Parts and Places: The Structures of Spatial Representation (Bradford Books)
An ontology, meaning a semantic structure defining named entities, and explicit and typed relationships, can be constructed in the absence of locational data, and spatial objects can be attached to this structure if and when they become available. The first includes the linked systems of Poor Law unions and registration districts in 19th century England and Wales, in which most but not all unions and districts were coterminous. The second case study includes the international system of nation-states, in which most units do not appear from nothing, but rather gain or lose independence.
We show that a relatively simple data model is able to represent much historical complexity. Introduction History is concerned not just with the past but specifically with the interpretation of documentary sources, distinguishing it from archaeology. Some historical documents are maps, but their depiction of relative locations cannot be assumed to be accurate.
Such gazetteers generally derive directly from topographic mapping, with feature typing derived from map symbologies. However, they are often poorly suited to historical use.
One problem is that toponyms rarely work as unique identifiers, so a particular name may refer to many different locations, and a particular location will commonly have multiple names, sometimes in multiple languages and changing in importance over time. More complex structures are clearly required, with multiple toponyms per feature, detailed source information for each toponym and, to disambiguate common names, some notion of hierarchy. A specifically historical agenda for gazetteer research was set out by Southall et al. Firstly, while digital boundaries for modern units are usually available from government, these generally cover only the last 30 to 50 years, and while very detailed paper boundary mapping is often available for the last or more years, digitization is very time consuming and expensive.
Secondly, boundaries may have been well-defined in periods well before they were mapped, but either no record exists at all, or there is only a textual description, from which it is even harder to construct a polygon; the US Atlas of Historical County Boundaries was constructed this way, but took decades [ 3 ].
Thirdly, as they go back further in time, historians increasingly encounter units listed in, for example, taxation records, whose geographical location is unknown, other than through their being part of some higher level unit. For all these reasons, building a knowledge base of historical administrative units as a conventional polygon-centered GIS is inappropriate. Digitization costs alone mean that at least our initial system needs to be based primarily on textual sources, and therefore must be a primarily semantic structure to which we can add geospatial data as it becomes available.
There are two broad models of knowledge organization systems for holding such information: thesauri and ontologies. Ontologies differ firstly by being more concerned with fundamental concepts, and secondly and more practically through a greater concern with relationships. The re-naming reflects the system including significant non-British content, as discussed below, and the re-launched system will also include API access at data. A number of other projects have taken broadly similar approaches. Kauppinen et al. Lacasta et al. The AUO, and the overall historical GIS that it is part of, have already been described at length [ 11 , 12 , 13 ], while Aucott et al.
The next section summarizes the database architecture, but at this level, the system is extremely abstract: it defines entities that can have various names, and have various kinds of relationships with other entities.
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For example, this structure could just as easily hold information on people and their family trees. Therefore, the main focus here is on the next level of generality, where particular administrative geographies are defined. The presentation is primarily through two detailed cases studies. Section 3 describes the representation of the system of Poor Law unions and registration districts, which were the most important statistical reporting units in late 19th century Britain, and the focus of the earliest work of the GB Historical GIS.
This paper is about the actual knowledge content, not about particular representations. In what follows, we focus on the internal representation of the data within a Postgres object-relational database using the PostGIS spatial extension.
The scripting enabled the system to include dates despite the complete lack of support for a time dimension in the underlying software. Then, a more conventional polygon coverage could be constructed for a given date by selecting those label points whose period of existence included the target date, and building polygons around them from the arcs that existed at the target date.
Statistical data were held in a separate Oracle database that could be accessed from ArcGIS, and linked to via the names held in the label points [ 17 , 18 ]. One limitation of this architecture was that construction was very time consuming, especially given the need to ensure that a valid polygon topology was in fact buildable for a full range of dates.
This meant that GIS construction often lagged far behind statistical transcription, and one major analytic project had to develop a quite different methodology for analyzing mortality decline in 20th century Britain [ 19 , 20 ]. Another limitation was that the GIS held just one name for each unit, while the historical sources often contained valid alternate spellings. The temporary solution was to include abbreviated county names within brackets in the labels for just these units, but it was increasingly obvious that a more systematic approach was needed for variant and ambiguous unit names.
This problem was shared with the archives sector in the UK, which—unlike libraries—routinely index by place, meaning not some GIS-based method but alphabetic indexing by place name, traditionally using index cards and now in specialized collections management software. In , the GB Historical GIS received new funding from the UK National Lottery, both to make our statistical data available to the general public, especially as local time series, and to provide an online name authority for the archives sector based on computerizing the existing authorities; meeting both goals with a single system.
The volumes are organized geographically by county; then, each county is sub-divided into entries for parishes, the most enduring and generally the most detailed administrative geography. In brief, the units table enumerates all the units of all types, but holds little information about them other than dates of creation and abolition, if known. The names table holds all the names that units are or were known by.
The use of the status table is discussed below. All the tables include start and end dates, and all the rows in all the tables are required to include authority identifiers linking to a single central table of authorities: all information must be attributed to a specific source. This detailed documentation of sources is almost impossible in traditional GIS, due to the very widely used Shapefile imposing a character limit on any annotations. A complete UML diagram for the AUO has been published elsewhere [ 12 ], and the system includes two additional types of table, which are both much smaller.
Secondly, the only major changes to this architecture since it was defined in — were under the QVIZ project in —, when the system was internationalized: an existing table identifying the languages used in names was extended, and several tables added to enable explanatory text to be held in multiple languages [ 14 , 24 ]. To understand the actual use of the system as an administrative unit ontology, and especially the use of unit types and status, we need to consider specific examples.
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Poor Law unions replaced the administration of poor relief by individual parishes in the first half of the 19th century. Central to the system was the Poor Law Commission, acting as a single authority across the whole country, and replacing the disjointed and self-governing local schemes [ 26 ]. However, in practice, the commission was operating a policy incorporating a string of compromises negotiated between different official boards at both national and local levels [ 27 ].
This national system governed by a single set of homogeneous rules was enforced locally by a Board of Guardians—or, prior to their establishment, other specific local act bodies until such boards could be created [ 28 ].
Mental representation, conceptual spaces and metaphors
Initial progress in implementing the new system was quick. However, because the unions were implemented alongside existing incorporations and Gilbert Unions, which were not spatially contiguous, inconsistencies resulted in provision, governance, and reporting in certain areas of the country.
Thus, the Act and subsequent Poor Law policies were shaped by both the existing geography of Poor Law provision and subsequent social development [ 27 ].
A series of acts following on from tried to alleviate the compatibility issues and consolidate these differing local entities into a single system. While the original act was amended several times, reform was never satisfactorily completed, and eventually led to all unions being abolished in under the Local Government Act of 19 and 20 Geo V, c.
This makes boundary changes over time difficult to document fully. The system of registration districts in England and Wales was similarly imposed by central government in to record births, marriages, and deaths independently from the Church of England. It was introduced following two Acts; the Marriage Act 6 and 7 Will.
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Registration districts were and are the spatial units for the compulsory recording of all vital events for the entire population by the Registrar General. Additionally, they were used as the primary reporting geography for the Census of Population between — Scotland had a separate system of registration districts introduced in , which is not covered here. Each unit was defined primarily in terms of its component parishes, although urban sub-districts could be sub-divisions of parishes.
The registration district geography generally followed the Poor Law union geography, enabling the two systems to share buildings and officials, but as discussed below, there were significant differences in particular localities. Registration districts and Poor Law unions were the very first administrative units to have their boundaries mapped by the GB Historical GIS Project, working in the mids. Our work developed out of the Labour Markets Database [ 29 ], which focused on measures of economic distress, and our immediate aim was not to map census data at yearly intervals, but to map and analyze Poor Law statistics, which are reported twice a year [ 30 ], and vital registration data, especially marriage statistics, which are reported annually.
Southall and Gilbert [ 31 ] showed that fluctuations in the marriage rate varied closely with the state of local economies. Requiring mapping for so many different dates justified the development of a unique time-variant architecture [ 18 ], rather than following earlier projects in constructing conventional GIS coverage for each census. However, our need to compute rates meant that we needed to be able to link in counts taken from the Census of Population for use as divisors.