Date (Creation)

2021-01-01

Citation identifier

gisco-services / https://gisco-services.ec.europa.eu/census/2021/INSPIRE/Data/CENSUS_INS21ES_A_BE_2021_0000

Point of contact

Organisation name	Individual name	Electronic mail address	Role
<span>Statbel (Directorate-general Statistics – Statistics Belgium)</span>, <span>Databases Citizens</span>		pieter.dewitte@economie.fgo pieter.dewitte@economie.fgov.be	Owner

Keywords

• EUROSTAT metadata

GEMET - INSPIRE themes, version 1.0

• Population distribution — demography

Access constraints

Other restrictions

Other constraints

Public access to spatial data sets and services would adversely affect the confidentiality of the proceedings of public authorities, where such confidentiality is provided for by law.

Access constraints

Other restrictions

Other constraints

No conditions apply to access and use

Use constraints

Other restrictions

Other constraints

No conditions apply to access and use

Spatial representation type

Vector

Distance

1000  metres

Language

English

Topic category

• Society

Begin date

2021-01-01

Reference system identifier

ETRS89-extended / LAEA Europe

Distribution format

Name	Version
Geopackage file(.gpkg)
GML	3.2.1
Text	CSV
Text	SDMX

OnLine resource

Protocol	Linkage	Name
WMTS	https://gisco-services.ec.europa.eu/cmaps/service?REQUEST=GetCapabilities&SERVICE=WMTS	ViewService (WMTS) of the Census 2021 data

OnLine resource

Protocol	Linkage	Name
ATOM	https://gisco-services.ec.europa.eu/census/2021/INSPIRE/Data/BE_PD_3035_CSV.zip	The compressed resource (CSV) file contains data and metadata

OnLine resource

Protocol	Linkage	Name
ATOM	https://gisco-services.ec.europa.eu/census/2021/INSPIRE/Data/BE_PD_3035_GML.zip	The compressed resource (GML) file contains spatial data and metadata

OnLine resource

Protocol	Linkage	Name
ATOM	https://gisco-services.ec.europa.eu/census/2021/INSPIRE/Data/BE_PD_3035_GPKG.zip	The compressed resource (GPKG) file contains spatial data and metadata

OnLine resource

Protocol	Linkage	Name
ATOM	https://gisco-services.ec.europa.eu/census/2021/INSPIRE/Data/BE_PD_3035_SDMX.zip	The compressed resource (SDMX) file contains spatial data and metadata

OnLine resource

Protocol	Linkage	Name
ATOM	https://gisco-services.ec.europa.eu/census/2021/INSPIRE/PD.atom	Downloadservice (ATOM-Feed) of all the various packages

Hierarchy level

Dataset

Statement

See 18.5 data compilationSee 18.1<span>Inside</span><em> Statistics Belgium</em><span>, a service which is independent of the service responsible for producing figures, is responsible for the final validation of the data. Internal validation procedures have been set up in order to ensure consistency between all hypercubes and grid data. An external evaluation was also carried out. The aim is, on the one hand, to ensure that the statistics produced are part of a time trend or, if interruptions are found, that these are the consequence of specific, cyclical socio-economic factors. Furthermore, the figures set out in the grid cells were compared with the already published population statistics.</span>

So following checks were executed for the grid statistics

<ul>

<li>Additivity of population figures and surface data were checked.</li>

<li>Comparison was performed with the demographic statistics already published. The numbers match exactly. The total area is comparable with cadastre results.</li>

<li>For each grid cell, the values of 2021 were compared with the grid in 2016. The differences are very acceptable. </li>

</ul>Highly accurate.

Statbel uses the concept of usual residence and tries to deduce this from the data in the population register. The population register disposes of longitudinal information. Therefore, we have information of moving citizens. Based on that information, it's possible to see if condition (i) of the definition of usual resident population is satisfied:

<em>"(i) those who have lived in their place of usual residence for a continuous period of at least 12 months before the reference date"</em>

Indeed, we can check whether someone lives already for 12 months in Belgium.

It's more difficult to see if condition (ii) is satisfied:

<em>"(ii) those who arrived in their place of usual residence during the 12 months before the reference date with the intention of staying there for at least one year"</em>

 In the population register, we have no information on the <strong><em>intention</em></strong><em> </em>to stay. But, based on the records with information of moving citizens in the months after the reference date, it is possible to estimate this. 

Remarks

<ul>

<li>This differs from the figures statbel publishes on its own website, where the registered population is used at midnight 31 December 2020 (=1st January 2021). Moreover, asylum seekers are included in the figures we submit to Eurostat which isn't the case in our national publications.</li>

<li>Both census statistics and demography use the same reference moment and data source (population register). As a consequence, the demographic part of the census is consistent with the demographic statistics published earlier.</li>

</ul>

Once the usual resident population is determined, we can precise with more geographical detail the usual residence. Municipality codes are available in the population register. Therefore, all levels NUTS1,2,3 and LAU2 can be derived from that information. To see in which km² grid cell the citizen has his/her usual residence, we use the address from the population register.

There is a geocoding of these addresses in what we call the CSAB file established by Statbel.

In a first step we require that members of the same household are attributed to the same geographical point. Therefore, it is important to determine the household id's before a grid cell id can be allocated. The composition of the households is also derived from information in the population register. Here, we distinguish between private households and collective living quarters. Private households are mainly determined based on information of the reference person in the household, whereas collective living quarters are determined by the information in the address.

To establish the CSAB file (geocode the addresses), the information in the population register has to be compared with geographical data coming form databases from the 3 regions (each NUTS 1 region has his own database). There is an automated step first. To compare addresses between the population register and the geographical data, intelligent algorithms are used as e.g. based on TF-IDF methods. Sometimes the exact address isn't available as such in one of the geographical registers. e.g. for a given street we have nr. 20 in the population register, but in the geographical databases we have nr. 18 and nr. 22. In those cases geographical interpolation can be used to estimate the geographical coordinates. In some other cases extrapolation can be used.

After that there is a manual step to geocode the rest of the addresses whereby geographical coordinates where not found in the automated step.

The CSAB file is updated each year with all new addresses. In the Belgian geographical databases, Lambert 72 (EPSG:31370) projection system is used. To attribute a grid ID, this is converted to the ETRS89 / LAEA Europe (EPSG:3035) system.

It is difficult to mention the exact accuracy of the geographical points, since this can change from address to address. Interpolated and extrapolated points are far less precise than addresses available in the original geographical databases. But the overall accuracy is very precise. Addresses in the original geographical databases are precise to the metre and sometimes even more detailed. Only 0,32% of the addresses is inter- or extrapolated. Exceptionally, it can be less precise for some extrapolated points. Mostly, only for points very near to the border of 2 different grid cells there is a very small risk the address is allocated to the wrong grid cell.

For the km² grid, not only population figures were supplied, but also land surface data. In most cases this is exactly 1 km². For border and coastal areas, the area was computed based on a GIS intersection of the GRID layer with the layer of the official Belgian borders both converted to the ETRS89 projection. Moreover, areas of water bodies such as lakes were subtracted from the initial surface. This information is estimated based on Corine Land Cover 2018 data.<span>Confidentiality - Regulation (EU) 2017/712 Art 4 and 5</span>There was some research in order to decide which SDC-method to use.

First the microdata were aggregated without SDC. These results were checked for sensitive information. The first conclusion was that for the hypercubes as well for the GRID-data, there are not a lot of sensible frequency counts. So, a very light SDC-method should suffice.

Different SDC-methods were considered:

<ul>

<li>Cell key method was never considered as a serious candidate because of the lack of additivity. Our dissemination team found it too difficult to explain to the general public that additivity is not preserved.</li>

<li>We performed record swapping in 2011, but due to some inconsistency problems in 2011 for the household data, there was very little support to use this method again. There was also a lot of criticism from census users regarding the record swapping method.</li>

<li>Also, cell suppression was considered as a bad choice due to reasons Eurostat mentioned in several meetings.</li>

</ul>

Statbel came up with a new method we could call "geographical perturbation".  This method only works for a very light SDC approach when only a very small percentage of the frequency counts is considered as confidentially problematic. This method is now applied for the grid data. Briefly explained, this method works as follows:

It is a pretabulated method, which means some of the modifications is done in the microdata before aggregation.

<ol>

<li>Based on some <span data-mce-mark="1">confidentiality</span> rules, we determine which grid cells have to be protected. These cells are determined on the basis of the aggregated data before a SDC method is applied.</li>

<li>Then we add some perturbations to the microdata. Households in a grid cell to protect are virtually moved to a point with different geographical coordinates. This is a point in another grid cell that should not be protected. This point is always located in the same municipality (same LAU2). We try to choose to the greatest extent possible a point in the same neighbourhood. In Belgium we have some statistical geographical areas that are very detailed. We call them the statistical sectors and these are more detailed than the LAU2 level. Statistical sectors can be considered as the neighbourhoods and are very important for our national dissemination. We choose, if possible, the nearest point (=inhabited building) in the same statistical sector. But (in some rare cases) if this point is too far away, we choose a point closer to the original point in another statistical sector, but always in the same LAU2 area.</li>

<li>Grid cells are recalculated based on the perturbated points. After that, the dataset is aggregated again.</li>

</ol>

Of course, the result of this method depends on the confidentiality rules used in step (1). We have tested this method where we started from different confidentiality rules, used in step 1 and we've compared the results with each other. These rules in step 1 are criteria based on frequency counts in grid cells such as number of people, number of households and the other frequency counts by grid cell we have to deliver to Eurostat in 2024. We compared relatively mild criteria with more severe criteria. After analysing the results, the conclusion was that one of the mildest criteria was sufficient for the protection of confidential data. Keeping the detailed rules secret is an important aspect to prevent anyone from being able to undo the protection.

Metadata

File identifier

CENSUS_INS21ES_A_BE_2021_0000 XML

Metadata language

English

Character set

UTF8

Hierarchy level

Dataset

Date stamp

2024-06-20T09:00:00

Metadata author

Organisation name	Individual name	Electronic mail address	Role
<span>Statbel (Directorate-general Statistics – Statistics Belgium)</span>, <span>Databases Citizens</span>		pieter.dewitte@economie.fgo pieter.dewitte@economie.fgov.be	Point of contact