Context

We all know of the Roman empire, but what about its emperors specifically?

Content

Here, you will find information on each of the emperors of the Roman empire, which lasted between 26 BC and 395 AD. Specifically, you can use data on their:

• Names
• Date of birth
• City and Province of birth
• Date of death
• Method of accession to power
• Date of accession to power
• Date of end of reign
• Cause of death
• Identity of killer
• Dynasty
• Era
• Photo

Acknowledgements

This dataset was provided by Zonination, who made it available on Wikipedia. See his repository on Github

Inspiration

What kind of trend can you find in these emperors' lives and reigns? What aspects of them allowed them to live longer?

Origo is a geospatial spreadsheet dataset documenting ancient migrants attested in the Epigraphic Database Heidelberg (EDH). It is derived from a subset of individuals in the EDH People dataset (available at: https://edh.ub.uni-heidelberg.de/data/download/edh_data_pers.csv) who explicitly declare their geographic origin in the inscriptions. Based on the data curated by the EDH team, we have geocoded the stated places of origin and further enriched the dataset with additional metadata, prioritizing machine readability. We have developed the dataset for the purpose of a quantitative study of migration trends in the Roman Empire as part of the Social Dynamics in the Ancient Mediterranean Project (SDAM, http://sdam.au.dk). The scripts used for producing the dataset and for our related publications are available from here: https://github.com/sdam-au/LI_origo/tree/master.

The dataset includes two point geometries per individual:

• Geographic origin (origo_geometry) – representing the individual’s place of origin or birth.

• Findspot (findspot_geometry) – indicating the location where the inscription was discovered, which often approximates the place of death, as approximately 70% of the inscriptions are funerary.

Scope and Structure:

The dataset covers 2,313 individuals, described through 36 attributes. For a detailed explanation of these attributes, please refer to the accompanying file origo_variable_dictionary.csv.

File Formats:

We provide the dataset in two formats for download and analysis:

1. CSV – for general spreadsheet use.

2. GeoParquet (v1.0.0) – optimized for geospatial data handling.

In the GeoParquet version, the default geometry is defined by the origo_line attribute, a linestring connecting the origo_geometry (place of origin) and the findspot_geometry (findspot of the inscription). This allows for immediate visualization and analysis of migration patterns in GIS environments.

Getting Started with Python:

To load and explore the GeoParquet dataset in Python, you can use the following code:

import geopandas as gpd import fsspec origo = gpd.read_parquet(fsspec.open("https://zenodo.org/records/14604222/files/origo_geo.parquet?download=1").open())

This data was scraped from https://en.wikipedia.org/wiki/List_of_Roman_emperors

Context

We have all learned about this important period in history, but this dataset ready for cleaning and analysis can give you important insight on this epic period of history.

About

The data was taken directly from Wikipedia without any modifications. For this reason, it is a great dataset to practice cleaning, dealing with NaNs, and extracting information from messy data.

This database compiles the biometrical data of cattle, sheep and pig, gathered from Switzerland and adjacent areas of Central-Eastern France. The data is dated between the Roman times and the High Middle Ages. This database was produced in relation to the MSCA-IF funded project "ZooRoMed: Supplying ancient empires and medieval economies: Changes in animal husbandry between the Late Roman period and the Early Middle Ages in the Rhine Valley" (https://cordis.europa.eu/project/id/793221); the project was hosted by the University of Basel between 2018 and 2021.

Biometrical abbreviations appear according to: Von den Driesch A (1976) A guide to the measurement of animal bones from archaeological sites. Harvard: Peabody Museum, Bulletin 1.

Many of these compiled datasets had previously been published individually as part of older site monographs, not easily accessible to people based outside of Switzerland, and this is the first time they have been brought together in an Open Access database.

Measurements were collected from a number of different sources:

from databases at the institute of Integrative Prehistory and Archaeological Science (IPAS) in Basel, Switzerland

from the literature (see bibliography in the document "Sites+references")

from unpublished databases belonging to the person who recorded the data (all of these people are co-authors here)

Both postcranial and tooth measurements are included in the database, but not every single measurement from the original reports was included, as a selection of the most common and useful measurements was made. The selection of measurements was made based on a number of parameters:

Their availability in databases and reports (generally linked to their prevalence in assemblages due to taphonomic processes, etc.)

The ease in which they can be taken consistently by different researchers

The ease of their use (for example, only phalanges that could be assigned as either fore or hindlimb were included

This dataset was compiled during the course of a European Commission Horizon 2020 Marie-Skłodowska-Curie Individual Fellowship (Grant Agreement no. 793221), which was held by Idoia Grau-Sologestoa from 2018-2021, and hosted by the institute of Integrative Prehistory and Archaeological Science (IPAS) the University of Basel.

The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area. Census Tracts 2010 reviewed 05/15/2015

Source: United States Census Bureau

Effective Date:

Last Update: 05/15/2015

Update Cycle: As needed, Census is completed every 10 years.

This data was created as part of a project studying the Register of Pope Gregory VII (d. 1085), funded by the Department of History at the University of Sheffield over the summer of 2020. The data was collected and analysed by George Litchfield with the assistance of Tom Stafford and Charles West. There is a CSV dataset, a project readme.txt and a project description, as well as numerous data visualisations.FindingsDuring the process of collecting this data, we discovered a likely mistake in the German historian Caspar’s 1920’s edited version of the register, which has then subsequently been carried across to Cowdrey’s translation, and the wider historiography. From Book 4 letter 13 to 15, in early March 1077, Gregory is stated to be in Carpineto. However, on the 21st and 23rd of March, Gregory is stated to be in Carpi and Bianello respectively, both of which are over 500km away from Carpineto Romano according to Google maps. It is therefore more likely that in March 1077 Gregory was in Carpineti, which is only around 50km away from both Carpi and Bianello. These same entries may also shed light on Gregory’s travels and travel more widely at this time. On the 21st of March, two letters are recorded, issued from different locations. The first, letter 16, is written from Carpi, while the other entry is written from Bianello. These locations are approximately 44km apart, and so may show us the distance Gregory and other messengers could cover per day (another instance of this occurs in Book 3 letter 3).The disorganisation of the register as it approaches its book 9 is well known, which suggests that the declining number of letters was another symptom of disorganisation in the papal chancery. However, while the data does show the overall trend of letters declining from 1074 to 1084, the average amount of words per letter generally increases over the course of his pontificate, with the exception of downward spikes towards 1082 and 1084, although the lack of entries for these years may be the cause of this. It could be suggested that though Gregory’s output really did decrease, rather than being purely a result of disorganisation, Gregory was simply trying to get more done in fewer letters.The data suggests that time of year was taken into account when deciding when to send letters. This is not immediately clear from the coloured mapping of letters by season. However, by looking at the average distance letters covered by month, it can clearly be seen that in the months of March, April and May, letters covered a greater distance than other months, especially the winter months of January and February. This could be said to show Gregory’s consideration of the weather and travel conditions when conducting business. One thing that may seem strange is the fact that the extremity locations such as in England and Norway were sent in the winter; presumably this was to enable them to complete the more dangerous and remote legs of their journey in the summer.Another notable set of results involving the month of sending is seen when the number of letters sent in each individual month is examined. Gregory’s correspondence tended to spike around April. This trend may be due to Easter, which would have been an important time for Gregory, and is also when he held a number of councils. This adds another important consideration into the mix when examining factors that influenced Gregory’s correspondence through letters.The superimposing of Roman roads onto a map of Gregory’s letters also help us visualise an aspect of his pontificate. As would be expected, the overwhelming majority of Gregory’s letters are sent to areas part of the old Roman Empire. However, this visualisation also neatly demonstrates that Gregory wasn’t limiting his diplomacy to just the old Roman Empire, and sought to bring influence of the Roman areas where this was perhaps lesser felt, especially the northern areas of eastern Europe.The extent of this communication becomes even more notable if we look at the most commonly written-to individual locations in the register. Bohemia and Hungary are first and sixth most written-to locations in the register. Although counting another region like Italy’s letters as a whole would result in a larger number, the letters to Bohemia and Hungary are highly concentrated on a specific group of people, whereas there would be larger variety in Italy’s letters. This provides statistical backing to some of Cowdrey’s arguments in his work on Gregory, namely that Gregory was attempting to enforce papal authority in the German-subject that was Bohemia, and assert the independence of Hungary from Germany, both of which were part of his larger strategy to contain Henry IV’s power in the east.Another argument of Cowdrey is that Gregory was ‘flexible’, and that the idea he ‘acted upon a number of sharply defined and clearly formulated principles of papal action’ is misleading. Yet this does not necessarily show data-wise in the strategy of his letter writing. As can be seen, the amount of clerical and secular recipients generally changes fairly proportionately with one another, with only a slight change where secular overtakes as 1082 approaches. So while the content of letters may change, there does not seem to be any big shift in what part of society Gregory is writing to.This work has suggested the possibilities of using modern data analysis to provide a fresh look at primary material that has already been extensively studied such as Gregory VII’s letters. There are many more possibilities, and it is our hope that someone will take this data set and do just that. One such idea could be breaking down the letters into zones of distance from Rome, and analysing whether this affects the content and tone of the letter. This could lead to a better picture of whether politics or earthly constraints were more of a determining factor in the writing of the letters.BibliographyH. E. J. Cowdrey, The Register of Pope Gregory VII 1073—1085: An English Translation (Oxford, 2002),H. E. J. Cowdrey, Pope Gregory VII, 1073–1085 (Oxford, 1998)Alexander Murray, ‘Pope Gregory VII and His Letters’, Traditio 22 (1966)