway (SN) to provide city statistics according to definitions compliant with ESS standards. To make sure we can provide statistics compliant with the ESS standards, an analysis of requested list of variables must be made. Furthermore, to do this in a well documented. transparent and open way, to make guidelines for other NSIs. A good documentation will make it easier for others to do similar for setting up their reporting schedules. Solutions will as far as possible be made upon open source programming like R or Python, and thus be made available to anyone. The use of existing APIs for classifications, codelists and statistical tables will be emphasised. The project will have emphasis on existing data sources and cost efficient methods for providing high quality statistics. Quality assessment will be done on data sources, and alternative data sources will be explored. Alternative data sources may e.g. be in form of geodata, open sources or State to Municipality reporting system (KOSTRA). The project will also search for novel methods for new typologies of LAU, e.g. along the urban-rural dimension and centrality, and explore pilots on very long time series. Norway had a major rewamp of the regional divisions in 2020, challenging possibilities for making time series. Pilots and test in this aspect may give experience for how to handle this, now and for future regional reforms. Which may benefit other NSIs. An extensive use of high quality geodata, e.g. ground properties, enterprises, population and Corine data, in combination with geocoding of more than 100 year old digitised registers and censuses is expected. Awareness raising and knowledge sharing is a natural part of this project. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
Project Type | Obfuscated Data |
Article Published Date | Obfuscated Data |
