Widows in Venice

Introduction

This project examines the socio-economic status and property dynamics of widows in the 18th- and early 19th-century Venice, focusing on two historical datasets: the Catastici and the Sommarioni. By analyzing these records, the project aims to uncover patterns in property ownership, tenancy, and rent payments, providing insights into widows’ roles and lives during this period.

The analysis focuses on identifying widows within the datasets and gathering key information such as property ownership, tenancy status, and rent values. It also compares trends across the two time periods to explore changes in widows’ economic circumstances. Specific questions include whether widows were more likely to own or rent properties and whether their properties differed in size or value from others.

Historical background

The project focuses on Venice during the period 1740–1808, a time marked by significant social and political changes. This era includes the dramatic Fall of the Republic of Venice to Napoleon in 1797, ending over a thousand years of independence. Unlike earlier centuries, the late 18th century was not plagued by major epidemics, allowing for relative demographic stability.

Venetian society in this period was structured by rigid gender roles and a hierarchical class system. At the top were the patricians, followed by citizens (popolani), and finally the commoners. These divisions were formalized through records like the libro d'Oro, which documented the city’s elite families. Social mobility was limited, and class often determined one's opportunities and rights within the Republic.

As in many European cities at the time, Jews were the only people allowed to lend money. They were forced to live in a Ghetto and paid expensive taxes to the city. During night they were locked in the Ghetto.

This historical context provides a backdrop for the analysis, offering insight into the societal structures, class dynamics, and economic realities that shaped the lives of Venetians, particularly widows, during this transformative period.

Motivation

Word cloud of all the tokens present in the Catastici that are not names

The situation of women in historical patriarchal societies is often difficult to fully understand. Their names are frequently only found in historical records when linked to male relatives, as women were long considered dependent on their fathers and later their husbands, with fewer rights than men. Wives were often referred to by their husband's name (e.g., Mrs. Leonardo Rossi would refer to Sofia Bianchi after marriage). Widows often faced the same fate, with their identities obscured or even forgotten.

This historical trend is evident in official documents like the Catastici and the Sommarioni, which list property owners. These records are dominated by male nouns and adjectives, as seen in the Word Cloud. However, it is interesting to note that a few female nouns and adjectives do appear, with widows among them. A closer examination of these widows can provide valuable, quantifiable insights into gender roles and the economic and cultural relationships in 18th-century Venice.

Project Plan and Milestones

The project is structured on a weekly basis, to ensure an even progression and workload. Each week has a clearly defined goal. The plan spans from the initial setup and data extraction through to final analysis and presentation, with clear milestones throughout.

The first phase of the project (07.10 - 13.10) is focused on defining the project's scope and structure. Here the focus was on creating a common understanding of the project to ensure good collaboration in the group. The following week data extraction of the widows in the two datasets started. In addition a review of historical papers on widows and Venice was done, providing the necessary context for the research (14.10 - 20.10). The analysis then shifted towards examining the widows mentioned in the Sommarioni and Catastici records. This stage involved comparative rent analysis and property ownership evaluation (8.10 - 03.11).

The mid-project milestones included a midterm presentation on 14.11, with further development of the analysis through the end of November (11.11 - 24.11). This phase focused on completing the property ownership and comparative rent analyses, as well as beginning to explore widow heritage and social aspects, such as the frequency of titles like "Vedova" and "Consorte" used in the records. These findings were progressively written into a shared wiki.

The final analysis phase, beginning 02.12, was dedicated to comparing the results of the previously conducted analyses, and identifying overarching trends related to widows in Venetian society. The last steps of the project (09.12 - 15.12) will involve finishing the wiki documentation and preparing the final presentation.

The project will conclude with the delivery of the GitHub repository and wiki on 18.12, followed by the final presentation on 19.12.

For a detailed overview of the workflow and corresponding milestones, see the table below.

Workflow

Week	Task
07.10 - 13.10	Define project and structure work
14.10 - 20.10	Write code to extract widow data Read historical papers on widows and Venice
21.10 - 27.10	Autumn vacation
28.10 - 03.11	Comparative rent analysis (catastici) Property ownership Heritage
04.11 - 10.11	Analysis: - Property ownership - Comparative rent analysis Prepare for the presentation
11.11 - 17.11	Midterm presentation on 14.11 Continue analysis
18.11 - 24.11	Finish property ownership analysis - Sommarioni & Catastici Finish comparative rent analysis - Catastici
25.11 - 01.12	Start widow heritage analysis
02.12 - 08.12	Compare all analyses to identify general trends for widows Interpret some of the results
09.12 - 15.12	Finish writing the wiki Prepare the presentation
16.12 - 22.12	Deliver GitHub + wiki on 18.12 Final presentation on 19.12

Dataset presentation

For this project, two primary datasets are used as the foundation for the analysis, the Catastici and the Sommarioni. These historical records provide information about property ownership, income, and land use in Venice.

Catastici

Catastici

The Catastici is a historical register from 1740 comprising 32'123 property records, collected through door-to-door surveys within a parish. The sequence of entries reflects the route taken during data collection. The original register contains five main columns of information:

• Owner information
• Tenants
• Income from rent
• Place name
• Urban function

The entries vary in detail, as there was no strict data format. Some records are highly detailed, while others lack certain information. During standardization and digitization, additional columns were created to improve data usability, such as Family Name and Owner Title.

For analysis, the transcription version "catastici_text_data_20240924.json" is used. This dataset includes both the original and standardized columns.

Sommarioni

Sommarioni

The Sommarioni is a cadaster from 1808, documenting properties and parcels in Venice alongside their assigned parcel numbers. In total it has 23,400 entries. The dataset is tabular and contains the following core information:

• Parcel Number: Corresponding to a specific property
• Owner Information: Listing the property owner
• Quality: Describing the function or use of the property

Similar to the Catastici, additional columns were added post-digitization to capture supplementary details. Unlike the Catastici, the Sommarioni does not include information about tenants of rented properties. For the analysis the dataset "sommarioni_text_data_20240709.json" was used.

Methodology

Property ownership analysis

For the property ownership analysis for the widows mentioned in the Catastici and Sommarioni a similar approach was used. First the widows were located in the relevant columns using the keywords "vedova" (literally widow) and "relicta" (etymologically: "person left behind"), and "consorte" (meaning wife of dead husband). After filtering the datasets using row-wise text matching for these keywords, the entries of the widows were saved. These new datasets were then used as the basis of further analysis. A distant reading methodology of the data was done by counting and and creating distributions of different variables given in the data. When counting properties, uniqueness of each property was ensured by the unique identification number of the parcel provided in the dataset. For ensuring uniqueness in widows, this was done for both datasets manually and by using likeness of standardized names.

Heritage Analysis

To explore inheritance patterns of widow-owned properties in Venetian records, two following two approaches were used.

Linking Catastici to Sommarioni

Properties owned by widows in the Catastici were linked to entries in the Sommarioni through matching the "id_napo" from the Catastici to the corresponding parcel numbers in the Sommarioni. For this analysis only the widows mentioned as "vedova" or "consorte" in the Catastici was used.

Due to the limited amount of data available, only 16 entries with an id_napo in the Catastici, manual inspection was conducted to identify familial connections.

Linking Sommarioni to Catastici

Properties listed in the Sommarioni were traced back to the Catastici using parcel numbers and name similarity.

Using the parcel numbers from the Sommarioni, they were linked with the id_napo of the Catastici. Using this method 388 links were found. To check for familiar relations between the owners a name similarity analysis was conducted. Here computational tools like difflib were used to compare widow names between datasets, accounting for spelling variations (e.g., "Bonvicini" vs. "Bonbicini"). A similarity threshold of 0.7 was applied, resulting in 269 mathces.

This methodology allowed for a combination of qualitative and quantitative analysis, addressing historical inconsistencies while exploring inheritance patterns across records.

Rent Analysis

For the rent analysis the following methodology was applied.

Before analyzing the rent, the different currencies had to be converted into lirae. For this the following conversion table was used. When a currency was not specified, the currency ducato was assumed. [13] [14] [15]

Venetian Currency Conversion

Currency	Value in Denari
1 Ducato	1488
1 Lira	240
1 Grosso	62
1 Soldo	12

To see if widows owned or rented multiple properties, their names were used to analyse. For the following rent analysis nobles were also extraced through a set of keywords ('nobil', 'conte', 'cavaliere', 'marchese', 'duca', 'principe', 'barone', 'illustrissima', 'illustrissimo'). In addition the Jewish Ghetto was extracted. The reason for highlighting these is because factors such as nobility and religion can potentially impact the rent.

Instances of charity was identified as properties where no rent is paid in money. This means that the quality_income column contains a reasonable justification ('gratis', 'amor dei') and there is no quantity_income. This made it possible to compare charity towards widows against charity in Venice in general.

The median rent was used as a robust estimator of economical situations for widow-owned properties and widow-rented properties, at the scale of Venice, at the scale of each district and at the scale of each parish. The difference between the median rent of an area and the median rent of widow owners and tenants in the same area was computed and the results of this is listed in the following tables. This information was then compared to geographical observations by plotting properties geographically, highlighting the widows using different shapes, the nobility with edges and size and the parishes with lines.

Results

Property Ownership Analysis

Catastici Property Analysis

Widows extraction in the Catastici

Using the methods described in the Property ownership analysis, a total of 312 unique mentions of widows were identified in the Catastici out of the 33'297 entries. Widows names were identified when they were mentioned as either "Relicta", "Vedova" or "Consorte" in the column of owner names or in the column of tenants names. Since one widow can own or rent several properties, instance were counted with and without repeats. In the tables below, counts of all mentions of widows as "relicta", "vedova" and "consorte" are displayed with and without repeats.

Number of mentions of Vedova and Consorte

Mentioned As	Owner Name	Tenant Name	Total mentions
Relicta	157	124	281
Vedova	25	54	79
Consorte	36	5	41
Total	218	183	401

Number of unique mentions of Vedova and Consorte

Mentioned As	Owner Name	Tenant Name	Total mentions
Relicta	95	116	281
Vedova	22	49	71
Consorte	29	5	34
Total	146	170	316

Antonia Franchini

As mentioned above, in total, 312 unique names of widows were identified. However, adding each count of unique instances of all keywords for both owners and tenants results to 316 instances, meaning four more instance than expected (see the tables above). This difference is due to a few widows in the Catastici who owned and rented different properties: Antonia Franchini vedova, Antonia relicta del quondam Giovanni Battista Rota and Raca relicta Vita Sachi. For instance, in 1740, Antonia Franchini was apparently renting a house and a fruit roll shop (casa e bogetta da frutaroll) owned by Nobil Domina Chiara Moro Zen. The property Antonia Franchini owned was an inviamento located in Cannaregio and was not rented to anyone.

Properties owned and rented by widows in the Catastici

It is intuitive to think that some widows could own several properties. On the same note, some widows could rent several properties. Following this idea, the number of widows owning or renting several properties was computed and their distribution is shown in the barplots below.

As expected most widows in the Catastici owned one single property (134/145 widow owners). Eleven of them, however, stand out and revealed to own more than one property, even up to more than twenty properties. These eleven particular widows could be extracted and their names of the four top of them are displayed in the table below. Similarly, one could think that people would most commonly rent one single property, which is the case for most of the widows (160/170 widow tenants). For ten of them, several properties are rented under their name, up to four properties for one of them. These widows' names are displayed in the table below.

Widows' Name	Number of Owned Properties
Nobil Domina Leonora Corner relicta Lorenzo Gabriel	23
Marina Saggio relicta del quondam Alvise	9
Maria Rizzardi relicta quondam Francesco Lizzini	8
Nobil Domina Perina Capello consorte del Nobil Homo Ser Polo	5

Widows' Name	Number of Rented Properties
Domenica Persego vedova Domino Val[azzo]	4
Lucia relicta del quondam Nicolò Da Gai	3
Antonia relicta del quondam Giovanni Battista Rota	2

Leonora Corner and Perina Capello

According to the counts calculated in our pipeline, Leonora Corner was the widow who owned the most properties in Venice in 1740. By looking at the 23 properties owned by Leonora Corner, this study identified that she was renting all of them to various prices and that all of them are located in the district Santa Corce. Considering her wealth and that she is also referred to as a Nobil Domina, it is likely that she had a great influence at that time. Interestingly though, when looking at the properties owned by Perina Capello whose was thought to own only five properties, this study could extract 25 additional properties that Perina Capello owned but for which she was mentioned as Nobil Domina Perina Capello and not consorte del Nobil Homo Ser Polo. This discovery makes her the actual noble widow owning the most properties in Venice this study could extract. Interestingly, the five properties where she is mentioned as a consorte are all located in Santa Croce and most of them are houses (casa and casetta) that she rented to both males and females. All her other properties were located in a different district: Dorsoduro.

Widows' Distribution across Venice districts

Districts of Venice

Through history, the construction and inhabitation of cities followed population dynamics, creating clusters of people related to their social and economical situation. One can learn a lot about a group and a population just by looking at their spacial distribution. In this optic, this study compared the spatial distribution of properties owned and rented by widows across Venice's districts with the global distribution of properties in Venice. The Figure below illustrates the results obtained when computing this data.

In the first panel of the graph below ("Property Owners") the distribution of owned properties across the district of the entire population tells us that regarding the total population of Venice, the district with the most owned properties in is Cannaregio where nearly 18% of the owned properties are found. On the contrary, the district with the less owned properties is the Ghetto Novossimo, which contains only 2% of the total owned properties. These observations make sense since Cannaregio and the Ghetto represent, respectively, the largest and the smallest area of the city of Venice, which directly affects the number of properties they can contain which thus affects the proportion of properties that can be owned in the first place. This study also computed the repartition of properties owned by widows across the district which revealed a completely different distribution. For instance, while Cannaregio represented 18% of the total owned properties, for properties owned by widows, only 9% of them are located in this district. Similarly, while the Ghetto represented only 2% of the total owned properties, for widows, this district contains nearly 7% of all the properties that are owned by widows.

To compare the difference in repartition between widows and global population, this study computed the ratios of the proportion of properties owned by widows in a district over the proportion the same district represents in the entire population. The results are shown in the second panel of the Figure below ("Relative Proportion of Properties Owned by Widows in each District"). If this ratio is equal to 1, this means that the proportion of properties owned in this district is the same for widows as for the global population. If this ratio is greater that 1, notably for the Ghetto Novossimo and Santa Croce whose ratios are respectively equal to 3.3 and 1.6, it means that the proportions of properties owned by widows in each district are equal to 3.3 and 1.6 times the global proportion.

These operations were also done on the rented properties, as shown in the last two panels of the figure below. From these, one can establish that properties rented by widows are also more present in Ghetto Novossimo and Santa Croce than the global population. In "Castello" however, the ratio is very close to one, meaning among all properties rented by widows, the proportion of them that are in Castello is approximately the same as the expected proportion of properties in Castello.

Note that the Ghetto is not exactly considered as a district, but more as part of Cannaregio. It however made sense to take it as a separate district considering the important impact it had on the distribution of the widow-owned and rented properties among the population.

Sommarioni Property Analysis

Using the methods described in Property ownership analysis, the study identified 659 entries related to widows out of a total of 23,400 entries in the Sommarioni. Since this dataset includes only property owners and excludes tenants, no conclusions can be drawn about the amount of widows renting properties.

Ownership Distribution

When looking at how many properties one widow holds, it is important to ensure that it is the same widow. When comparing the data it appears that in the 'owner' category there are 443 unique owners, whilst in the 'owner_standardised' there are only 360 unique widows. This means that there must be different spellings and errors in the way the widows are written in the 'owner' section compared to the cleaned and standardized section, which is as expected. When looking at the new list of widows, it is still possible to see the same widows, but written differently and further refinement is therefore necessary. After looking for similarities in the names, there are 246 unique widows.

Most widows own a single property, as illustrated in the histogram, which shows an exponential decrease in ownership frequency with increasing property counts.

From the data:

• The majority of widows own one property.
• The graph shows similarities to an exponential decay.
• The maximum observed ownership is 25 properties, held by Loredana Grimani, wife of Giovanni Morosini.

Loredana Grimani

Loredana Grimani is the widow holding the most properties in Venice in 1808. This exceptional case may indicate significant wealth, and further investigation into the Grimani-Morosini family could provide more context. From the presentation given on the Venice Data [16], there is a graph from showing the distribution of family ownership - weighted by ownership portion. The graph, based on Catastici data, highlights that both the Morosini and Grimani families controlled a significant share of Venetian properties during this period. It is reasonable to assume that by the time of the Sommarioni in 1808, the Grimani family’s property holdings had remained relatively stable.

Geographic Distribution of Widow-Owned Properties

The graph compares the proportion of properties owned by widows to those owned by the general population in each district. This comparison reveals significant regional differences:

• In Cannaregio, widows own a disproportionately large share of properties compared to the general population.
• In Castello, widow property ownership is notably lower than that of the general population.
• In Dorsoduro, San Marco, and San Paolo, widows own slightly more properties than average, while in Santa Croce, widows own slightly fewer properties.

These findings suggest that socio-economic and demographic factors may influence the distribution of widow property ownership across districts.

• 

  Fraction of properties owned by widows and people per district

• 

  Normalised average area of properties owned by widows in a given district

Property Size and Wealth Indicators

The figure shows what the average area of a property owned by a widows in a given district is, normalized by the average area of the properties in that district. This might give an indication of the wealth of the different districts. Though it has to be said, that the area given in the Sommarioni is likely computed from the vectorization available in the GeoJSON file.

Key observations include:

• In Castello, widow-owned properties are approximately 40% larger than the average, a notable finding considering the low number of widows holding property there. This discrepancy may reflect wealth concentration among widows in Castello.
• In Dorsoduro, the average property size for widows is comparable to the district average.
• In other districts, widow-owned properties are generally smaller than the average, suggesting a relatively worse economic situation for widows in these areas.

Property Functions

The final aspect of the analysis focuses on the types and functions of widow-owned properties. The graph below shows the distribution of properties by the number of distinct functions they serve.

From this data:

• Most properties serve a single function, while over 100 properties serve two functions.
• A smaller number of properties have three or four functions, which may reflect detailed notations in the Sommarioni or unique uses of these properties.
• Of the 659 widow-owned properties, 555 are rented (partially or fully), while 104 are not rented at all. The non-rented properties primarily include vegetable gardens (orto) and covered walkways (sottoportico).
• Only nine widows are listed as living in the properties they own, an unexpectedly low number that may merit further investigation.

Catastici and Sommarioni: Properties Analysis Comparison

When comparing the results of the different analysis of the Catastici and Sommarioni only the intersection of the columns from the two sets are possible to use. This is due to the datasets not containing the same data. An example for something that falls outside this scope is the aspect of the tenants, due to them not being mentioned in the Sommarioni. A few common aspects can still be compared between the analysis of both datasets.

Amount of extracted widows

In the Catastici, out of 33'297 entries, this study could only extract 104 widows (70 vedova VS 34 consorte), while in the Sommarioni, even though it contains 23'400 entries, which is less than the Catastici, 659 widows (651 vedova VS 8 consorte) could be found. This rises multiple questions like if the difference is representative of a true difference in number of widows in Venice population between the two time points or if it is due to some bias induced by the data and the way widows were recorded.

Distribution of owners in each district

As seen in Distribution of the widows across Venice districts, in 1740, there were strikingly more widows that were recorded to own properties in the Ghetto Novossimo (part of Cannaregio) than the rest of the population, while in the Sommarioni Property Analysis widows tended to own more properties in completely different regions, namely Castello and Dorsoduro. These regions are also different from the ones in which widows tended to rent more properties than the global population. This drastic change in the locations of widow-owned properties between the two time points could be investigated.

Heritage analysis

The inheritance of properties by widows in Venice offers insight into historical family dynamics and property ownership structures. This study examines links between property records in the Catastici and Sommarioni to identify patterns of inheritance. The analysis focuses on widows who owned property, as tenants are not mentioned in the Sommarioni.

Catastici to Sommarioni

Of the 61 widow-owned properties in the Catastici, when only looking at the widows mentioned as "consorte" and "vedova", only 16 contained valid id_napo values, enabling direct comparison. Manual inspection of these entries yielded the following results. From these 16 entries, some of them id_napos related to the same parcel number. Therefore only 11 distinct cases are given in the datasets.

For four of the entries there was no apparent relationship between the widow-owned properties in the Catastici and corresponding entries in the Sommarioni. For example, the property linked to id_napo 4270 (Catastici: Gerolema; Sommarioni: DA' RIVA Giovanni Battista) showed no familial or functional connection.

For another seven of the entries there is a possible relationship between the two datasets. Several cases suggested familial inheritance, often indicated by shared last names between the Catastici and Sommarioni entries.

Elena Vianol and Paolina Mocenigo

An example of this is id_napo 4896, where in the Catastici the owner of a house with a shop is called Elena Vianol (widow of Ferigo Renier). In the Sommarioni the owner is called Renier Bernardino, which is likely a family member. Elena Vianol (widow of Ferigo Renier) also appeared in multiple instances where properties were inherited by individuals with the surname Renier. Another example is Paolina Mocenigo (widow of Michiel Morosini) who showed a similar trend, with properties inherited by Morosini Elisabetta.

Sommarioni to Catastici

Attempting to trace properties from the Sommarioni back to the Catastici yielded 388 potential links based on matching parcel numbers. Given the volume of data, computational methods were employed to identify connections.

The analysis focused on name similarity, which presented challenges due to variations in spelling (e.g., Bonvicini vs. Bonbicini). Despite these difficulties, clear inheritance patterns were identified in several cases.

The analysis revealed clear inheritance patterns in several cases, particularly among prominent families like the Renier and Morosini. These findings suggest that property often stayed within family lines, with widows playing a transitional role in ownership. Discrepancies in name spelling, inconsistent recording practices, and incomplete historical data hindered efforts to establish conclusive links for many properties. These limitations highlight the need for refined computational techniques and deeper contextual understanding in future research.

Rent and Geographic Analysis

The following section will analyse how the rent price varies in the different districts of Venice. The analysis will include how the media price is in each district and how it relates to the price paid by tenants and widow owners renting out their properties. The entire analysis will only be based on the Catastici.

Classification: Jewish and Nobles

Widows live in very different situations depending on their socioeconomic situation, the number of children they have and if they remarry or not. To understand the rent paid and earned by widows it is useful to identify different groups within the observed population. Isolating the nobility from the rest of the population can be insightful to understand rent patterns. Another useful separation is to isolate the Jewish society from the rest of the Christian society. Only one property (out of 745) in the Jewish Ghetto is owned by a noble and it does not involve widows. The condition of Jews in the Ghetto is discussed in the section related to the Ghetto.

Charity

From the Catastici it is appearent that not everyone is paying rent with money, or even paying rent at all. It appears like people are allowed to pay rent using money or goods. An common example for a good used for paying rent is sugar. However, no widow owner was found receiving payment in goods and no widow tenant was found paying in goods. Properties with no rent paid, meaning not paid in money or good, fall into the following three categories.

• charity (for instance : "gratis": free , "per carità": per charity, "per grazia": per grace, "amore dei": for the love of God)
• refusal to pay ("giurò non pagar affitto": swore not to pay rent)
• no comment

It is difficult to determine if no comment entries are mistakes and rent was actually paid, if they fall into charity or if some sort of agreement between owner and tenants. Focusing on explicit instances of charity, charity towards widow tenants is two times higher than charity in general. Widow owners were not found practicing charity.

Charity in Venice

	Total number of properties	Properties where no rent is paid	Mentioned as charity
Venice	33,297 (100%)	3,115 (9.35%)	169 (0.50%)
Widow Owners	143 (100%)	25 (17.18%)	0 (0%)
Widow Tenants	169 (100%)	4 (2.36%)	2 (1.18%)

Rent in Venice

Nobility and Widowhood

Widowhood is not the only factor that can influence the rent. A key social aspect which also has an influence on the rent is nobility. This section will explore this in combination with widowhood.

Median Rent and Number of Properties

	In Venice	Widow Owned	Widow Rented
TOTAL	124.0₤ 29999	124.0₤ 182	111.6 179
Noble Owner	124.0₤ 8913	124.0₤ 52	124.0₤ 45
Non-Noble Owner	124.0₤ 21086	117.8₤ 130	111.6₤ 134
Noble Tenant	496.0₤ 431	645₤ 3	403₤ 9
Non-Noble Tenant	124.0₤ 29568	111.6₤ 179	111.6₤ 170

If one looks at the numbers, it appears so as that the widow owners are renting their properties around the medain price. But if one excludes the nobel widows it is visible that the non-noble widows rent their property below the average price and widow tenants pay below the median rent. This shows how the overall results from one district can be influenced by different factors, giving a wrong impression for the rest of situation. Focusing on the yellow cells, about 30% of widows owners are noble, while only 5% of widow tenants are noble.

The scale of the districts

Zooming in to the scale of the districts, it is clear that the economical situation of widows is different in each district.

It is worth mentioning that widows are not present in equal proportions in each district. In particular, the Ghetto is very dense with both widow owners and widow tenants.

The median rent also varies for the different districts. San Marco is the district with the highest median rent, while Dorsoduro has the lowest.

In general, it is visible that widow tenants rent for a price below the median rent in every district except for San Marco, San Polo and Cannaregio. San Marco and San Polo are also the two districts with the lowest density of widow-owned and widow-rented properties, so this might have an impact on the results. Widow tenants seem to pay a similar price to the median in Cannaregio.

The economical situation of widow owners is very different in each district. In Santa Croce and Dorsoduro, the poorest districts, they rent out their properties at a lower price than the district's median. Widow owners seem to rent their properties at a similar rate as the rest of owners in Castello. In San Marco, Cannaregio and the Ghetto widows rent out their properties at a price higher then the median for the districts.

Median Rent in the districts

Sestiere	Median Rent	Widow Owners Median Rent Difference	Widow Tenants Median Rent Difference	Properties	Widow Owned Properties	Widow Rented Properties	Widow Properties Density
Castello	124.0₤	+0.0₤	-12.4₤	5774	36	49	1.47%
Santa Croce	111.6₤	-21.7₤	-31.0₤	3218	45	36	2.52%
Cannaregio	124.0₤	+124.0₤	0.0₤	6016	25	31	0.93%
Dorsoduro	86.8₤	-13.6₤	-15.5₤	5835	32	20	0.89%
San Marco	210.8₤	+49.6₤	+80.6₤	5697	20	28	0.84%
Ghetto Novossimo	124.0₤	+18.6₤	-37.2₤	529	12	8	3.78%
San Polo	142.6	-31.0	+31.0	2930	12	7	0.64%

To identify geographical biases it is necessary to observe rent at smaller scales.

Following, each district will be looked analysed further. For each of them, the parishes in which widows are involved is provided by the dataset. Parishes represent local religious communities. People do not necessarily belong to the closest parish to where they live. In the following plots, parishes are represented by a line encircling all of its members. Sometimes, non members happen to fall inside the parish's shape despite not belonging to it. Nobility owned properties are highlighted in black. Widow owners are highlighted in blue squares and yellow squares depending on their nobility status. Similarly, widow tenants are highlighted in red diamonds and yellow diamonds. Rent is shown with color. Here, the main method of investigation is to manually identify patterns in the following visualizations and comparing them to information about rent in the district's parishes.

Rent in San Marco [5]

San Marco

San Marco is a very rich district where rent is almost the double compared to the rest of Venice.

The widows representation in this district is low. Noble widows are integrated within the noble community. Interestingly in this district, most of the nobility is grouped in San Salvador. When ignoring the widows, the pattern of rent highlights key commercial elements of the district. For instance the main shopping street in the parish of San Salvador, "Merceria", is very visible because of the high rent.

Almost all widow tenants are concentrated in San Luca, though it is not clear to as why. San Luca is the cheapest parish of San Marco after San Samuel, but it is also located more centrally with regards to the cities activities.

Overall, widows rent out their properties above the median rent in this district, despite the fact that it is already the most expensive district.

Additionally, from the graph it is visible that the properties of the widows are located further away from the districts center.

Selected Parishes of San Marco

Parish	Median Rent	Widow Owners Rent Median Difference	Widow Tenants Rent Median Difference	Properties	Widow Owned Properties	Widow Rented Properties Size
Santa Maria Zobenigo	183.4₤	+126.6₤	+188.6₤	256	5	5
San Luca	161.2₤		+68.2₤	503	0	10
San Bortolomio	223.2₤	+24.8₤	+24.8₤	503	5	3
San Basso	396.8₤	+703.7₤	-124.0₤	135	2	1
San Marco	502.2₤	-254.2₤	+117.8₤	84	1	2
San Salvador	272.8₤	-71.8₤		521	2	0
San Vidal	310.0₤	-148.8₤		175	2	0
Sant'Angelo	186.0₤	+46.5₤		506	2	0
San Ziminian	248.0₤		+124.0₤	714	0	2
San Paternian	186.0₤		+24.8₤	178	0	2
San Maurizio	192.2₤		+303.8₤	139	0	2
San Samuel	124.0₤	+148.8₤		419	1	0
San Moise	204.6₤		-93.0₤	859	0	1
TOTAL San Marco	210.8₤	+49.6₤	+80.6₤	5697	20	28

Rent in Castello [6]

Castello

Castello has some widows, that really gather in specific parishes in the east of the district, in San Giovanni in Bragora, San Martin and Santa Maria Formosa.

Widow tenants pay lower rent than the median rent of their parish. This is the case in rich parishes like San Severo, as well as in poorer parishes like San Martin. Sant Antonio and Santa Maria Formosa are exceptions, as widow tenants in those parishes can afford expensive rents.

Also in this district it is visible that widows rent more in the outer regions of the district, further away from the center.

Widow owners are able to own expensive properties in some parishes and cheap properties in other, their situation is balanced at the scale of the district.

Santa Maria Formosa is a very diverse parish, were nobles and non nobles meet. Widows in Santa Maria Formosa have a good economical situation.

On the other hand, most of the widow tenants are living in cheap properties in San Martin and San Giovanni in Bragora and pay less then the median.

Parishes of Castello

Parish	Median Rent	Widow Owners Rent Median Difference	Widow Tenants Rent Median Difference	Properties	Widow Owned Properties	Widow Rented Properties Size
San Martin	86.8₤	+49.6₤	-6.2₤	563	3	14
Santa Maria Formosa	186.0₤	+74.4₤	+31.0₤	747	10	7
Santa Marina	186.0₤	-86.8₤	-46.5₤	383	7	10
San Severo	260.4₤	-148.8₤	-40.3₤	207	4	6
San Pietro di Castello	99.2₤	-24.8₤	-12.4₤	1495	6	3
San Giovanni in Bragora	124.0₤	+106.0₤	-52.7₤	399	4	4
Sant'Antonino	189.1₤	+120.9₤	+58.9₤	240	1	5
Santa Giustina	117.8₤	+520.8₤		321	1	0
TOTAL Castello	124.0₤	+0.0₤	-12.4₤	5774	36	49

Rent in Cannaregio [7]

Cannaregio

Cannaregio is a district where widow tenants are the most economocially integrated out of all the Venice districts, meaning they pay about the same rent price as the median. The widow owners in Cannaregio own valuable properties.

The nobility owns significant parts of the district, but these are not necessary located in one area, as is the case in other districts. The rent variations in this district are high.

As previously mentioned, also in Cannaregio it is evident that the widows properties lies somewhat offcenter.

Parishes of Cannaregio

Parish	Median Rent	Widow Owners Rent Median Difference	Widow Tenants Rent Median Difference	Properties	Widow Owned Properties	Widow Rented Properties
Santi Apostoli	161.2₤	-62.0₤	-55.8₤	618	9	2
Santa Sofia	136.4₤	+155.0₤	+43.4₤	546	4	6
San Marcuola	117.8₤	+71.3₤	+83.7₤	1432	2	6
San Marcilian	124.0₤	+117.8₤	+272.8₤	589	2	4
San Cancian	124.0₤	+124.0₤	-62.0₤	629	3	1
Santa Maria Nova	198.4₤		-111.6₤	183	0	4
San Giovanni Grisostomo	186.0₤	+136.4₤	+124.0₤	187	2	1
San Lunardo	148.8₤		-74.4₤	117	0	3
San Felice	186.0₤	+155.0₤	+434.0₤	351	1	1
San Geremia	99.2₤	+148.8₤	-49.6₤	1082	1	1
Santa Fosca	124.0₤	+620.0₤	+347.2₤	163	1	1
Santa Maria Maddalena	124.0₤		-37.2₤	119	0	1
TOTAL Cannaregio	124.0₤	+124.0₤	+0.0₤	6016	25	31

Rent in San Polo [8]

San Polo

Widows are not very present in San Polo. It is the district with the lowest density of widow properties. Additionally, very few properties are owned by nobility in this district.

San Polo is the only district in which the tendency is the other way around, namely widow owners own cheaper properties and widow tenants rent more expensive properties.

Parishes of San Polo

Parish	Median Rent	Widow Owners Rent Median Difference	Widow Tenants Rent Median Difference	Properties	Widow Owned Properties	Widow Rented Properties
San Giovanni Elmosinario	124.0₤	-12.4₤	+49.6₤	797	6	1
San Mattio	136.4₤	+31.0₤	-37.2₤	319	5	1
San Toma	136.4₤		+24.8₤	272	0	2
Sant'Aponal	148.8₤		+130.2₤	400	0	2
San Polo	161.2₤	-117.8₤		353	1	0
San Stin	124.0₤		-49.6₤	169	0	1
TOTAL San Polo	142.6₤	-31.0₤	+31.0₤	2930	12	7

Rent in Santa Croce [9]

Santa Croce

Santa Croce has a significant number of widows.

Widow tenants live in properties with rent lower than median rent.

The number of property owned by widows in this region can be deceiving because it is quite high. Though by closer inspection it is clear that most of the properties are owned by a handful of very rich widows. For instance Nobil Domina Leonora Corner relicta Lorenzo Gabriel owns 23 of the 26 properties of the Santa Croce parish. Even if the rent for widow owners properties in Santa Croce seems to be below the median rent, it only reflects the median rent of properties owned by Leonora Corner and not her economical situation. In fact her income from those 23 properties sums up to 2321.9₤.

All widow owned properties of the parish Santa Lucia are owned by Maria Rizzardi. In Santa Maria Mater Domini 4 out of the 5 properties owned by widows are owned by Perina Capello.

Parishes of Santa Croce

Parish	Median Rent	Widow Owners Rent Median Difference	Widow Tenants Rent Median Difference	Properties	Widow Owned Properties	Widow Rented Properties
Santa Croce	111.6₤	-23.2₤	-37.2₤	739	26	25
Santa Maria Mater Domini	124.0₤	+31.0₤	-31.0₤	152	5	5
Santa Lucia	86.8₤	+49.6₤		151	8	0
San Simeon Apostolo	99.2₤	+334.8₤	-37.2₤	198	1	3
San Cassiano	186.0₤	-86.8₤		546	3	0
San Giacomo dall'Orio	99.2₤	+24.8₤	-55.8₤	657	1	1
San Giovanni Decollato	124.0₤	+99.2₤	+12.4₤	98	1	1
San Simeon Profeta	93.0₤		+0.0₤	447	0	1
TOTAL Santa Croce	111.6₤	-21.7₤	-31.0₤	3218	45	36

Rent in Dorsoduro [10]

Dorsoduro

Dorsoduro is the poorest of all the districts, as it has the lowest median rent. In this region a majority of widow tenants rent for below the local median rent. Additionally a majority of widow owners rent out properties below the median rent. Even though this district is so poor, a significant part of the district is nobility owned.

In the parish San Raffael the situation for widow tenants looks dramatic. Similarly, widow owners in San Nicolo and San Gregorio own very cheap properties.

Parishes of Dorsoduro

Parish	Median Rent	Widow Owners Rent Median Difference	Widow Tenants Rent Median Difference	Properties	Widow Owned Properties	Widow Rented Properties
San Nicolo	59.9₤	-11.9₤		1137	11	0
San Gregorio	86.8₤	-12.4₤	+198.4₤	487	6	3
San Raffael	74.4₤	+576.6₤	-43.4₤	772	1	7
Santa Margherita	99.2₤	-43.4₤	+6.2₤	483	3	3
Sant'Agnese	111.6₤	+49.6₤	+18.6₤	269	2	4
San Barnaba	124.0₤	-37.2₤	-62.0₤	904	3	2
San Pantalon	111.6₤	+111.6₤	+446.4₤	639	2	1
San Basegio	74.4₤	-37.2₤		359	2	0
San Vio	86.8₤	+372.0₤		233	2	0
TOTAL Dorsoduro	86.8₤	-13.6₤	-15.5₤	5835	32	20

Rent in the Ghetto [11]

The Ghetto

The Jewish Ghetto is made of three parts that were added at different times in history. There is almost no nobility in this district. The situation of tenants is the same as in most districts, their rent is lower than the median. For widow owners, the situation seems to be better, meaning they charge more then the median rent price for their properties.

We find proportionally more widows in the Ghetto compared to the other districts. This might be the consequence of the following socio-cultural dynamic given in the article: "There was a tendency to look down upon women who remarried because of concern that they were seeking sexual satisfaction from other men or transferring their late husbands' assets or children to another family." — Jewish Women's Archive, "Italy in the Early Modern Period".

Parishes of the Ghetto

Parish	Median Rent	Widow Owners Rent Median Difference	Widow Tenants Rent Median Difference	Properties	Widow Owned Properties	Widow Rented Properties
Ghetto Vecchio	124.0₤	+12.4₤	-24.8₤	276	7	5
Ghetto Nuovo	124.0₤	+105.4₤	-55.8₤	207	5	2
Ghetto Nuovissimo	148.8₤		+68.2₤	46	0	1
TOTAL Ghetto	124.0₤	+18.6₤	-37.2₤	529	12	8

Conclusion and interpretation

This analysis highlights the diverse economic situations of widows in 18th-century Venice.

It appears that widows experience slightly more charity than the rest of the city, but the phenomenon remains rare.

The non-noble widows rent their property below the average price and widow tenants pay below the median rent. This highlights that a lot of widows are in difficult economical situations. This is especially true in the poor district Dorsoduro.

Widow tenants sometimes tend to live on the outskirt or in poor neighborhoods, but most of the time they rent cheap properties even when they are close to the heart of districts.

Limitations, discussion and quality assessment

Showcases of limitations

The pipeline this project followed could only recognize instances of widows if they were mentioned using one of the three keywords among: relicta, consorte and vedova. This methods raises two problems that the following examples perfectly illustrate. These examples question the ability of this study to identify all the widows present in both datasets.

Chiara Pisani: rarely qualified as a widow

Properties of Chiara Pisani [12]

Chiara Pisani was an extremely wealthy widow of the 18th century Venice. She was part of the Pisani family. Accounts of here life mentioned that she was left in charge of a significant fortune after loosing both her father in 1737 and her husband in 1738. [17] At the time of the Catastici (in 1740) she was 36 years old. Looking for Chiara's name in the Catastici, can give a better idea of how significant her fortune was: in 1740, she was the owner of 39 properties. Her total income from rent was 16,812 lirae. This is about 135 times the median rent of Venice of 124 lirae. She is sometimes mentioned as Chiara Pisani, sometimes as the tutelle of her sons, sometimes as the procuartor of her uncle Nicolò Pisani. Most strikingly, she is only mentioned once as a 'relicta', which made her identification more difficult, and mislead the analysis of her total properties. Chiara Pisani is unfortunately not an isolated case. Other widows were not always mentioned using the keywords from the proposed pipeline and some are very probably not mentioned as such at all. A refinement of the pipeline would include more keywords and extract more systematically if other mentions include the name of the widow, maybe wometimes without a specific keyword.

Cattarina Cavaliera: the relevance of semantic analysis

The relatively small number of widows identified in the records may imply that widowhood as the head of a household was often a temporary state. Widows might have remarried, joined a convent, or come under the care of their sons. The mentions of their relative can sometimes give important insight on the particular familial situation of each woman in the dataset and most especially of widows. This is supported by an example in the Catastici: “Nicolò et ISeppo Fratelli Gatto quondam Gerolamo eredi di Cattarina Cavaliera sua madre” (Nicolò and Iseppo Gatto, brothers, sons of the late Gerolamo, heirs of Cattarina Cavaliera, their mother). This suggests that Cattarina Cavaliera was indeed a widow and was not recorded as an independent head of household for long. This information can only be understand after a semantic analysis of the text, which is not provided in this study. Refining the pipeline by adding this feature would greatly improve the ability to find instances of widows.

Discussion and Quality assessment

The analysis conducted on the Catastici and Sommarioni data reveals important insights but is constrained by several methodological and data limitations.

The study cases of Chiara Pisani and Cattarina Cavaliera support the hypothesis that more widows are present in both the Catastici and the Sommarioni but that this study could not identify yet. This limitation is notably due to the chosen methodology, since once a widow has been identified, her status is not propagated to other entries this widow might own. This conservative approach might be very limiting.

Another key issue lies in the small sample size: only 16 cases were identified using the id_napo when examining the heritage between the two registers Heritage analysis. This amount is insufficient for drawing concrete conclusions about widows. If the keyword "relicta" would have been used for the Catastici in this analysis, more widows would potentially found having a id_napo. Additionally, inconsistencies in standardised sections like "owner_standardised" in the Sommarioni, which still includes spelling variations, makes a comparison harder. The heritage analysis would be more complete if the resulting data would have been used to see how the economic situation of widow changes across time.

The methodological tools used, such as difflib for identifying name similarities, while helpful, may have overlooked certain matches, and the narrow scope of the methods applied may not fully capture all the information given in the data. The absence of tenant data in the Sommarioni further restricts the ability to generalize findings, particularly for poorer widows who may be underrepresented in the cadaster.

Despite these challenges, the data quality is largely acceptable, though it is important to acknowledge potential errors introduced during the creation of the cadasters and the digitization process. However, combining these historical records with other sources adds quantitaive foundation to an else qualitative analysis.

This study's transparency and reproducibility increases its quality, since all analyses are documented and accessible on GitHub. Future research can build on these foundations by broadening the scope to include female-headed households, which might provide a more representative picture of widows in Venice. Exploring broader themes, such as the nobility's control of Venetian real estate, the role of the Catholic Church and charity, marriage laws, community dynamics, migration patterns, and economic activities across districts, can clarify confusing factors and pinpoint causes for observed phenomena.

Ultimately, the knowledge bottleneck about Venice in this era limits interpretive potential, but the Catastici and Sommarioni datasets, when combined with additional sources, offer valuable insights that can help enrich the understanding of Venetian widows and their societal contexts.

Conclusion and continuation

Conclusion

After conducting various analysis the most clear trends are the following. In the Catastici cadaster from 1740 not a lot of widows are identifiable as owners or tenants compared to the amount of entries given. The proportion of widows owning or renting properties is higher in the Jewish Ghetto than anywhere else. In general widows rent and own cheap properties unless they are nobles. It appears as charity in the Venetian society during this time is low in general but higher towards widows.

In 1808 there are more widows mentioned in the Sommarioni cadaster compared to the Catastici from 1740. Most of these widows tend to rent out their property. Only 9 widows are explicitly mentioned as living at their own property. In general the properties held by the widows are smaller than the average size of a property in the given district, which might indicate worse economic situations.

Continuation

This project has been an attempt to collect knowledge on the widows living in Venetian society in 1740 and in 1808. There is still plenty to uncover about how life was for them and possible research areas are described followingly.

The functions of the properties owned by widows in the Catastici were not exploited like in the Sommarioni. One could extract those information and compare them to the Sommarioni.

When it comes to the heritage analysis, this can be further analysed by using geoemtric matching between the two datasets. By comparing spatial data where id_napo values are unavailable, one could link all the widows mentioned in the Catastici to the Sommarioni, giving more insight into the heritage.

This project also wanted to analysis the vocabulary used to qualify owner and tenants, but due to lack of time this analysis had to be set aside. One could explore the usage pattern between consorte, vedova and relicta to describe widows and see if any evolution is observed between the Catastici and the Sommarioni. Analysis on the etymology and usage of this specific words might prove fruitful.

A last aspects that can be further explored are the different case studies of the widows mentioned explicitly in the report, such as Loredana Grimani.

Deliverables

The main deliverable of the project are this Wikipedia page where one can find the results of the different analysis conducted during the span of the project and the tools used to extract the different data. For more details, please review the Results section.

In addition, all the code used for the analysis can be found in the GitHub repository of this project:

Our Github Repository

Credits

Course: Foundation of Digital Humanities (DH-405), EPFL

Professor: Frédéric Kaplan

Authors: Eglantine Vialaneix, Nathanaël Lambert, Lisa Marie Njå

Date: 18.12.2024

References

• Image of the Venice Datasets – Retrieved from DH-405 lecture slides
• Fall of the Republic of Venice, Wikipedia
• Napoleon, Wikipedia
• A Chronology of the Black Plague in Venice, History Walks Venice
• Citizen of the Republic of Venice, History Walks Venice
• Libro d'Oro, Wikipedia
• Wall & Moring (PDF), INED
• Peek into Private Lives of Venice, Venetian Cat Blog

Supplementary Information

Dictionary of Useful Words and Idioms

Italian	English	Description
vedova	widow	Refers to a woman whose husband has passed away.
mestiere	profession	A term used to describe one's occupation or trade.
parrocchia	parish	Parishes in Venice were local religious districts, each centered around a parish church. Every house in Venice belonged to a specific parish, forming a network of smaller communities within the larger city.
sestiere	district of Venice	The name given to the districts of Venice: San Marco, San Polo, Santa Croce, Dorsoduro (which includes the island of Giudecca), Castello, and Cannaregio.
fratelli	brothers	The plural form of fratello (brother).
sorelle	sisters	The plural form of sorella (sister).
ved	widow of	An abbreviation of vedova.
quondam	son/daughter of	Literally means "formerly" or "previously." Often used in historical contexts to indicate lineage.
fratelli quondam	brothers of the father	Refers to a person and their brothers from the same father (e.g., siblings from a deceased patriarch).
fu di	of the late man	Similar to quondam, but explicitly indicates that the father is deceased.
q.m.	abbreviation of quondam	A shorthand version of quondam used in records and documentation.
sudett-o/-a/-i	part of another place	Indicates that certain rows in a table belong to one geographical or administrative area.
consorte	married with	Indicates a spouse, often implying the husband is deceased.
della fu	of the late woman	Used to indicate lineage or connection to a deceased mother.