This map displays the largest extents of three major empires during their territorial peaks. The Roman Empire reached its greatest extent in 117 AD under the reign of Trajan. The Mongol Empire reached its greatest extent in 1279 AD under the reign of Kublai Khan. The British Empire reached its greatest extent in 1921 AD under the rule of King George V. The regions for each shown on the map represent a snapshot in time of the extent of each empire during their year of greatest extent. This means that some territories that may have been owned by a particular empire at one time may not be included in this map if it was not owned by the empire during its time of greatest extent.

When asked how people felt about their country's former empires, the most common feeling was one of indifference. Apart from the Netherlands, where half of respondents said they felt some level of pride relating to the Dutch colonial empire, the most common response was that people's respective empires were neither something to be proud nor ashamed of; this sentiment was most strongly felt in Spain, where over two thirds of respondents claimed that they felt indifferent or did not know how to feel. After the Netherlands, people in the United Kingdom (which had the largest empire the world has ever seen) felt the most pride, although it was still less than one third of respondents. In half of the countries surveyed, there was a higher number of people who said their country's colonial past was more to be ashamed of than proud of, and this was felt most strongly in Italy. In Germany, almost one third of respondents said they did not know how to feel about the German colonial empire.

Colonialism in European schools

In 2020, many still feel that education systems across Europe have overlooked the role played by empires throughout history; in stark contrast to education systems across other continents, where colonial backgrounds and independence movements are often ingrained in national identities. Through factors such as the slave trade and mass migration, intercontinental empires laid the foundation for the multi-cultural and multi-ethnic societies that exist across the globe today, therefore, the understanding of colonialism plays a key role in understanding how race and representation work in modern society.

Recent years have seen a greater push to make the study of empires, slavery and colonialism a compulsory part of European education systems; in 2011, France introduced an obligatory module on the Algerian War and transatlantic slavery for high school students, and Britain's Labour Party planned on introducing the topic to the national curriculum had they won the 2019 election. On the other hand, most countries include only optional modules for high school students, and many teachers skip the topic due to it's complexity and sensitivity. Some studies from the Netherlands also claim that only the positive aspects of Dutch colonialism are taught in schools, while the negatives are "airbrushed" over; which is one possible explanation for the high levels of pride relating to the Dutch Empire among the survey's respondents.

In the century between Napoleon's defeat and the outbreak of the First World War (known as the "Pax Britannica"), the British Empire grew to become the largest and most powerful empire in the world. At its peak in the 1910s and 1920s, it encompassed almost one quarter of both the world's population and its land surface, and was known as "the empire on which the sun never sets". The empire's influence could be felt across the globe, as Britain could use its position to affect trade and economies in all areas of the world, including many regions that were not part of the formal empire (for example, Britain was able to affect trading policy in China for over a century, due to its control of Hong Kong and the neighboring colonies of India and Burma). Some historians argue that because of its economic, military, political and cultural influence, nineteenth century Britain was the closest thing to a hegemonic superpower that the world ever had, and possibly ever will have. "Rule Britannia" Due to the technological and logistical restrictions of the past, we will never know the exact borders of the British Empire each year, nor the full extent of its power. However, by using historical sources in conjunction with modern political borders, we can gain new perspectives and insights on just how large and influential the British Empire actually was. If we transpose a map of all former British colonies, dominions, mandates, protectorates and territories, as well as secure territories of the East India Trading Company (EIC) (who acted as the precursor to the British Empire) onto a current map of the world, we can see that Britain had a significant presence in at least 94 present-day countries (approximately 48 percent). This included large territories such as Australia, the Indian subcontinent, most of North America and roughly one third of the African continent, as well as a strategic network of small enclaves (such as Gibraltar and Hong Kong) and islands around the globe that helped Britain to maintain and protect its trade routes. The sun sets... Although the data in this graph does not show the annual population or size of the British Empire, it does give some context to how Britain has impacted and controlled the development of the world over the past four centuries. From 1600 until 1920, Britain's Empire expanded from a small colony in Newfoundland, a failing conquest in Ireland, and early ventures by the EIC in India, to Britain having some level of formal control in almost half of all present-day countries. The English language is an official language in all inhabited continents, its political and bureaucratic systems are used all over the globe, and empirical expansion helped Christianity to become the most practiced major religion worldwide. In the second half of the twentieth century, imperial and colonial empires were eventually replaced by global enterprises. The United States and Soviet Union emerged from the Second World War as the new global superpowers, and the independence movements in longstanding colonies, particularly Britain, France and Portugal, gradually succeeded. The British Empire finally ended in 1997 when it seceded control of Hong Kong to China, after more than 150 years in charge. Today, the United Kingdom consists of four constituent countries, and it is responsible for three crown dependencies and fourteen overseas territories, although the legacy of the British Empire can still be seen, and it's impact will be felt for centuries to come.

This dataset is about books. It has 2 rows and is filtered where the book is Empire : the history of the British empire. It features 7 columns including author, publication date, language, and book publisher.

Some of the biggest sports empires in the world own not only entire franchises, but also sports media and hospitality businesses. The most valuable global sports empire in 2024 was Liberty Media, worth an estimated 18.22 billion U.S. dollars. The mass media company owns Formula One and has partial ownership of the Drone Racing League. Kroenke Sports & Entertainment Kroenke Sports & Entertainment, although not the largest sports empire in the world, has control over multiple sports franchises, a football club, various stadiums, eSports teams, TV channels, sports magazines, and more. One of the teams from the company’s football club is Arsenal F.C., a professional football club based in North London. Despite having stakes in companies outside of the U.S., Kroenke Sports & Entertainment is based in Denver, Colorado. Fenway Sports Group Fenway Sports Group, the third largest sports empire in the world, is an American multinational sports conglomerate that owns numerous sports teams such as the Boston Red Sox and the Pittsburgh Penguins. The former team has won nine world championships and ranked as the one of the most valuable franchises in Major League Baseball as of 2023. Similar to Kroenke Sports & Entertainment, Fenway Sports Group is based in the United States.

This dataset is about books. It has 2 rows and is filtered where the book is War and gold : a five-hundred-year history of empires, adventures and debt. It features 7 columns including author, publication date, language, and book publisher.

This dataset is about book series. It has 1 row and is filtered where the books is A history of Latin America : empires and sequels 1450-1930. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

ABSTRACT Throughout Brazil’s Independence process, its central elites and the Crown planned what was to become of their new nation. Arguments over political systems and the continuation of slavery were at the heart of the debate, which drew in rich, poor, and the enslaved alike. As the empires of the Old World were rent at the seams by wars and conflicts, Brazil was rethinking its role in the world. In this article, inspired by the dialogue between micro-history and global history, and by the trans-imperial trajectory of the Bavarian doctor Georg von Schaeffer, I examine the political ideas that informed the consolidation of the Brazilian Empire as a de facto empire. I also situate the ideas and proposals put forth by Schaeffer, a representative of the Brazilian government in Europe, within the crisis of legitimacy sparked by the Napoleonic invasions, the subsequent independence of Portuguese America, and the array of political projects that were able to emerge as a result. Through an analysis of the diplomatic documentation produced by the Brazilian Empire’s main posts in Europe, I reveal a complex web from which the Brazilian government drew information, and the channels that carried news of alliances, clashes, and political repertoires that would go into the making of a tropical empire.

When compared with modern travel across Europe, North Africa, and the Middle East, journeys in Roman times were more likely to be measured in days or weeks rather than hours. Today, the average flight from London to Rome takes between 2.5 and three hours, whereas this journey could have taken between three and six weeks in Roman times, depending on the cost and mode of transport. When looking at journeys from Rome to other major cities outside the Italian peninsula, those that utilized travel across the Mediterranean were generally the fastest in relation to total distance. For example, the cheapest journeys to Lugdunum and Carthago were of similar distance, but the land journey to Lugdunum was roughly three or four times as long as the sea journey to Carthago (depending on the season), and this was also true for military movements. Infrastructure The Romans were notably famous for their road networks, with eventual totals of over 400,000 kilometers of road; 20 percent of which was paved. This infrastructure was essential to the defense of the empire, as it allowed much greater movement for Rome’s armies, as well as economic sustainability, for the movement of merchants, slaves, and cargo. Sea trade and transport was also an essential part of the Roman Empire's success, however Rome controlled virtually all of the Mediterranean coast by 200CE, therefore there was no major military threat at sea apart from pirates. Methodology These figures come from ORBIS: The Stanford Geospatial Network Model of the Roman World, which was launched in 2013 by a team of historians and IT specialists at Stanford University. It is an attempt to give greater insight into the logistics of travel through the Roman Empire, in conditions similar to those of 200CE (although some locations did not exist at this time). Users can create hypothetical, approximate journeys across the empire, looking at the duration, distance, and price per journey. The model takes various factors into account, including seasonal variations (such as the weather’s impact on sea travel or mountainous journeys), modality of transport, and pricing variations, among many others. While the source acknowledges it uses a simplified model of the transport network across the empire, there are over 363,000 possible outcomes for journeys between 632 sites, making this the most comprehensive model of its kind.

This dataset is about books. It has 3 rows and is filtered where the book subjects is Byzantine Empire-History-Manuel II Palaeologus, 1391-1425. It features 9 columns including author, publication date, language, and book publisher.

About this dataset

Context

The dataset tabulates the Empire population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Empire. The dataset can be utilized to understand the population distribution of Empire by age. For example, using this dataset, we can identify the largest age group in Empire.

Key observations

The largest age group in Empire, OH was for the group of age 60 to 64 years years with a population of 39 (14.77%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Empire, OH was the 80 to 84 years years with a population of 0 (0%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Empire is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Empire total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Empire Population by Age. You can refer the same here

This dataset is sourced from an elegant deck of playing cards created in 1856 to teach members of Russia's elite families about the empire they inhabited. The cards—all 80 of them—provide us with a unique perspective on how the subjects of the tsar “saw” their country on the eve of the emancipation of the serfs. The resulting data includes hundreds of attributes describing the distribution of economic activities, ethnic groups, geographical features, and historical "particularities." The data is accompanied by a readme, a file catalog, a codebook, and a glossary. Spatial units: 3 semi-autonomous regions (polygons); 77 provinces (polygons); 417 towns (points); 180 rivers (lines)

This dataset contains the data collected for the Histories of Reception of Photography in the Ottoman Empire project, undertaken as a Marie Skłodowska-Curie Action project at the Department of Philosophy, Classics, History of Art and Ideas (IFIKK) at the University of Oslo (UiO) from 01.09.2022 until 31.08.2024. The dataset consists of the books and articles on photography written in Western Armenian and in Ottoman Turkish in the late 19th and early 20th century.

With the UrbanOccupationsOETR, a European Research Council-funded research project hosted at Koç University 2016-2022, we wanted to highlight the importance of rural economic dynamics to explain differences in long-term regional economic development in the late Ottoman Empire. We provide an Excel dataset on the crop-specific agricultural mix and land area of an Ottoman region, Bursa, in the 1840s. This dataset is the result of a new geosampling methodology we devised, representing a key development in the agricultural and overall economic history of Southeast Europe and the Middle East.

The 1840s serve as a good period to choose for base years mainly due to three main factors to sample economic data on a regional scale. First, due to Tanzimat reforms (planned and only partially accomplished transformation of the Ottoman central administration in the mid-nineteenth century), the 1840s marked a watershed of bureaucratical information gathering. Especially, the temettuat registers were created as a by-product to realize a drastic change in tax collection. With at least in its first iteration, the unsuccessful abolishment of tax-farming by the Tanzimat decree in 1839, the Ottoman central administration aimed to transform the existing indirect and communal taxation with direct and individual modalities. To accomplish this goal, the administration had to survey the tax base, which was in disguise due to centuries-long tax farming practices. The temettuat registers were conducted in the core regions of the empire with the main exception of the imperial capital, Istanbul. Second, the 1840s correspond to the last period before the beginning of drastic territorial losses, primarily in Southeast Europe, which triggered in size and frequency unprecedented waves of emigration and immigration between the core territories of the empire both in Southeast Europe as well as in Anatolia, which continued until the official demise or the implosion of the empire. Third and lastly, the 1840s serves as a very suitable point to assess the dynamics of pre-industrial and ancienne regime agricultural dynamics due to the lack of modern means of mechanization, irrigation, and fertilization combined with extremely rudimentary transport facilities.

The temettuat surveys are invaluable resources for they provide agricultural asset- / crop-type specific agricultural mix information with cultivation area per household. However, extracting their detailed information requires a team and years. To overcome this, we developed a sampling strategy that selected five locations per subdistrict using the Analytical Hierarchy Process (AHP), considering factors of agricultural suitability (85% weight), connectivity to historical roads (within a 500-meter to the closest road or to the Danube, 15% weight, justified by its impact on suitability), and subdistrict population size (chosen villages must represent at least 5% of the subdistrict's total population).

Our geosampling methodology of the 1840s tax registers (temettuat) is based on contemporary Ottoman population registers. With this geosampling method, we aim to estimate the regional (district (sancak) and subdistrict (kaza)) level total area of cultivation and shares of the agricultural mix for key products. We are using two mid-nineteenth-century datasets: Ottoman tax (TMT) (temettuat) surveys for agricultural asset / crop type and cultivation area and the population (nüfus) (NFS) registers for population-based sampling. Connectivity is based on a detailed and provenly accurate 1940s German military map of Turkey, Deutsche Heereskarte (DHK). The agricultural suitability raster is an amalgamation of the Land Capability Classification (LCC) encapsulating the variables of soil quality and quantity and the Digital Elevation Model (DEM) based on Shuttle Radar Topography Mission with 30-meter-resolution and comprising elevation, slope, and ruggedness data.

In the end, a geosampling initiative was undertaken across six regions in Southeast Europe and Anatolia, namely Ankara, Bursa, Plovdiv, Ruse, Manisa, and Edirne, covering a total of 277 locations with 17,675 households. Our project team entered the economic data from those records into a Microsoft Access database. We employed a specially crafted data entry template to systematically organize the tax survey data into multiple categories.

After geosampling locations, our objective extended to deriving estimates for the total cultivated area within each subdistrict and regions. To achieve this goal, it was imperative that the data undergoes coding the cultivation areas into a standardized and comparable land-use scheme. We adopted the Corine Land Cover (CLC) nomenclature from the European Union's Earth Observation Programme (Copernicus), established in 1985 and regularly updated. Our study followed the revised guidelines issued by the European Environment Agency on 10.05.2019. Despite its primary design for contemporary land cover analysis, CLC nomenclature proved well-suited for accurately representing the agricultural tax data and the historical context of the 1845 Ottoman tax surveys.

In our analysis, we coded micro-level cultivated land entries associated with individual households, using CLC's highest detail level. Successfully, every cultivated land entry was coded into the third level of detail in CLC, encompassing sub-categories such as 2.1 – “Arable land”, 2.2 – “Permanent crops”, 2.3 – “Pastures”, and 2.4 – “Heterogeneous agricultural areas”—all falling under the overarching category of 2 - Agricultural areas. Additionally, we coded entries related to 3.1 - “Forest” and 3.2 – “Shrub and/or herbaceous vegetation associations”, falling under the primary category of 3 – “Forest and seminatural areas.”

Finally, cultivation area expressed in Ottoman measurement units like dönüm (1/9,2 of a hectare) are converted into hectares to ensure consistency and ease of spatiotemporal comparison.

We provide the geosample data of the Bursa region, positioned in Western Anatolia, renowned for its historical and economic significance, large and cosmopolitan population, and diverse geophysical characteristics. This data covers all the geosampled households, the individuals residing in them, and their CLC-coded agricultural assets / crops with quantity / cultivation area.

The Bursa region comprised 591 geolocated settlements in 12 subdistricts in 1840. Notably, the city of Bursa, serving as the major urban center and regional capital, was intentionally left out of the sample. Additionally, the subdistrict of Pazarköy, with its 14 settlements, was excluded. Despite being initially part of the Bursa region in population registers, it became attached to the northern neighboring Kocaili district in 1845. Consequently, out of the 576 remaining settlements, we geosampled 55 populated places from 11 subdistricts, covering 3547 households, representing 12% of the total households in the region, totaling 30,518. The variables of the tax surveys of the geosampled locations were read, extracted, and entered into the customized Microsoft Access database.

In the Bursa region, there are a total of 13,344 entries for agricultural assets coded with CLC across all 55 sampled populated areas. Our dataset includes all these entries and covers 3,325 households (out of the total of 3,547 sampled households) that owned these assets. This allows for a comprehensive analysis of the agricultural mix and land area at a detailed level.

The tax survey data was transcribed in Turkish using modern Turkish spelling and punctuation to keep the nuances of the original source. That said, because the original register information is largely presented in a standardized fashion and grouped under detailed variables, the data can easily be translated into other languages and coded into specific coding schemes.

The categories and descriptions of the variables of the geosample dataset for the Bursa region are as follows:

Between Art and Empire examines the ways in which the British Empire shaped the establishment, collection, and display practices of the National Gallery from its founding in 1824 to 1874. As one of Britain’s foremost public art institutions, the National Gallery provides a key case study for understanding the entanglement of British imperialism and cultural institutions in the nineteenth century. The Gallery was established at a time when Britain had been positioning itself as a global economic and political power through the dominance of the empire in its colonies. Its foundation relied on donations, bequests, purchases and time invested in trusteeships from individuals who were actively profiting from the systems of Empire. The thesis takes a broad view of the British Empire by considering imperial trade, commerce and slavery in both the British East and West Indies. It also adopts an intergenerational and interfamilial study to examine the complex connections between imperial wealth and cultural patronage. Few previous histories of the National Gallery have contextualised the institution within the broader framework of the British Empire, thus overlooking some of the important connections discussed in this thesis. Between Art and Empire begins with an expansive approach to institutional history to clarify some of the links that the National Gallery has with the British Empire. The focus is not solely on the ownership history of objects in the collection, but also encompasses the economic, social and ethical implications of the sources of wealth used to purchase these objects. It then highlights individual histories of Gallery stakeholders, their families, and the colonised people exploited by them to reveal the ways in which the personal intersects with larger societal systems, and networks of power and exploitation. This results in a complex and entangled relationship between the National Gallery and Britain’s colonial past.

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This dataset contains the data collected by Gaëtane Vallet regarding the entourage of Roman emperor Trajan, as well as the social networks extracted by Vincent Labatut from these data, and all the files resulting from their analysis. The associated R source code is available separately on GitHub : https://github.com/CompNet/TrajanNetThe various archives available in this dataset match the output folders of the R scripts. See the GitHub page for more details.If you use these data or this source code, please cite :------------- TODO ----------

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This dataset is about books. It has 2 rows and is filtered where the book is AQA GCSE history. Migration, empires and the people. It features 7 columns including author, publication date, language, and book publisher.

About this dataset

Context

The dataset tabulates the Empire town population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Empire town. The dataset can be utilized to understand the population distribution of Empire town by age. For example, using this dataset, we can identify the largest age group in Empire town.

Key observations

The largest age group in Empire, Wisconsin was for the group of age 50 to 54 years years with a population of 333 (12%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Empire, Wisconsin was the 80 to 84 years years with a population of 36 (1.30%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Empire town is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Empire town total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Empire town Population by Age. You can refer the same here