Category Archives: Analysis

Bührers’ professions over time

What kind of work did the Bührers live off? A total of 815 Bührers in the dataset (10% of which are women) have profession information ranging from general titles such as “farmer” to  very specific ones like “advanced planning manager at funeral home”.

Distribution of professions among Bührers

Professions have been coded with the Historical International Standard Classification of Occupations (HISCO) Tree of Occupational Groups, with modified category names to convey the predominant characteristic of the groups (categories 0-1, 7-9). The number of persons per time slice ranges from 23 (born prior 1750), 63 (born after 1750) up to 262 (born after 1850).

What comes as a surprise is the relatively low share of farmers (category 6) that never exceeded 20%. For most of the time there is a predominant share of production jobs, especially in the 18th and 19th century. Their nature, however, changed over time: e.g. from shoemakers to mechanics (category 8) or carpenters to factory workers (category 9). Not surprisingly some professions have ceased to exist, e.g. “Schalenmacher” (wooden bowl maker).
Women prior the 20th century had expected “woman professions” such as seamstress or nurse, with the odd teacher towards the end of the 19th century. It is only in the 20th century when “Professional, technical and related workers” (categories 0 & 1) become predominant occupations.

There is a clear bias to record/know professions with higher status, e.g. the “Vogt” (the equivalent of a bailiff) that features 6 times for the time slice up to 1750; the same holds true for other professions in the category 2 Administration/Mgmt such as “Gemeindepräsident” (mayor).

What does “family” mean or how related emigrated Bührers are to me

Back in 2011 when I started working with the Bührer dataset it was clear to me that all the emigrated Bührers are “family”, i.e. are more or less closely related to me. A first glimpse at the map’s family tree in 2015 showed that this assumption is somewhat shaky – most of the emigrated Bührers are rather distant relatives.

Degrees of relationship relative to me

A renewed look (see above) gives a more precise picture: relative to me (generation and degree of relationship = 0) the closest emigrated relative is Michael Bührer (generation = 5, degree of relationship = 6) who directly descends from the 10th generation of my direct line of ancestors. The degree of relationship of US persons (living or dead) ranges from 6th to 11th degree. Not that related after all…

Note that indicated degree of relationship according to my calculation (I didn’t find an authoritative source on how to calculate it) doesn’t increase in direct descendancy unless the generation is below 0.

Showing migration flows

The migration flows of the Bührers lend itself to visualisation with a chord plot, done with R‘s circlize package after a post by Guy Abel.

Bührer migration flows

The plot shows migration flows between regions as well as flows within a region that exceed 200 km. “Regions” are essentially place clusters that have been visually identified on the map. It includes all persons born as Bührer (“Named”) from the dataset, where migration can be inferred based on georeferenced events. Note that a particular person can feature in several flows, e.g. first emigrating to northwestern Ohio with a subsequent migration to Kansas.

In contrast to my maps – that only show the United States – you can also see that some Bührers emigrated to Brazil (around Curitiba) as well as India (Mangalore). Either migration is likely to predate the known emigration to the United States.

Analyzing the Bührer dataset

What data of the available Bührer dataset actually made it on one of the maps? A mosaic plot, done with the vcd package from the open source statistical software R (, gives a quick overview over the relevant factors.

Mosaic plot of the Bührer dataset
Mosaic plot of the Bührer dataset

The plot essentially shows areas proportional to the number of persons, ordered by the emigration status (left) and map # (top). For a given combination the successive blocks in the color red, black and grey denote Named, Married and Descendants persons respectively (see The methodology – preparing genealogical data for maps for explanations). These three categories make up roughly 4’500 persons of the original dataset, with the remainder not being shown. The small circles denote combinations that didn’t occur in the dataset.

A few observations:

  • Only a small fraction of persons in the dataset actually show up on map 1 and 2. This is comes as no surprise, given the large number of e.g. Swiss-based Bührers, “Assumed US” persons as known descendants of emigrants with no place information or “Undetermined” persons where location information could neither be determined nor inferred.
  • The number of Bührers emigrating for the generation prior 1880 (map 1) is significantly larger than the number of emigrating spouses from Switzerland, reflecting the fact that most married once overseas. A look at the category “Third country emigrated to US” indicates that a substantial part of the Bührers – at least for the first generation – preferred to marry other emigrants.
  • There’s very little Bührer emigration happening for the generations born after 1880 (map 2) – almost all Bührers in that period are America-born.

The plot has featured in a small presentation R User Meetup Mosaic plot Thomas Roth 20160803 (includes the R code) in a Zurich R User Group Meetup.

Plotting the map’s family tree

The – with 13 A3 pages very wide – family tree (Family Tree of Emigrated Buehrers) shows all persons that emigrated to the United States including their ancestors as well as their immediate relatives. Persons are aligned horizontally by generation, with oldest generations on the top. Squares denote males, circles females and triangles marriages. Persons represented by black line symbols are shown on the map whereas those with grey line symbols are not. Otherwise symbology follows the one for the map, i.e. line styling indicates category and colours show common male ancestors.

Family Tree of Emigrated Buehrers - Detail
Detail of the family tree of emigrated Bührers

Data for the family tree was prepared in the project’s PostgreSQL database stripping irrelevant persons and families. The family tree was drawn in yEd ( in “Family Tree” mode and styled via Properties Mapper.

The methodology – preparing genealogical data for maps

The production of the map showing the emigration of Bührers from Switzerland to the United States relied on the following, largely self-developed sequential steps:

  • Normalization, completion and geocoding of places used for family and persons events
  • Identification and categorization of in-scope persons, notably persons born as Bührer or name varieties such as Buehrer (“Named”), spouses (“Married”) and their children/grandchildren (“Descendant”) that have different family names
  • Constructing a sequence of geocoded events for a person’s life, also considering childbirth for women. In case geocoded events lacked dates a natural sequence was assumed, i.e. birth followed by marriage, childbirth, death and burial.
  • Determination of an emigration/residence status relative to Switzerland, the US or third countries. Of particular interest were those that emigrated to the US as well as confirmed or assumed US residents
  • Determination of a common male ancestor for all Bührers that emigrated or have lived in the US and the generation relative to him
  • Deriving a family status for emigrants, i.e. whether emigrants emigrated as single, with their spouse or family
  • Assignment of persons to a time period (generations prior/beyond 1880) based on known birth years, ensuring a consistent assignment of couples and siblings to the same period
  • Construction of migration path segments following the sequence of geocoded events
  • Aggregation of migration paths per county and time period, including aggregated indicators such as the category of in-scope person with Bührer prevailing and the minimal generation involved
Geocoding places in MacFamilyTree
Geocoding places in MacFamilyTree
Sample PostgreSQL script
Sample PostgreSQL script (categorization of in-scope persons)