Standardised Interfaces for Geographical Analyses: their significance or function for statistical output. Experiences in the Netherlands

Mathieu Vliegen1

Geographically referencing of statistical outputs has become a relevant topic in international discussions because of the growing importance of comparable regional and spatial statistics at this level, particularly for policy purposes. A possibility of standardised interfaces in this respect is regularly advocated like, for example, a European system of grid squares. Reality is, however, refractory, from a regional or spatial viewpoint is refractory and its analyses show many various aspects. National statistical institutes have to take it into consideration when referencing statistical outputs about that reality. The article portrays practices on this point at a national statistical institute and developments in those practices during the last decades. It debouches into a pleading for a multi-aimed geographically referencing practice in accordance with the multi-functional analyses of the geographical reality.

1. Introduction The present topic of standardised interfaces for geographical analyses of statistical data can be dealt with in various ways. This topic is mostly treated from a technical perspective. The way basic content data can geographically be referenced, the precision of methods used in this kind of referencing, their consistency in time and space and their relationship to the problem of confidentiality imposed by the original content data are often dominating the discussions on this topic. Although those questions are, indeed, important, I will not address them here. Instead I want rather to draw the attention to another aspect in the geographical referencing process of statistics. That aspect refers to the significance or function of referencing methods in relation to geographically meaningful statistical output. To my opinion, this aspect is often overlooked in discussions on geographical referencing and questions about standardization of referencing methods for geographical analyses.

Generally speaking, almost everybody will agree to the statement that statistical output for geographical analyses should be demand and not supply driven. Unfortunately, a completely demand driven statistical output for geographical analyses is not always possible. The geographical component present in content data sources can prevent such a demand driven output, when it does not fit to the geographical scale requested. On the other hand, being zealous to compile geographically referenced statistical output, one should be on the alert not to publish meaningless data from a geographically viewpoint.

As far as I can review the demand side at present, I distinguish a need for three kinds of geographically referenced statistical output, namely regionally, spatially and geometrically referenced statistical output. By regionally referenced statistical output I mean statistics for territorial units which are ultimately based on boundaries of units of an administrative kind. By spatially referenced statistical output, on the other side, I mean statistics for territorial units that are solely based on specific features of the earth surface. No boundaries of units of

1 The author was former Programme Manager Geography and Real Estate at Statistics Netherlands.

The author likes to thank Niek van Leeuwen at Statistics Netherlands for his comments on a first draft of this paper.

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an administrative kind interfere with the result of this kind of geo-referencing. The boundaries are solely fixed by the specific feature of the earth surface in question. Finally, by geometrically referenced statistical output I mean statistics which are based on a system of co-ordinates projected on the earth surface. A well-known system in this respect is the grid system, i.e. a system of co-ordinates based on squares of a certain width, for example 500 x 500 metres. Less known is a system of hexagons, i.e. a system of co-ordinates based on six-sided polygons. It should be noted that such systems of co-ordinates do not interfere neither with boundaries based on territorial units of an administrative kind nor with boundaries based on spatially oriented territorial units.

Those three different kinds of geographically referenced statistical output require basically their own geographical interface(s). Such interfaces can be viewed as geographical tools or geographical support systems enabling the compilation of geographically referenced statistics from raw content data in registers or (sample) surveys by linking the geographical components in those tools to the data in those registers or surveys. In order to understand the interfaces required for the three kinds of geographically referenced statistics mentioned above it is useful to consider, first, the distinct referencing methods for those three kinds of statistics more in detail. That will be done in the next section on the basis of experiences in the Netherlands. Section 3 discusses then the geographical interfaces developed for those various kinds of geographically relevant statistics in the Netherlands. The question of standardised interfaces for those various kinds of geographically referenced statistics will finally come up for discussion in the last section.

2. Methods of geographic referencing

2.1 Regionally referencing Regionally referenced statistics have a longstanding tradition at Statistics Netherlands. Since its founding by Royal Decree of 9 January 1899 the process of regionally referencing statistical output started right away, when the Population Census was taken in that same year. In the course of time various modes of regionally referencing came into practice. The principle underlying all of these various modes was regionalisation of national figures or providing figures on the distribution of phenomena over the whole territory of the country.

During the more that one century old history of Statistics Netherlands a lot of various territorial subdivisions has been used for the regionalisation of national figures. The territorial subdivisions used at present in the regionalisation process refer to administrative or normative subdivisions on the one hand, and analytical or functional subdivisions at the other hand.

The administrative or normative subdivisions are of various kinds. - First, the institutionally defined administrative subdivisions of the provinces at an

intermediate regional level and the municipalities at the local level. The boundaries of the provinces are quite stable over time. The boundaries of the municipalities are not so stable over time, since their number is diminishing almost every year, due to a general policy of the central government to strengthen the local government for their tasks to perform.

- Second, the administratively defined territorial subdivisions for the performance of a specific policy task at a particular regional level. Such specific regional policy-oriented subdivisions are, for example, the regional labour market platforms for labour market policies; police regions for safety policies and district-courts for judicial policies. These policy-oriented regions do only change from time to time. Those

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changes are dependent on changes in the respective policies. All those territorial subdivisions have the municipalities as building blocks.

- Finally, at the micro-geographical level the subdivision of the territory of the municipalities into postcode sectors (four figures) and postcodes (four figures plus two characters). Devised originally only for the distribution of the postal mail, this territorial subdivision became very soon a very strong instrument for market and other research.

The analytical or functional territorial subdivisions were introduced for the purpose of a specific regional statistical description. The use of administrative or normative territorial subdivisions leads only to regional descriptive statistics. Those statistics do not take regional elements into account at all. The ‘region’ in those kinds of statistics is just a formal category. Regional statistical descriptions, on the contrary, do exactly search for that regional element in regional statistics. The ‘region’ in those descriptions takes here on a meaning as regards content. The use of such regional statistical descriptions in the regionalisation process leads to what a former Director-General of Statistics Netherlands has called ‘regional statistical differentiations’. Such regional statistical differentiations provide namely insight in the diversity between regions (Verstege, 1957).

In the course of time various analytical or functional subdivisions of the national territory have been drawn up. At present some of those subdivisions are not used anymore, due to developments which have taken place in society during the last century. The most important ones still used nowadays are the following.

- First, the thematically oriented territorial subdivisions into agricultural areas and tourism regions. The goal, or the point of view, with which the regional statistical differentiations in these fields are sought, decided the type of those subdivisions. The point of view in the domain of agricultural phenomena is very different from the point of view in the tourism domain, yielding, therefore, much specialised territorial subdivisions in each of both statistical fields. The subdivision into agricultural areas has a long-standing tradition, which dates back to the second half of the nineteenth century. Since then, it has been revised several times, the latest one in the beginning of the nineties of the last century. As compared with the agricultural areas, the tourist regions are not so old, since their origin lies in the seventies of the last century.

- More important are two thematically encompassing territorial subdivisions at an intermediate geographical level. The first one to be mentioned here is the functional subdivision of the national territory into forty COROP-regions at the intermediate level between the provinces and the municipalities2. Its origin dates back to the late sixties of the last century, when regional economic policy was greatly expanded resulting in an increasing interest for regional economic statistics. The delineation method was based on a functional orientation principle – sometimes also called the nodal principle. The various parts of a region using this orientation principle are focused on a central place (‘node’) in that region, whereas the various parts of other regions are focused on different central places in those regions. The central place and the other geographical parts focusing on that central place form one region. However, the nodal principle could not been applied completely for the delineation of the

2 The name of this subdivision has been derived from the Committee on the Co-ordination of the

Regional Research Programme (abbreviated as COROP in Dutch). Statistics Netherlands devised it on behalf of this Committee for the implementation of a statistical programme consisting of regional accounts and regional statistics on employment, investments and traffic flows. More information on the COROP-regions can be found in Raets and Van Batenburg (1983) and in Vliegen (1999 and 2003).

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COROP-regions, since for policy reasons at that time they had to fit into the boundaries of provinces3. Soon after the introduction of the COROP-regions they became part of the European Nomenclature of Territorial Units for Statistics (NUTS). Since this functional territorial subdivision came into existence, it has been revised only once, when the new created land in the IJsselmeer was declared as a new province. However, small boundary changes in the COROP-regions take regularly place, due to changes in de administrative structure of the municipalities.

- A second thematically encompassing analytical twofold subdivision refers to twenty-two urban areas. An increasing demand for urban statistics as a consequence of a growing attention to urban development in national and international policies led to the delineation of larger urban agglomerations with their urban regions in the late nineties of the last century. A larger urban zone (grootstedelijke agglomeratie) was defined as an administratively adjusted continuous build-up area with a large number of jobs (at least 50 thousand), of potential users of public facilities (at least 150 thousand) and of inhabitants (if possible, more than 100 thousand). The administrative adjustment took place at the level of the municipalities. An urban region (stadsgewest) consists of a larger urban agglomeration with surrounding municipalities, which are mutually interconnected by interrelations based on commuting flows at the labour market and flows of removals at the housing market. Its delineation is, therefore, also nodal based4.

- Finally, at the micro-geographical level the subdivision of the municipal territory into neighbourhoods and districts (being a grouping of neighbourhoods) should be mentioned. The basic ideas underlying this twofold subdivision were laid down at the traditional Census of 1947 (Vliegen, 1999 and 2003). Formerly revised only on the occasion of the Censuses held up to 1971, the two-fold subdivision is updated annually since the middle of the eighties of the last century. Since that date the subdivision is also primarily the responsibility of the municipalities themselves. Statistics Netherlands co-ordinates only that subdivision at the national level.

A comparison of the present situation with regard to regionally referenced statistics (Beeckman, 2006) with the similar situation of say ten to twenty years ago (Raets and Van Batenburg, 1983, Vliegen, 1996) shows quite a lot of differences. Compared to that earlier period the present situation can be characterised by

- a diminution in regionally referenced statistics for (a) administratively defined territorial subdivisions with respect to specific policy purposes, and (b) thematically oriented territorial subdivisions;

- an increase in regionally referenced statistics for the thematically encompassing subdivisions of the COROP-regions, the urban regions and the large urban

3 Not long after its creation the COROP-regions surpassed the subdivision into economic-geographic

areas which had been used as the analytical and thematically encompassing territorial subdivision in the regionalisation process since the beginning of the twenties of the last century. Its delineation method, however, was based on a zonal principle. That method yields areas where a given set of phenomena occurs to an equal degree, while in other areas those phenomena were either absent or present to a different degree. More information on this subdivision can be found in Raets and Van Batenburg (1983) and in Vliegen (1999).

4 More information on the delineation of the larger urban agglomerations and their urban regions can

be found in Vliegen (2003 and 2005).

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agglomerations at an intermediate geographical level; and for the municipal neighbourhoods and districts at the micro-geographical level5.

2.2 Spatially referencing A first attempt at compiling spatially oriented statistics was made in the Census of 1920, when a new subdivision of the municipal territory was introduced. The territory of every municipality was then subdivided in so-called ‘inhabited places’ and ‘areas with scattered houses’. The practical delineation of the ‘inhabited places’ was left to the mayors of the municipalities. For that purpose they had received the relevant fragment of the topographical map (scale 1: 25 000) for their municipality and guidelines how to draw lines on that map around all groups of dwellings known under a common name ant to provide those with a name (Vliegen, 1999).

Although this subdivision is theoretically spatially in intent, it is administratively oriented in its effect, since it refers to the municipal territory. Consequently statistics for the ‘inhabited places’ (and areas with scattered houses) were only published at the level of the municipality. In those municipal tables, however, a possibility was given for those users interested to derive manually also the relevant statistics for inhabited places located on the territory of two or more municipalities. Between brackets the word ‘partly’ was namely added to the name of such inhabited places in the tables for every municipality in question.

The same procedure was applied in the Censuses up to the last traditional one in 1971 on the understanding that the municipal subdivision into ‘inhabited places’ and ‘areas with scattered houses’ was replaced from 1947 on by a subdivision of the municipal territory into districts and neighbourhoods (CBS, 1950). Finally, at the Censuses of 1960 and 1971 a specific table was also published for such inhabited places – now named localities and agglomerations - with their number of inhabitants, the municipality or municipalities to which they belong as well as the codes of their constituent neighbourhoods (CBS, 1964 and 1981).

A more systematically approach for this kind of spatially referenced statistical output started only recently. The Census tables 2001 of the European Union for urban areas (Eurostat, 2001) as well as the availability of relevant maps in digital form gave rise to such an approach. The spatial unit, to which this kind of geographically referenced statistics relates, is called the population cluster. It is defined as a continuous morphological build-up area mainly inhabited by people with a clearly recognisable street formation and with at least 25 dwellings located in that build-up area. That definition corresponds for the most part with the definition of the United Nations for a locality as a distinct population cluster. Compared to the United Nation’s definition a population cluster is, however, defined more restrict. It excludes namely also groups of buildings ‘…though not part of such a built-up area, form a group to which a locally recognised place name is uniquely attached..’ or ‘… constitute a group, none of which is separated from its nearest neighbour by more than 200 metres’ (United Nations, 1998). Apart from such groups of buildings the definition mentioned above excludes also other forms of settlements from being a population cluster, such as ribbon development along rivers, rivers or canals in the Netherlands or similar settlement patterns in rural areas.

5 More and more publications with regional statistics in the Statline Databank at the Website of

Statistics Netherlands contain figures for a territorial grouping of provinces (NUTS 1 level), provinces (NUTS 2 level), COROP-regions (NUTS 3 level), urban regions, larger urban agglomerations and municipalities. Figures for the municipal neighbourhoods and districts are presented in separate publications.

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Various digital maps have been used for the practical delineation of the population clusters. The most important one was the digital land-use map of Statistics Netherlands. Other maps were the National Road Map of the Ministry of Traffic and Transport, to which the Dwelling Register from Statistics Netherlands had been linked at the street level, and the Topographical Map (scale 1:10 000) of the Topographic Agency Cadastre, from which the area covered by buildings was extracted. The actual delineation was performed in a GIS application especially designed for the analysis of those various maps. The criterion of 25 dwellings was taken from the recommendations to local authorities with regard to the delineation of neighbourhoods. One of these recommendations says namely that a grouping of 25 dwellings in a rural area should be delineated as a separate neighbourhood. Figure 1 shows the map with the spatial distribution of the 2 026 population clusters delineated, together with an indication of their various sizes6.

Figure 1. Population clusters, 2001

50 000 inwoners of meer10 000 tot 50 000 inwoners2 000 tot 10 000 inwoners500 tot 2 000 inwonersminder dan 500 inwoners

6 More information on the concept of the population clusters and their practical delineation can be

found in Vliegen et al (2006).

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The spatial unit of the population cluster is not comparable with its similar precursors in the traditional censuses from 1920 on mentioned above. First of all, the definition of an inhabited place, a locality or an agglomeration (a locality located at the territory of two or more municipalities) in those traditional censuses is less strict than the definition of the population cluster. As consequence, ribbon development or similar settlement patterns with in rural areas with a common place name are often also classified as an inhabited place or locality in those censuses. Moreover, the way of delineating the inhabited places and localities in those censuses differs considerably from the delineation of the population clusters. This is particularly the case in the censuses after World War II, when the basic unit for the delineation of localities consisted of a neighbourhood with a built-up area.

2.3 Geometrically referencing Statistical data were geometrically referenced by a grid system of 500 x 500 meter for the first time at the last conventional census of 1971. This kind of referencing was one of the desiderata for the planned 1970 census by a working group of various researchers in the social and geographic sciences (SISWO, 1968).

The grid referenced data, however, were never published, since the discussion in the Netherlands about the census and other databanks in relation to the protection of privacy continued even after the census 1971 had been taken. That socio-psychological climate of public distrust with regard to a census in general from the viewpoint of privacy aspects was again running higher during the preparation of the planned 1981 census. Within that climate it was not thought advisable to publish statistics at such a small geographical scale7. An example of the results which could have been published at that time is shown in figure 2. Until the nineties of the last century geometrically referencing by way of a grid system was completely out of the picture. At the beginning of those nineties, however, the interest in using the grid system for statistical purposes increased suddenly. That increasing interest was aroused by its pre-eminent suitability as a practical calculating tool in the modelling of concepts.

1. The first concept which was modelled along these lines was the concept of urbanisation. The history of measuring that concept dated already back to the fifties of the last century. At that time a multi-dimensional typology based on physical and socio-economic criteria was developed to measure the degree of urbanisation of the municipalities (CBS, 1958). In the nineties, however, it became more and more difficult to update that typology, particularly due to the developments in the urban field. It was then decided to develop a new measure based on generally accepted ideas about urbanisation that could be applied to various geographic levels and that, moreover, would be easy to implement and easy to update annually. That new measure was called the address density of the surrounding area. That measure stands for one of the most essential features of urbanisation, namely the concentration of human activities. It was assumed that each of these activities is associated with an address. The concentration of human activities at a certain location is then defined as the address density in the area surrounding that location.

7 The result of those discussions is well-known. The planned 1981 census was first postponed and

then later on never taken, when the census law had been revoked by parliament (Vliegen en Van de Stadt (1988) or Van der Laan (2000).

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Figure 2. Number of dwellings per grid square of 500 x 500 meter, 1971

10 - 2425 or more

9 or less

Operationally the area surrounding a location was defined as the area within the radius of one kilometre, which – translated in grid squares of 500 x 500 meter – covers 13 grid squares of that size (one grid square for the location and twelve grid squares at a distance to one kilometre from that location grid square). The switch from ‘the address’ to the ‘grid square of 500 x 500 meter’, had operationally for a specific geographic area as consequence that the un-weighted average per address in the formula used for the calculations had to be replaced by the weighted average per grid square, the weight being the number of addresses in every grid square. So, the address density of a certain geographic unit was then calculated as the weighted average of the address density of the surrounding area for the grid squares in that geographic area, with the number of addresses in that grid square as weight (Den Dulk et al., 1992; Van de Stadt and Vliegen, 1993; Vliegen and Van de Stadt, 1994).

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2. Another strong impulse for the use of the grid system as a practical calculating tool in the modelling of concepts came from activities undertaken in the nineties for new Acts on the Municipal and Provincial Fund, organised by the Ministry of Finance and the Ministry of Home Affairs and Kingdom Relations.

(a) The first modelling of concepts in which the grid squares were involved, refers to measurable criteria for grasping the potential customers of local public facilities (Vliegen and Van Dosselaar, 1998). The idea behind that concept is simple. Cities and towns having a broader range of public facilities than suburbs or rural areas are financing those facilities not only for their own inhabitants but also for customers living in their surrounding areas without receiving payment for that service. From the viewpoint of local expenditures that situation is very unsatisfactory. It was, therefore, necessary to have a theoretical model for the estimation of the potential of customers of local public facilities in the various kinds of settlements that could be used as a funding criterion, so that municipalities with various kinds of public facilities should be financially compensated according to the broadness in the range of those facilities.

The theoretical model developed for that kind of estimation was borrowed from the attraction model of Huff representing consumer spatial behaviour in order to delineate retail trading areas and to define their potential customers (Huff, 1964). However, the theoretical model to be developed for estimating the potential of customers of local public facilities should also take into account the differences between the various public facilities in scale as well as in geographic range in the various settlements. Therefore, a distinction was made in the model between the estimation of the potential of customers of public facilities in settlements with a local impact and in settlements with a regional impact. In the local variant the range was limited to a distance of 20 km; the maximum distance in the regional variant was settled at 60 km. Moreover, it was also necessary to define the distance between those various settlements, since it was assumed that settlements of various size and geographic location would compete with each other.

After developing the theoretical attraction model and the formulas to be used for the calculations it was still necessary to define, among others the settlement and the distance between the settlements. And here the use of the grid system came in. After a thorough examination, a proxy for the continuous built-up areas based on the national grid system was chosen for the definition of the settlement. That proxy was developed in a pilot project by Statistics Netherlands a few years earlier for the delineation of localities. It was defined as a configuration of grid squares of 500 x 500 meter with at least 25 addresses per grid square which are contiguous at least at one side or as an isolated grid square with 25 addresses or more (Vliegen, 1993) . Only one amendment to this proxy was made by the relevant Ministries: they should not cross the boundaries of the municipalities for funding purposes. Proxies extending to the territory of two or more municipalities had, therefore, to be split up in two or more municipal settlements. Figure 3 shows that grid system with the municipal settlements.

The distance between the municipal settlements was defined as a straight line from the centre of one settlement to the centre of another settlement; the centre

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of a settlement being the centre of gravity of the grid squares forming the settlement, re-weighted for the number of addresses in every grid. Figure 3. Municipal settlements (grid-based proxies for the continuous built-up area) 2005

(b) The municipal settlements based on the grid system of proxies for the

municipal continuous built-up areas were as successful as an approximation of those settlements in reality that the number of the municipal settlements per municipality was included as a separate criterion in the new Act on Municipal Funding. Moreover, those proxies for the municipal continuous built-up areas were also included in that new Act as a diversifying factor for other criteria in that Act (BZK, 2006). The criteria for which that is the case, are:

- the area land; - the area covered by buildings; - the area covered with the soil characteristics of Holocene clay and

peat which are found up to a depth of 8 metres from ground level, with a cumulative thickness of at least five metres. These soil characteristics give namely rise to such specific expenditures by some local authorities that financial compensation for those expenditures is necessary.

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The calculations of all these very different kinds of areas are performed for the total territory of every municipality as well as for their settlements and sparsely populated areas separately. All those area calculation are performed in a GIS application by overlaying the relevant maps. These maps include (a) various selections from the topographical map (scale 1:10 000) of the Topographic Agency Cadastre, such as area land, area inland waters and area covered by buildings, (b) the map with the boundaries of the Holocene clay and peat from the Netherlands Institute of Applied GEOSIGNS TNO, (c) the map of the municipal boundaries of the Topographic Agency Cadastre and, finally, (d) the grid system with the grid squares of 500 x 500 meter with at least 25 addresses per grid square (Vliegen and Van Leeuwen, 1999).

(c) For the Act of the Provincial Fund still another criterion based on the grid system has been developed, namely the number of people living in an urban area and in a rural area in the relevant province. The urban area has been defined for this purpose as every grid square of 500 x 500 metres with an address density of the surrounding area of 1 500 addresses or more; the rural area as every grid square with an address density of the surrounding area with less than 1 000 addresses. Those concepts can be considered as derivatives from the concept of urbanisation as measured by the address density of the surrounding area at the level of the municipality mentioned above.

(d) It should be noted, finally, that the population statistics had also to be geometrically referenced for all applications of the grid system mentioned above under the present Acts of the Municipal and the Provincial Fund.

3. Interfaces for geographic Referencing Statistics Netherlands has at present a nearly complete system of interrelated interfaces for the various methods of geographical referencing of its statistical output described in the previous paragraph. That system has been built step by step during the last three to four decades. It consists of a set of administratively oriented registers with (geo-)codes and names and a set of polygons with boundaries with geo-codes. The present set of registers and polygons is summed up in scheme 1.

Scheme 1. System of interrelated geographic interfaces at Statistics Netherlands

Registers with (geo)codes and names

Polygons with Boundaries

Type of referencing Regionally Geographic Basic Register Postal District Register Territorial Subdivision Register Municipal Boundaries¹ Neighbourhood Register Neighbourhood Boundaries Spatially Population Cluster Register Population Cluster Boundaries Geometrically Geographic Basic Register Grid systems with various widths Address Co-ordinate Register ¹ Boundaries of other territorial subdivisions can be derived from the municipal boundaries in

combination with the codes from the Territorial Subdivision Register

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Regionally referencing of administrative source data can be done by three kinds of registers - the Geographic Basic Register, the Postal District Register and / or the Territorial Subdivision Register – or by a combination of those registers. The choice of which register(s) is (are) used for the referencing process depends on (a) the geographical component present in the source data, e.g. address, postcode or municipality, and on (b) the geographical level(s) at which the final statistics can ultimately be published. When the source data consists of digital maps, for example the Land-use map, the Topographical map, the National Road Map etc., regionally referencing of the relevant statistics can be done by overlaying those maps with the polygons of the Municipal or even the Neighbourhood Boundaries.

Analogically, administrative source data can be spatially referenced by the Population Cluster Register. There is only one restriction for this kind of referencing. The source data should contain the address or the most essential part of it, namely postcode and house number. No restriction adheres to the spatially referencing of statistics compiled from digital maps using the polygons of the Population Cluster Boundaries in a GIS environment.

Finally, administrative source data can be geometrically referenced in two ways, namely by (a) the Address Co-ordinate Register for referencing with the individual co-ordinate or by (b) the Geographic Basic Register for a referencing directly with the co-ordinate of the grid system of 500 x 500 metres. The address or the postcode in combination with the house number should be present in the source data here too. Geometrically referencing of statistics based on digital maps by grid systems of various widths can be done without any problem in a GIS environment.

An alternative way of regionally, spatially or geometrically referencing of administrative source data containing addresses is first, to reference those source data with the individual co-ordinate using the Address Co-ordinate Register and then as a next step, to link the co-ordinate of the reference data source alternatively with the polygons of the Municipal, Neighbourhood or Population Cluster Boundaries, or to whichever grid system.

Essential for the system of the geographically interfaces of registers and polygons are inter- linkages between various (geo-)codes, respectively polygons within every register / polygon system and between those registers / polygon systems. The most detailed administrative geographic interface is the Geographic Basis Register. That register contains all postal addresses in the Netherlands with basically the postcode, the name of the postal district, the municipal code, the municipal neighbourhood / district code as well as the geo-code of the grid square of 500 x 500 meter per address. The Postal District Register is basically derived from the Geographic Basic Register. It contains the codes of the postal districts and the municipal codes. The Neighbourhood Register contains the codes and names of the municipalities, their neighbourhoods and districts. The Territorial Subdivision Register contains the code and name of every municipality and the code and name of the particular region of the various territorial subdivisions to which that municipality belongs. All these registers are stemming from the first half of the eighties of the last century8.

The Address Co-ordinate Register was obtained only last year from the Cadastre. It contains basically the individual co-ordinate for every address with its postcode. The Population Cluster Register created also last year, contains an identification number and the name of every population cluster with its geometrical location and the code and the name of the

8 A more detailed description of all these registers can be found in Vliegen (1990). However, that

description is somewhat outdated with regard to the update and automation aspects of those registers, due to organisational and automation developments since then.

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municipally or municipalities to which that population cluster belongs. The geometrical location refers to the centre of gravity of its inhabitants (Vliegen et al, 2006).

The Polygons of the Municipal Boundaries are obtained since the end of the eighties from the Topographic Agency of the Cadastre. Those polygons contain also the official code of the several municipalities. The Polygons of the Neighbourhood Boundaries created at Statistics Netherlands at the beginning of the nineties, contain also the codes of the municipal neighbourhoods and districts as well as the code of the municipalities to which those neighbourhoods and districts belong. The polygons of the Municipal Boundaries of the Topographical Agency of the Cadastre and those of the Neighbourhood Boundaries of Statistics Netherlands are completely harmonised by integrating the municipal boundaries into the neighbourhood boundaries9.

The co-ordinates in the grid system and the co-ordinates of the polygons are the co-ordinates of the national system, the so-called ‘Rijksdriehoeksmeting’. The national co-ordinate system is since 2000 based on the European Reference system ETRS89. A final remark regards the status of the present system of geographic interfaces. It is not completed yet and probably it will never be nearing completion. Possibly, other regionally and particularly, spatially interfaces will be necessary already soon in the near future, depending on the articulation of new needs of users for statistics at a particular regional or spatial level. The only prohibitive factor could be the technical availability of the necessary geo-data for the compilation of such statistics. Purely technical prerequisites are no obstacle anymore for the development of such interfaces. The manageability of GIS software has been strongly improved, technically as well as organisationally. Moreover, Statistics Netherlands can get gratuitously access to geo-data of public authorities, public organisations or public services, since the possibility of getting access to all kinds of content data in public databases is legally defined. By combining various maps with geo-data, such as the topographical map and the National Road map, and the Address Co-ordinate Register, for instance, it would be relatively easy to create now already a geographic interface for street blocks – which interface at its turn, could be interlinked with the addresses from the Geographic Basic Register. Another spatially oriented geographic interface could be a Basin Register by combining the Address Co-ordinate Register with the Polygons of those Basins. Statistics on this spatial level would be particularly for the Netherlands very relevant.

4. Geographical analyses and standardised interfaces Before answering the question of standardised interfaces for geographical analyses one should keep first two other questions in mind. A first question refers to the demand of the users of geographical data for such analyses on the one hand in relation to the supply of such data by the statistician on the other hand. The second question to keep in mind relates to the informational and technological developments which are already influencing the statistical processes or may be doing so still more in the near future.

Looking at the demands by users for statistical data at a geographical level one may roughly distinguish three categories of such users. A first category of users are policy makers in the regional field. Those policy makers may be situated at the level of the central, regional or local government. They may want to perform geographical analyses in view of making

9 A more detail description of the harmonisation of both kinds of polygons can be found in Van Beek

et al (1994). The automated process described in that article has been changed since then, due to the rapid developments in the GIS technology.

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regional or local policies or in order to monitor regional or local policies they decided already upon. In both cases the kind of policies pursued will define the geographical level(s) of the statistical data they demand for. The geographical levels mostly used are here of a regional normative kind.

A second category of users are the regional scientists. They do mostly not ask for data of a regional normative kind for their geographical analyses, but statistical data at a regional analytical level, a spatial level or a geometrical level.

The last kind of users I would like to call the business community. Those users are mostly interested in regional areas where they can set up their firms or where they can sale their products. They are using mostly data at administrative levels for their geographical analyses which are often of a different kind than the levels the policy makers are asking for.

The conclusion from these various demands should be evident for regional statisticians trying to supply statistics for those various kinds of users. Those statisticians will be forced to compile statistics at various geographical levels in order to cope with those different demands. Consequently, the regional statistician will be in want of various geographical interfaces to do his job adequately.

The informational and technological developments which are already influencing the statistical processes or may be doing so are also of various kinds. A regional statistician working in a National Statistical Office has to take into consideration, first of all, the informational developments influencing the statistical processes at the national level. In the case of the Netherlands, for example, such a development is the creation of a Social Statistical Database, which contains now already coherent and detailed information on persons, households, jobs and social benefits. It is created by micro-linkage and micro-integration of demographic and socio-economic data from a wide variety of administrative registers and sample surveys (Linder, 2004).

Second, the regional statistician should also be attentive to informational developments outside his office which can be used for the compilation of relevant statistics. Such developments are the availability of more and more administrative registers at public authorities, public organisations and public services. Again in the Netherlands, for example, projects at the public level are on the way to create various authentic registers. At present they refer already to the developments of Basic Registers of Persons (an improvement of the present population register), a Basic Register of Companies and Organisations, A Basic Register of Buildings and Addresses, a Basic Cadastral Register and a Basic Topographic Register. All these Registers will be based on legal Acts and will be realised within two or three years.

Finally, the regional statistician should be aware of technological developments, particularly in the field of Geographical Information Systems (GIS). The use of GIS is already widely spread. Until now it is, unfortunately, often only restricted to the presentation of statistical data or to the storage of geographical data. Geographical Information Systems should, however, more and more also be used as an instrument for the compilation of statistics from data sources with geo-information or digital maps with relevant topographical data for statistics. Some examples of that kind of use in the Netherlands have been given in the previous section. Which conclusions can now be drawn from those considerations with regard to the question of standardised interfaces for geographical analyses?

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First, the creation of one and only one standardised interface will not be possible. As we have seen above, various kinds of users require their own geographical levels in statistics in order to perform their own analyses from their own perspectives or purposes. In other words, those various users want to use various kinds of regionally, spatially and geometrically referenced statistics. Regionally, spatially and geometrically referencing processes are, however, often mutually not compatible with each other in their results. Moreover, an incompatibility exists between the geographically referencing processes even within each of those types.

Second, existing geographically referencing systems have to be considered as ‘snapshots’ in view of an ongoing process of informational and technological developments. At least two kinds of geographical referencing exist since the development of Geographical Information Systems, namely (a) an administrative one in the form of registers with administrative codes and names and (b) a geographical one in the form of polygons with codes and eventually names. Both systems have ‘their raison d’être’, since the source data for the compilation of statistics are different in form.

Third, looking at the present state of the art one could at most try to co-ordinate both systems of geographically referencing in such a way that the standardised interface could consist of an Address Co-ordinate Register in combination with a set of polygons for the boundaries of the various regional and spatial subdivisions. In such a situation one could possibly derive the other administratively oriented registers with codes and names from the combination of the Address Co-ordinate Register and the various polygons by plotting the individual co-ordinate into those polygons. The polygons should then be organised in such a matter that administrative code and names can be attached to those polygons.

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