High-value datasets – building data in EU Member States
Publication Date/Time
2023-08-07T06:00:00+00:00
Learn more about buildings in the EU with open data
This is part of a series of articles
[https://data.europa.eu/en/publications/datastories?keywords=high-value+datasets+-&country=All&year=&sort_by=created&sort_order=DESC&items_per_page=10&keywords=High-value+datasets%E2%80%AF%E2%80%93&merged-select=created&items_per_page=10]
showcasing examples of high-value datasets from different thematic
categories. High-value datasets are defined by EU law based on their
potential to provide essential benefits to society, the environment
and the economy. This series aims to help readers find reliable and
accurate information from official sources relating to the
availability of various high-value datasets, and to present this
information through data visualisation. You can check out the article
providing an overview of high-value datasets here
[https://data.europa.eu/en/publications/datastories/high-value-datasets-overview-through-visualisation].


Only datasets specifically defined by law can be considered high-value
datasets, and as such the data presented in the articles does not
necessarily fall under that definition. Instead, the data has been
chosen to be thematically adjacent to high-value datasets and to
showcase what can be done with information made available by official
EU bodies and EU Member States. The official list of high-value
datasets adopted on 12 December 2022 can be found in the legal
documents
[https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=PI_COM:C(2022)9562]
that define them and their characteristics. 

 

BUILDING DATA IN THE HIGH-VALUE DATASETS

Geospatial data is one of the categories of high-value datasets, and
it includes information within the scope of the ‘Inspire’ data
themes
[https://inspire-geoportal.ec.europa.eu/theme_selection.html?view=qsTheme]
such as administrative units, geographical names, addresses and
cadastral parcels, as defined
[https://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:32007L0002]
in Annex I and Annex III to Directive 2007/2/EC of the European
Parliament and of the Council. 

Geospatial data also includes information about buildings and their
characteristics. This information is available at different levels of
detail, ranging from a broad overview to a very detailed view up to a
scale of 5 000 to 1. It provides important details about buildings,
such as their unique identifiers, their size and shape, the number of
floors, and how they are used.
[https://data.europa.eu/sites/default/files/img/media/9.buildings5-01.png]
An important source for data about buildings is the Census Hub
[https://ec.europa.eu/CensusHub2/query.do?step=selectHyperCube&qhc=false].
The Census Hub is a project
[https://ec.europa.eu/eurostat/documents/4031688/6285607/KS-02-14-480-EN-N.pdf/05b4ca91-1f72-4dbb-ae2c-d3a07f56d795?t=1418305944000]
of the European Statistical System to provide high-quality, detailed
and comparable data on the size and characteristics of the population
and the housing stock of Europe, including detailed data on dwellings.
For the scope of the project, dwellings were defined
[https://ec.europa.eu/eurostat/statistics-explained/index.php?title=People_in_the_EU_%E2%80%93_statistics_on_housing_conditions&oldid=266849]
as ‘a room or a suite of rooms in a permanent building designed for
habitation by a private household’.

Data on dwellings is available from the country level down to the
municipality level. It offers a wide range of variables among which
are the type of building, type of heating, number of rooms and useful
floor space. Different variables are available at different
administrative unit levels, from country to region-, province- and
city-level data.

A particularly interesting set of information concerns buildings’
period of construction. This data provides valuable insights into the
historical development and characteristics of an area’s landscape.
Understanding the period of construction helps researchers, urban
planners and architects gain a deeper understanding of architectural
styles, construction techniques and materials used throughout
different eras. Analysing data on the period of construction of
buildings allows for the identification of trends, patterns and
changes in housing stock over time, facilitating the assessment of
urban growth, demographics and societal transformations. This
information is essential for preservation efforts, urban
revitalisation projects and effective city planning, enabling
stakeholders to make informed decisions about infrastructure
development, restoration and conservation.

The data can be downloaded for countries, regions and provinces, and
divides dwellings’ period of construction into nine time groups –
from those built before 1919 to the most recent ones built after 2006.
The following visualisation presents the dispersion of residences
across various time periods, with larger figures denoting a greater
number of constructed dwellings. Within this depiction, it is possible
to observe the post-World-War-II reconstruction efforts in multiple
countries and to distinguish countries where a substantial portion of
their urban scenery took shape nearly a century ago.
[https://data.europa.eu/sites/default/files/img/media/9.buildings5-02.png]
One of the most detailed datasets about buildings is made available
[https://land.copernicus.eu/local/urban-atlas/building-height-2012] by
Copernicus [https://www.copernicus.eu/en], the European Union's Earth
observation programme. The data
[https://land.copernicus.eu/local/urban-atlas/building-height-2012?tab=metadata]
is a 10-meter-high resolution raster layer containing height
information generated for selected cities and urban centres as part of
the Urban atlas [https://land.copernicus.eu/local/urban-atlas] suite
of products. It allows for a street-level view of urban development in
major EU cities.

A 10-meter resolution makes it possible to zoom in on neighbourhoods,
historical monuments and even single buildings in hundreds of cities.
This way the different ways cities developed over time become evident.
Some, such as Bucharest, show a ‘flatter’ development with smaller
differences in building height across the city. Other cities such as
Helsinki and Stockholm, on the other hand, exhibit a significant
concentration of high-rise buildings in small parts of their areas. 
[https://data.europa.eu/sites/default/files/img/media/9.buildings5-03.png]
 

BUILDING DATA FROM DATA.EUROPA.EU

Looking for dwellings or building data
[https://data.europa.eu/data/datasets?query=dwellings%20OR%20building&]
on data.europa.eu yields a very high number of results. For example,
the portal offers information about the type
[https://data.europa.eu/data/datasets/244100-0?locale=en] of dwellings
in Belgium, the building cost
[http://data.europa.eu/88u/dataset/4506-price-indices-figures-building-costs-new-dwellings?locale=en]
of new dwellings in the Netherlands since 1994, and so on. 

Another useful case study is from the Finnish open data portal, which
made available
[http://data.europa.eu/88u/dataset/f439f4ca-2c13-41bf-be91-1ece5f957915~~1]
data on several variables concerning the housing stock in Helsinki.
They include the year of construction and type of dwelling, the number
of rooms and floor area, but also aggregated information such as the
dwelling stock and dwelling density by district and subdistrict.

Within this dataset, an interesting metric worth analysing is the
amount of residential space individuals possess. Depicted in the
subsequent visualisation is the evolution of square meterage per
person in Helsinki since 1990 across varying household sizes. The
findings show an overall growth in per capita floor space, with a
12 % increase over the aforementioned period. Notably, households
consisting of seven or more members exhibited the most substantial
growth, with their per capita floor space expanding from 10.4 to 13
square meters, representing a 25 % surge. The increase, however, is
mostly due to the years between 1990 and 2000. Since then, floor space
per capita for large families has been declining. In households with
six members, for example, the average floor space available per person
decreased by around one square metre between 1990 and 2020. On the
contrary, smaller households experienced an increase, resulting in
individuals having access to more extensive floor areas for their
personal use, with singles reaching an average of 49 square meters, up
from 46 in 1990. 
[https://data.europa.eu/sites/default/files/img/media/9.buildings5-04.png]
Similarly, the Swedish open data portal made available another dataset
through which it is possible to study the distribution of dwellings in
the Greater Stockholm area
[http://data.europa.eu/88u/dataset/http-catalog-scb-se-resource-ssd-lagenhetombakbpltar?locale=en].
It includes information about the type of ownership, period of
construction and size of the dwellings from 1989 to 2016. 

The Statistics Sweden website also offers other information, such as
the number of dwellings
[https://www.statistikdatabasen.scb.se/pxweb/en/ssd/START__BO__BO0104__BO0104D/BO0104T5/]
by region, type of building and useful floor space from 2013 to 2022.
Such a dataset was used to build the following visualisation, which
shows an overall increase of the number of dwellings in the Greater
Stockholm area. The bulk of the growth was due to small dwellings with
a surface area of 30 square metres or less, which increased by 62 %
in one- or two-dwelling buildings, by 25 % in multi-dwelling
buildings, and by 54 % in other type of buildings. At the same time,
a significant – albeit smaller – growth was also registered for
slightly larger dwellings. In the case of one or two-dwelling
buildings, the stock of large houses of more than 190 square metres
also notably increased by about 15 %, while for other type of
buildings the growth was also visible in the central-upper part of the
distribution – from 121 to 170 square metres. Most houses in the
Greater Stockholm area are built in multi-dwelling buildings, which is
the category that experienced the overall larger growth in absolute
values.

Statistics Sweden defines the different types of buildings as follows:
‘one- or two-dwelling buildings’ means detached one- and
two-dwelling buildings, along with semi-detached, row and linked
buildings. ‘Multi-dwelling buildings’ means buildings with three
or more apartments including balcony-access housing. Lastly, ‘other
buildings’ refers to buildings that are not intended for residential
purposes but still contain ordinary dwellings, for example buildings
used for business or public activities.
[https://data.europa.eu/sites/default/files/img/media/9.buildings5-05.png]
 

OTHER OFFICIAL DATA PROVIDERS

Eurostat offers
[https://ec.europa.eu/eurostat/en/web/main/search/-/search/dataset?text=dwellings]
several datasets about dwellings and housing as well. Examples include
a survey
[https://ec.europa.eu/eurostat/databrowser/view/prc_colc_surf/default/table?lang=en]
of dwelling sizes by type of dwelling in EU cities, used as a
correction coefficient
[https://ec.europa.eu/eurostat/databrowser/explore/all/economy?lang=en&subtheme=prc.prc_colc&display=list&sort=category&extractionId=PRC_COLC_SURF]
when calculating inflation and the cost of living in different
countries.

The ‘Inspire’ geoportal [https://inspire-geoportal.ec.europa.eu/]
has a specific section
[https://inspire-geoportal.ec.europa.eu/overview.html?view=themeOverview&theme=bu]
dedicated to building data. In it, it is possible to search for
information about a Member State or the EU as a whole. For Italy and
Germany, in particular, there is a higher number of datasets available
ranging from historical villages
[https://inspire-geoportal.ec.europa.eu/download_details.html?view=downloadDetails&resourceId=%2FINSPIRE-c22038a7-4e03-11e8-a459-52540023a883_20230305-223302%2Fservices%2F1%2FPullResults%2F7281-7300%2Fdatasets%2F2&expandedSection=metadata]
in the Liguria region to theatres and stages in Trier
(Rhineland-Palatinate state).

More aggregated data about dwellings is also provided by the European
Environmental Agency [https://www.eea.europa.eu/en], which looks at
topics concerning energy consumption
[https://www.eea.europa.eu/data-and-maps/figures/households-energy-consumption-by-end-uses-3]
and efficiency, among other things
[https://www.eea.europa.eu/data-and-maps/data/external/floor-area-of-dwellings].
The Joint Research Centre has produced several studies
[https://publications.jrc.ec.europa.eu/repository/search?query=dwellings&sort=relevance]
aimed at understanding various topics related to housing, which ranged
from energy renovation through energy-efficient and asbestos-free
dwellings
[https://publications.jrc.ec.europa.eu/repository/handle/JRC129218],
to building a stock inventory to assess seismic vulnerability across
Europe
[https://publications.jrc.ec.europa.eu/repository/handle/JRC112031].

 

METHODOLOGICAL NOTES

When this story was produced, data
[https://ec.europa.eu/CensusHub2/query.do?step=selectHyperCube&qhc=false]
on the period of construction from the Census Hub was temporarily
unavailable for the following countries: Cyprus, France, Greece,
Liechtenstein, Lithuania, the Netherlands and Portugal. Cities to
include in the visualisation for Copernicus data were selected among
countries not previously covered in the high-value datasets themed
series of data stories
[https://data.europa.eu/en/publications/datastories?keywords=high-value+datasets+-&country=All&year=&sort_by=created&sort_order=DESC&items_per_page=10&keywords=High-value+datasets%E2%80%AF%E2%80%93&merged-select=created&items_per_page=10].


 

Download the data visualisations
[https://gitlab.com/dataeuropa/data-provider-repository/-/blob/master/Data%20stories/HVD%20Data%20Stories/Buildings/Buildings-data-visualisations-png.zip] presented
in this article and the data behind them
[https://gitlab.com/dataeuropa/data-provider-repository/-/blob/master/Data%20stories/HVD%20Data%20Stories/Buildings/Data-Buildings-data-story-07-08-2023.xlsx].

 

_Article by Davide Mancino_

_Data visualisations by Federica Fragapane_
