The world has become much more peaceful, and yet, even after adjusting for inflation, global military spending is now three times greater than at the height of the Cold War. These developments have motivated a renewed interest from both policy makers and scholars about the drivers of military spending and the implications that follow. Existing findings on the relationship between threat and arming and arms races and war hinge on the completeness and accuracy of existing military spending data. Moreover, data on military spending is used to measure important concepts from international relations such as the distribution of power, balancing, the severity of states’ military burdens, and arms races. Everything we know about which states are most powerful, whether nations are balancing, and whether military burdens and arms races are growing more or less severe rests on the accuracy of existing military spending estimates.

The Military Bases dataset was last updated on September 02, 2025 and are defined by Fiscal Year 2024 data, from the Office of the Assistant Secretary of Defense for Energy, Installations, and Environment and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The dataset depicts the authoritative locations of the most commonly known Department of Defense (DoD) sites, installations, ranges, and training areas world-wide. These sites encompass land which is federally owned or otherwise managed. This dataset was created from source data provided by the four Military Service Component headquarters and was compiled by the Defense Installation Spatial Data Infrastructure (DISDI) Program within the Office of the Assistant Secretary of Defense for Energy, Installations, and Environment. Only sites reported in the BSR or released in a map supplementing the Foreign Investment Risk Review Modernization Act of 2018 (FIRRMA) Real Estate Regulation (31 CFR Part 802) were considered for inclusion. This list does not necessarily represent a comprehensive collection of all Department of Defense facilities. For inventory purposes, installations are comprised of sites, where a site is defined as a specific geographic location of federally owned or managed land and is assigned to military installation. DoD installations are commonly referred to as a base, camp, post, station, yard, center, homeport facility for any ship, or other activity under the jurisdiction, custody, control of the DoD. While every attempt has been made to provide the best available data quality, this data set is intended for use at mapping scales between 1:50,000 and 1:3,000,000. For this reason, boundaries in this data set may not perfectly align with DoD site boundaries depicted in other federal data sources. Maps produced at a scale of 1:50,000 or smaller which otherwise comply with National Map Accuracy Standards, will remain compliant when this data is incorporated. Boundary data is most suitable for larger scale maps; point locations are better suited for mapping scales between 1:250,000 and 1:3,000,000. If a site is part of a Joint Base (effective/designated on 1 October, 2010) as established under the 2005 Base Realignment and Closure process, it is attributed with the name of the Joint Base. All sites comprising a Joint Base are also attributed to the responsible DoD Component, which is not necessarily the pre-2005 Component responsible for the site. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529039

Version 2 (18 March 2025) includes a further 356 service itineraries. In addition, 41 entries from the previous version were updated or expanded. Currently the database covers a total of 1,858 Jewish soldiers, 421 wives and 83 children.

ORIGINAL VERSION 1 (18 September 2024)

With more than 1,500 individual entries, this is the inaugural instalment of my research database collated in the framework of the Project Forgotten Soldiers: Jewish Military Experience in the Habsburg Monarchy. This is an open access database, and everyone is welcome to use it according to their own scholarly and personal interests. In 1,189 cases we have official documented records confirming the soldiers were Jewish. In another 313 entries I was able to identify likely Jewish soldiers based on circumstantial evidence cross-referencing names and places of birth, with the presence of confirmed Jewish soldiers drafted into the same units as part of the same recruitment drive. This dataset further includes evidence for 156 spouses and 47 children. While military records do mentions these, their number suggests that the Habsburg army preferred to enlist unmarried men.

The database is structured in a similar way to an official individual entry in the Habsburg military records. These were arranged in tables, with soldiers listed by seniority. Name, place and land of birth are followed by age and religion. This latter rubric allows identifying the bulk of the Jewish soldiers. Also included in the record is marital status, profession (if any), number, names and ages of children (if any), followed by a short summary text of the soldier’s service itinerary. While not always consistent in detail, these texts mention enlistment dates, transfers between units, promotions, desertions, periods as prisoner of war and military awards (if any). I have taken the material from the personal records and added several additional parameters:

The soldiers are entered into the database according to their date of enlistment. This is followed by a colour-coded table showing their years of service. To see the meaning of the different colours employed, scroll to the legend at the end of the dataset.

Following the years of service, we see the date when the soldier left service (final year in service for incomplete service records). When known, the reason the soldier left the army is given (discharge/ death/ desertion etc).

Then come the three most important columns within the table: service record, primary sources and units. At first glance, these columns have only a few letters and numbers, but bring your mouse courser onto the relevant field marked with red triangles. An additional window will then open:

a. Service Record: Shows the entire service record of the soldier arranged by date. I use original German as it appears in the archival records. If you see spelling differences with modern German – they are there for a reason.

b. Primary Sources: Provides the information on all the archival records consulted to reconstruct the service itinerary. The number in the field denotes the number of the archival cartons consulted.

c. Units: Number of units in which a soldier serves. Bringing the cursor on to the field will open their list. Most Jewish soldiers served in the line infantry (IR) and the Military Transport Corps (MFWK or MFK). However, there were also Jewish sharpshooters, cavalrymen, gunners and even a few members of the nascent Austrian Navy.

The next two columns provide entries of the soldier’s conduct and medical condition, which in Habsburg military jargon was referred to rather callously as Defekten. I note the original medical diagnoses verbatim. When possible to identify, I note the modern medical term.

General database-wide parameters are then noted in the next part of the table. Among others, it provides information on enlistment type (conscript/ volunteer?), main branches of service (such as Infantry/ Cavalry/ Artillery), and roles within the military (such as non-commissioned officers/ drummers/ medics).

Concluding this part of the table are columns covering desertions, periods as prisoner of war and awards of the army cannon cross (for veterans of 1813-14) and other military awards.

The last column provides the original German outtake rubric as to how the soldier left service. In special cases, additional service notes are provides on the right.

How to use this dataset

This depends on what you are looking for. Firstly, download the dataset on to your computer via the link provided below. It is a simple Excel file which is easy to work with. If you wish to find out whether one of your ancestors served in the Habsburg army, use a simple keyword search. Please note that in our period there was no single accepted orthography meaning that some letters were used interchangeably (for instance B/P; D/T). There were also various patronymic suffices used in different parts of the monarchy (-witz in German/ -wicz in Polish/ -vits in Hungarian). Habsburg military clerks were mostly German speakers who often recorded the name phonetically. For instance, Jankel/ Jankl/ Jacob/ Jacobus all denote the same name. A Jewish teenager who identified himself as Moische when first reporting to duty, may have stayed so in the military records for decades, even if he was already a non-commissioned officer whose subordinates referred to as Herr Corporal.

If you study the history of concrete Jewish communities, use the keyword search and the filter option to find entries in the database where this locality is mentioned. Some places like Prague and Lublin could be identified effortlessly. In other cases (and see the above point on German-speaking clerks), place names were recorded phonetically. The military authority usually stuck to official Polish names in Galicia, and Hungarian in the Lands of the Crown of St. Stephan. In reality, a Jewish recruit from Transcarpathian Ruthenia could have his place of birth recorded in Hungarian, Romanian or Rusin. When I could not identify the place in question, I marked it with italics. Do you think you identified something I could not? Excellent! Then please write me, and I will correct the entry in the next instalment of this database.

I should stress that, currently, the database is not statistically representative. I have worked chronologically, meaning that there are disproportionally more entries for Jewish soldiers from the Turkish War, the first two Coalition Wars, and the Wars of 1805 and 1809. If you look at some of my other databases (for instance, that of the 1st Line Infantry Regiment 'Kaiser'), you will find least as many Jews who served in the wars of 1813-15. I will cover these in due course. This said, using the filter option of the Excel sheet, you can already make some individual queries. For instance, did Jewish grenadiers meet the minimal height requirement to be eligible for transfer into the elite infantry? (Hint: they did not!) If you are interested in the historical study of nutritional standards, compare the height of the soldiers with their year and place of birth. In my other project, I made calculations of the average height of Habsburg soldiers and I can already reveal that Jewish conscripts were, on average, several centimetres smaller than their non-Jewish comrades drafted in the same annual intake. Whatever stereotypes said, most Jews in the Habsburg Monarchy around 1800 were very poor and the sad fact of malnutrition as a child is reflected in their height as adults.

I should stress that this is a cumulative database. ZENODO has an excellent feature allowing updated versions to supersede earlier files while retaining the same DOI (Digital Object Identifier) and metadata. As my research progresses, I plan to upload new versions of this database bi-annually. This includes not only adding new entries, but also expanding and correcting existing ones. It might well be that the service record of a soldier covered up to 1806 will be brought to a later date, possibly even to his discharge from the army. If you have not found whom you are looking for, or if you want to work with larger samples for your research, visit this page again in a few months’ time. And if you do use this database for scholarly research (by all means, please do), do not forget to cite it as you would cite any other item in your bibliography! If you are a museum professional and you want to employ material from your database to illustrate your exhibitions, you are welcome, but please cite this resource for others to learn. Links to this database will also be appreciated.

This dataset displays the number of active duty personnel and their location, by country. Included in these figures are the numbers for Army, Navy, Marine, and Air Force branches of the United States Military. Note: this data includes rounded figures for personnel involved in Operation Iraqi Freedom (OIF)and Operation Enduring Freedom (OEF). This data was collected from the department of Defense directly at: http://siadapp.dmdc.osd.mil/personnel/MILITARY/history/hst0706.pdf .

This project updates INTERNATIONAL MILITARY INTERVENTION (IMI), 1946-1988 (ICPSR 6035), compiled by Frederic S. Pearson and Robert A. Baumann (1993). This newer study documents 447 intervention events from 1989 to 2005. To ensure consistency across the full 1946-2005 time span, Pearson and Baumann's coding procedures were followed. The data collection thus "documents all cases of military intervention across international boundaries by regular armed forces of independent states" in the international system (Pearson and Baumann, 1993). "Military interventions are defined operationally in this collection as the movement of regular troops or forces (airborne, seaborne, shelling, etc.) of one country inside another, in the context of some political issue or dispute" (Pearson and Baumann, 1993). As with the original IMI (OIMI) collection, the 1989-2005 dataset includes information on actor and target states, as well as starting and ending dates. It also includes a categorical variable describing the direction of the intervention, i.e., whether it was launched in support of the target government, in opposition to the target government, or against some third party actor within the target state's borders. The intensity of the military intervention is captured in ordinal variables that document the scale of the actor's involvement, "ranging from minor engagement such as evacuation, to patrols, act of intimidation, and actual firing, shelling or bombing" (Pearson and Baumann, 1993). Casualties that are a direct result of the military intervention are coded as well. A novel aspect of IMI is the inclusion of a series of variables designed to ascertain the motivations or issues that prompted the actor to intervene, including to take sides in a domestic dispute in the target state, to affect target state policy, to protect a socio-ethnic or minority group, to attack rebels in sanctuaries in the target state, to protect economic or resource interests, to intervene for strategic purposes, to lend humanitarian aid, to acquire territory or to dispute its ownership, and to protect its own military/diplomatic interests. There are three main differences between OIMI and this update. First, the variable, civilian casualties, which complements IMI's information on the casualties suffered by actor and target military personnel has been added. Second, OIMI variables on colonial history, previous intervention, alliance partners, alignment of the target, power size of the intervener, and power size of the target have been deleted. The Web-based resources available today, such as the CIA World Fact Book, make information on the colonial history between actor and target readily available. Statistical programs allow researchers to generate all previous interventions by the actor into the target state. Since competing measures and data collections are used for alliances and state power, it was thought best to allow analysts who use IMI the freedom to choose the variables or dataset that measure the phenomena of their choice. Third, the data collection techniques differ from OIMI. OIMI relied on the scouring of printed news sources such as the New York Times Index, Facts on File, and Keesing's to collect information on international military interventions, whereas the computer-based search engine, Lexis-Nexis Academic, was used as the foundation for the new study's data search. Lexis-Nexis Academic includes print sources as well as news wire reports and many others. After Lexis-Nexis searches were conducted for each year in the update by at least four different investigators, regional sources, the United Nations Web site, and secondary works were consulted.

Bangladesh BD: Armed Forces Personnel: Total data was reported at 227,000.000 Person in 2020. This stayed constant from the previous number of 227,000.000 Person for 2019. Bangladesh BD: Armed Forces Personnel: Total data is updated yearly, averaging 214,000.000 Person from Jun 1985 (Median) to 2020, with 33 observations. The data reached an all-time high of 252,000.000 Person in 2005 and a record low of 91,300.000 Person in 1985. Bangladesh BD: Armed Forces Personnel: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bangladesh – Table BD.World Bank.WDI: Defense and Official Development Assistance. Armed forces personnel are active duty military personnel, including paramilitary forces if the training, organization, equipment, and control suggest they may be used to support or replace regular military forces.;International Institute for Strategic Studies, The Military Balance.;Sum;Data for some countries are based on partial or uncertain data or rough estimates.

Here are a few use cases for this project:

1. Military Intelligence and Threat Analysis: Utilize the "Army_type" computer vision model to analyze satellite images, drone feeds, or ground-level reconnaissance imagery to identify and monitor movement or positions of various military units. This information can assist in assessing potential threats, providing valuable insights for decision-making in national defense operations.

2. Geopolitical Conflict Monitoring: The model can be employed in monitoring and tracking the movements of military assets and troops in regions of geopolitical tensions or disputed territories. Understanding the distribution of military forces can help predict potential conflict flashpoints and help in implementing diplomatic solutions before any escalation.

3. Search and Rescue Operations: In disaster scenarios or during military operations, the "Army_type" model can aid in identifying locations of specific military units or assets that might require immediate assistance. The information gathered from real-time analysis can help coordinate search and rescue efforts or assist in evacuating military personnel from high-threat areas.

4. Military Base Planning and Security: The model can contribute to the efficient base planning for armed forces. By analyzing surrounding areas, the model can identify potential threats or vulnerabilities, enabling authorities to make informed decisions on base fortifications and resource allocation to guarantee the safety of military personnel and assets.

5. Training and Simulation Exercises: The "Army_type" computer vision model can be integrated into military training programs, providing realistic simulations to prepare military personnel for real-world scenarios. The model can help create objective evaluations of exercises by continuously monitoring and identifying individual units, allowing for more focused feedback and better understanding of potential strengths and weaknesses in strategic maneuvers.

United States US: Military Expenditure data was reported at 609.758 USD bn in 2017. This records an increase from the previous number of 600.106 USD bn for 2016. United States US: Military Expenditure data is updated yearly, averaging 277.591 USD bn from Sep 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 711.338 USD bn in 2011 and a record low of 45.380 USD bn in 1960. United States US: Military Expenditure data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Defense and Official Development Assistance. Military expenditures data from SIPRI are derived from the NATO definition, which includes all current and capital expenditures on the armed forces, including peacekeeping forces; defense ministries and other government agencies engaged in defense projects; paramilitary forces, if these are judged to be trained and equipped for military operations; and military space activities. Such expenditures include military and civil personnel, including retirement pensions of military personnel and social services for personnel; operation and maintenance; procurement; military research and development; and military aid (in the military expenditures of the donor country). Excluded are civil defense and current expenditures for previous military activities, such as for veterans' benefits, demobilization, conversion, and destruction of weapons. This definition cannot be applied for all countries, however, since that would require much more detailed information than is available about what is included in military budgets and off-budget military expenditure items. (For example, military budgets might or might not cover civil defense, reserves and auxiliary forces, police and paramilitary forces, dual-purpose forces such as military and civilian police, military grants in kind, pensions for military personnel, and social security contributions paid by one part of government to another.); ; Stockholm International Peace Research Institute (SIPRI), Yearbook: Armaments, Disarmament and International Security.; ; Data for some countries are based on partial or uncertain data or rough estimates. For additional details please refer to the military expenditure database on the SIPRI website: https://sipri.org/databases/milex

This dataset gives spending on defense programs for the most recent year available as a percent of gross domestic product (GDP); the GDP is calculated on an exchange rate basis, i.e., not in terms of purchasing power parity (PPP). Source: CIA World Factbook 2007: https://www.cia.gov/library/publications/the-world-factbook/docs/notesanddefs.html#2010 Accessed: 10.2.07

The United States Military Installations database contains the boundaries and location information for important military installations in the United States and Puerto Rico. The database includes records for 405 military installations. Source: National Transportation Atlas Database URL: http://www.bts.gov/publications/national_transportation_atlas_database/2006/

The National Waterway Network is a comprehensive network database of the nation's navigable waterways. The data set covers the 48 contiguous states plus the District of Columbia, Hawaii, Alaska, Puerto Rico and water links between. The nominal scale of the dataset varies with the source material. The majority of the information is at 1:100,000 with larger scales used in harbor/bay/port areas and smaller scales used in open waters. Purpose: The National Waterway Network is a geographic database of navigable waterways in and around the United States, for analytical studies of waterway performance, for compiling commodity flow statistics, and for mapping purposes.

Gabon GA: Military Expenditure data was reported at 175,400.000 XAF mn in 2017. This records an increase from the previous number of 120,300.000 XAF mn for 2016. Gabon GA: Military Expenditure data is updated yearly, averaging 39,000.000 XAF mn from Dec 1967 (Median) to 2017, with 34 observations. The data reached an all-time high of 175,400.000 XAF mn in 2017 and a record low of 740.000 XAF mn in 1968. Gabon GA: Military Expenditure data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Gabon – Table GA.World Bank.WDI: Defense and Official Development Assistance. Military expenditures data from SIPRI are derived from the NATO definition, which includes all current and capital expenditures on the armed forces, including peacekeeping forces; defense ministries and other government agencies engaged in defense projects; paramilitary forces, if these are judged to be trained and equipped for military operations; and military space activities. Such expenditures include military and civil personnel, including retirement pensions of military personnel and social services for personnel; operation and maintenance; procurement; military research and development; and military aid (in the military expenditures of the donor country). Excluded are civil defense and current expenditures for previous military activities, such as for veterans' benefits, demobilization, conversion, and destruction of weapons. This definition cannot be applied for all countries, however, since that would require much more detailed information than is available about what is included in military budgets and off-budget military expenditure items. (For example, military budgets might or might not cover civil defense, reserves and auxiliary forces, police and paramilitary forces, dual-purpose forces such as military and civilian police, military grants in kind, pensions for military personnel, and social security contributions paid by one part of government to another.); ; Stockholm International Peace Research Institute (SIPRI), Yearbook: Armaments, Disarmament and International Security.; ; Data for some countries are based on partial or uncertain data or rough estimates. For additional details please refer to the military expenditure database on the SIPRI website: https://sipri.org/databases/milex

Foreign military training has become a key component of the United States’ security policy. What explains the variation in US training allocation across countries and over time? Past work on security assistance, such as training, focuses on its effectiveness and consequences, largely overlooking questions about which countries receive it in the first place. To understand what drives US military training partnerships, we conducted a global statistical analysis of training from 1999 to 2018, structured around four logics: building relationships through defense diplomacy, deterrence against external, interstate threats, capacity-building in fragile states, and promoting democratic norms to advance democracy around the world. We find that the four logics receive support, with relationship-building and response to interstate and internal threats most consistently so. This analysis demonstrates the different ways the United States has used training in support of the US-led global order and raises questions about how to achieve accountability given these multiple logics. More broadly, the findings also have relevance for understanding how other states allocate training in conjunction with, in emulation of, or in opposition to the United States.

This dataset includes over 200 US military cemeteries, compiled using information from the National Cemetery Administration, National Park Service, American Battlefield Commission, US Army, state veterans departments, and others. For the majority of cemeteries, within the description field, you will find a link to the cemetery's web page along with the physical address. This data was found online at http://bbs.keyhole.com/ubb/showflat.php/Cat/0/Number/132750/an/0/page/0#132750.

Dataset description

Based on databases, scientific and internet publications, this dataset lists small armed UAVs and missiles deployed and used worldwide, as well as systems under research and development, with their properties. Non-armed UAVs are included to investigate the global usage of small UAVs and thus overall interest in smaller systems. This comprises non-armed systems which could be provided with or used as weapons.

The two datasets list properties of small and very small UAVs below 2 m size (wingspan, length and rotor diameter) and of missiles with diameters below 69 mm. Currently (Version 2.0) the datasets are comprised of 152 UAVs and 50 missiles, respectively.

In order to minimise a contribution to proliferation of these systems, only public sources were investigated, i.e. the internet as well as publicly available databases and catalogues. Furthermore, where information is incomplete, no estimates based on the laws of physics or stemming from engineering expertise are given. Improvised or modified versions of UAVs or missiles, already in use by non-state actors, are left out for the same reason.

As far as has been available, for UAVs the basic properties with the year of introduction are listed to allow statements on trends of UAV capabilities in recent years. Due to the sheer number of UAV types available today, we focused mainly on UAVs intended to fulfil military roles, such as reconnaissance or combat. An exception are UAVs that fall under the very small (<0.2 m) category. There, most UAVs are still in the research or development stages and not in military service nor designed for military use. However, research and development (R&D) of some systems had been funded originally by military institutions. In any case, these projects are important indicators of the future potential of these small-sized aircraft.

Project Webpage

The datasets are a part of the research project "Preventive Arms Control for Small and Very Small Aircraft and Missiles" of TU Dortmund University. The project has been funded by the German Foundation for Peace Research (DSF, https://bundesstiftung-friedensforschung.de/) in its funding line "New Technologies: Risks and Chances for International Security and Peace".

For a full description of this project, visit https://url.tu-dortmund.de/pacsam.

The hydro polygon/arc coverages were created using TIGER/LINE 2000 shapefile data gathered from ESRI's Geography Network. The individual county hydrography line shapefiles were processed into Arc/Info coverages and then appended together to create complete state coverages. They were then edited to remove unwanted features, leaving a state-by-state database of both important and navigable water features. Attributes were added to denote navigable features and names. Also, an attribute was added to the polygons to denote which were water and which were land features. The state databases were then appended together to create a single, nationwide hydrography network containing named arcs and polygons. These features also contain a state FIPS. Because some of the hydro features are represented by lines instead of polygons, the complete hydro dataset consists of 2 shapefiles, one for lines and one for polygons. They must be used together to paint a complete picture.

Iceland IS: Military Expenditure data was reported at 0.000 ISK mn in 2017. This stayed constant from the previous number of 0.000 ISK mn for 2016. Iceland IS: Military Expenditure data is updated yearly, averaging 0.000 ISK mn from Dec 1960 (Median) to 2017, with 58 observations. Iceland IS: Military Expenditure data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Iceland – Table IS.World Bank.WDI: Defense and Official Development Assistance. Military expenditures data from SIPRI are derived from the NATO definition, which includes all current and capital expenditures on the armed forces, including peacekeeping forces; defense ministries and other government agencies engaged in defense projects; paramilitary forces, if these are judged to be trained and equipped for military operations; and military space activities. Such expenditures include military and civil personnel, including retirement pensions of military personnel and social services for personnel; operation and maintenance; procurement; military research and development; and military aid (in the military expenditures of the donor country). Excluded are civil defense and current expenditures for previous military activities, such as for veterans' benefits, demobilization, conversion, and destruction of weapons. This definition cannot be applied for all countries, however, since that would require much more detailed information than is available about what is included in military budgets and off-budget military expenditure items. (For example, military budgets might or might not cover civil defense, reserves and auxiliary forces, police and paramilitary forces, dual-purpose forces such as military and civilian police, military grants in kind, pensions for military personnel, and social security contributions paid by one part of government to another.); ; Stockholm International Peace Research Institute (SIPRI), Yearbook: Armaments, Disarmament and International Security.; ; Data for some countries are based on partial or uncertain data or rough estimates. For additional details please refer to the military expenditure database on the SIPRI website: https://sipri.org/databases/milex

This dataset is part of the TransWarSoldierWWII project, funded under the European Commission’s Horizon Europe program (Grant agreement ID: 101063708, DOI: 10.3030/101063708). It provides an overview of wartime letterswritten by non-German volunteers and conscripts from Belgium (BE), the Netherlands (NL), and Luxembourg (LU) who served in the Waffen-SS during World War II.

The dataset does not contain full letter texts but includes structured metadata, case study overviews, and thematic tagging, enabling researchers to analyze the letters’ historical context and content without direct access to sensitive personal writings.

This is the first attempt to record the Jewish soldiers who became casualties in the numerous Wars between the Habsburg Monarchy and Revolutionary and Napoleonic France. Jewish military service in the Austrian and Austro-Hungarian army from the mid-19th century onwards, especially during the First World War, is well known and documented. By contrast, nothing comparable has been done for the very first Jewish soldiers in modern history. The time has come to set the record straight!

The current database was compiled from the personal records of the War Archive (Kriegsarchiv) of the Austrian State Archives. At that time, the Habsburg army did not publish casualty lists other than mentioning the names of the most senior officers. To find individual Jewish soldiers who became casualties, one must identify serving Jewish soldiers in the regular musters and revision papers. Those found so far can be seen in the database Jewish Soldiers of the Habsburg Army (1788-1820), which should be used in parallel with this one. The current database offers an outtake with a separate list of Jewish soldiers who were killed, wounded, missing in action, or taken prisoner. The first version has 253 entries. These are arranged chronologically based on the date the soldier first became a casualty. The name of the battle or the action shows at the top of the table. Under each such action, up to four sub-categories are given:

1. K/KIA (Killed in Action) – Soldier killed outright in combat. Readers might be surprised how few such cases appear in the database. There are several possible reasons. Firstly, since 1781 the Habsburg manpower reports began to omit the rubric Vor Feind geblieben (left in front of the enemy) denoting soldiers killed in battle. This was part of a broader rationalisation of military records in the early days of Joseph II’s rule. Whichever was the cause of their death, all fatalities were now perceived as irrecoverable manpower wastage. Soldiers who died in service were now simply marked as gestorben. Identifying combat deaths is only possible by looking at monthly reports called Standes- und Diensttabellen. Even then, the number of combat deaths remains extraordinarily low. It appears that the Habsburg army formally recorded a soldier as ‘killed in action’ only if the body was identified. For this to happen, the army had to remain in control of the battlefield – in other words, the battle had to be won. For much of the Revolutionary and Napoleonic period, this was rarely the case on the Austrian side. It appears that most combat deaths in the period landed in the rubric as ‘missing-in-action’.

2. W/WIA (Wounded in Action) – Muster rolls did not record wounds at all. Monthly tables did so very rarely. The latter were intended primarily as financial documents to record the source of the men’s pay. When a soldier entered hospital, his pay was issued from the hospital fund whose accounts were later reimbursed by the man’s regiment. While dates of hospitalisation were meticulously recorded, the cause of hospitalisation was not mentioned. In most cases, identifying wounded soldiers can only be done indirectly. When dozens or hundreds of men from the same unit were hospitalised on the same day directly after a major battle, it can be reasonably assumed that these were combat casualties. A sure way of identifying a wounded soldier was through the medical evaluation papers (Superarbitrierungs-Liste), which were filed for men no longer fit for wartime service. These papers always mentioned combat wounds, as this was a major argument in favour of making the soldier eligible for admission into the invalids. Unfortunately, the survival rate of these documents is variable and the majority simply do not exist. This database employs two categories for wounded soldiers. When medical papers or hospitalisation date allows clear identification, a soldier is entered into the database as a certain case. When broader context allows (such as wartime service and numerous other hospitalisations from the same company on the same day, suggesting a skirmish), such men are entered as probable cases.

3. P/POW (Prisoner of War) – Unlike the previous two rubrics, the Habsburg military records usually mentioned soldiers taken prisoner (Kriegsgefangen/ In Kriegsgefangenschaft gefallen). The reason was again financial. Firstly, returning men had to be issued with backpay. Secondly, from the Third Coalition War onwards, reciprocal wartime prisoner swaps (Cartel) were discontinued, but the system remained in place to ensure that mutual settlement of accounts between two belligerent armies could happen after the war. This is not the only reason why prisoners make the largest single category in our database. For much of the Revolutionary and Napoleonic period, entire Austrian army corps were forced to surrender (for instance in Ulm in 1805). This happened so often that musters from 1806 and 1811 sometimes blankly omitted case of POWs, based on the assumption that nearly every soldier fell prisoner in the previous war. Therefore, for regiments who fought in Germany and Austerlitz in 1805, and in Bavaria and Deutsch-Wagram in 1809, one must also consult the monthly tables.

4. M/MIA (Missing in Action) – Recorded as Vor Feind vermisst or vermisst for short, this category denotes men who were missing when the battle ended. Anything could have happened to them. Some were dead (see rubric one), but others were taken prisoner, were lost, or deserted. The army recorded such missing men for the same reason as prisoners of war – to settle their backpay in future if necessary.

The total for each category of casualties is given at the bottom of the table for every war fought by the Habsburg army from 1792 to 1815. At the right hand side of the table are the grand totals for each category marked in red. At the end of every personal record are fields showing what happened to the soldier after he became a casualty. Wounded could recover or perish in hospital, while the prisoners and the missing could return. The same soldier could appear in the database more than once as he could be taken prisoner, be wounded or go missing several times. Only for those killed in action could the record be closed. For those who survived, the final fate was noted where known: discharge (including sub category), invaliding, desertion, or non-combat death. Men still in service when last mentioned in the documents are noted as ‘serves’. Whether complete or not, a detailed service record for each soldier as as I could reconstruct it from the sources is available in the database Jewish Soldiers of the Habsburg Army (1788-1820).

Sweden SE: Military Expenditure data was reported at 47,605.000 SEK mn in 2017. This records an increase from the previous number of 46,491.000 SEK mn for 2016. Sweden SE: Military Expenditure data is updated yearly, averaging 31,289.000 SEK mn from Jun 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 47,605.000 SEK mn in 2017 and a record low of 2,725.500 SEK mn in 1960. Sweden SE: Military Expenditure data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sweden – Table SE.World Bank.WDI: Defense and Official Development Assistance. Military expenditures data from SIPRI are derived from the NATO definition, which includes all current and capital expenditures on the armed forces, including peacekeeping forces; defense ministries and other government agencies engaged in defense projects; paramilitary forces, if these are judged to be trained and equipped for military operations; and military space activities. Such expenditures include military and civil personnel, including retirement pensions of military personnel and social services for personnel; operation and maintenance; procurement; military research and development; and military aid (in the military expenditures of the donor country). Excluded are civil defense and current expenditures for previous military activities, such as for veterans' benefits, demobilization, conversion, and destruction of weapons. This definition cannot be applied for all countries, however, since that would require much more detailed information than is available about what is included in military budgets and off-budget military expenditure items. (For example, military budgets might or might not cover civil defense, reserves and auxiliary forces, police and paramilitary forces, dual-purpose forces such as military and civilian police, military grants in kind, pensions for military personnel, and social security contributions paid by one part of government to another.); ; Stockholm International Peace Research Institute (SIPRI), Yearbook: Armaments, Disarmament and International Security.; ; Data for some countries are based on partial or uncertain data or rough estimates. For additional details please refer to the military expenditure database on the SIPRI website: https://sipri.org/databases/milex