NOTE: 2001-2013 enlisted totals include "cadets-midshipmen" so officer+enlisted=total. This may not be the correct assumption, but the historical tables only have "officer" and "enlisted" totals.

Access a market-leading database of 18 million verified military veterans, backed by our money-back quality guarantee. Our veteran mailing lists are meticulously updated and verified every month to ensure accuracy. Understanding that every campaign is unique, we provide a comprehensive range of demographic and psychographic filters to help you target the exact veteran audience you need.

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Our military veterans email campaign offers targeted outreach to qualified veteran leads with a guaranteed open rate, ensuring your message reaches a receptive audience. After the campaign, you can opt to receive a list of veterans who opened your email, providing a valuable pool of warm leads for follow-up. If you prefer to manage your own campaign, we also offer highly accurate veteran email lists, complete with unlimited usage rights for ongoing marketing efforts.

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The World's Top Military Strength Dataset is a comprehensive compilation of data gathered from various reliable sources, providing a detailed analysis and comparison of the military capabilities of countries worldwide. This dataset serves as a valuable resource for policymakers, researchers, defense analysts, and military enthusiasts, enabling them to assess and understand the relative strength and capacities of different nations' armed forces.

The dataset encompasses a wide range of parameters that are crucial in evaluating military power. It includes both quantitative and qualitative metrics, capturing factors such as defense budget, personnel strength, equipment inventory, technological advancements, research and development investments, logistical capabilities, and more. By incorporating multiple dimensions, the dataset offers a comprehensive view of a country's military prowess.

Data within the dataset has been meticulously scraped and curated from reputable websites, government publications, defense journals, and international reports. Rigorous efforts have been made to ensure data accuracy and consistency, minimizing errors and biases to provide users with reliable information.

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

The dataset depicts the authoritative boundaries of the most commonly known Department of Defense (DoD) sites, installations, ranges, and training areas in the United States and Territories. 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 Deputy Under Secretary of Defense for Installations and Environment, Business Enterprise Integration Directorate. Sites were selected from the 2010 Base Structure Report (BSR), a summary of the DoD Real Property Inventory. This list does not necessarily represent a comprehensive collection of all Department of Defense facilities, and only those in the fifty United States and US Territories were considered for inclusion. 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.

This layer is sourced from maps.bts.dot.gov.

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.

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.

Information about the types of eating disorders, some reasons why the military community are at risk, warning signs and how to get help. The Missouri Eating Disorders Council (MOEDC) created this document so support service members, veterans and their families.

This dataset is about countries per year in the United Kingdom. It has 64 rows. It features 4 columns: country, armed forces personnel, and military expenditure.

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.

This dataset, released by DoD, contains geographic information for major installations, ranges, and training areas in the United States and its territories. This release integrates site information about DoD installations, training ranges, and land assets in a format which can be immediately put to work in commercial geospatial information systems. Homeland Security/Homeland Defense, law enforcement, and readiness planners will benefit from immediate access to DoD site location data during emergencies. Land use planning and renewable energy planning will also benefit from use of this data. Users are advised that the point and boundary location datasets are intended for planning purposes only, and do not represent the legal or surveyed land parcel boundaries.

SELECTED SOCIAL CHARACTERISTICS IN THE UNITED STATES VETERAN STATUS - DP02 Universe - Civilian population 18 Year and over Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 Veteran status is used to identify people with active duty military service and service in the military Reserves and the National Guard. Veterans are men and women who have served (even for a short time), but are not currently serving, on active duty in the U.S. Army, Navy, Air Force, Marine Corps, or the Coast Guard, or who served in the U.S. Merchant Marine during World War II. People who served in the National Guard or Reserves are classified as veterans only if they were ever called or ordered to active duty, not counting the 4-6 months for initial training or yearly summer camps.

Services and Support Programs for Military Service Members and Veterans, 2012-13 (PEQIS 19), is a study that is part of the Postsecondary Education Quick Information System (PEQIS) program; program data is available since 1997-98 at . PEQIS 19 (https://nces.ed.gov/peqis/) is a cross-sectional survey that collected information on the services and support programs available to students who are military service members and veterans at the institution. The study was conducted using self-administered paper-and-pencil questionnaires of a person at the postsecondary institution that is familiar with the institution programs for military service members and veterans. Key statistics produced from PEQIS 19 were services and support programs for military members and veterans.

This dataset is about countries per year in Zimbabwe. It has 64 rows. It features 4 columns: country, armed forces personnel, and military expenditure.

United States US: Military Expenditure: % of GDP data was reported at 3.149 % in 2017. This records a decrease from the previous number of 3.222 % for 2016. United States US: Military Expenditure: % of GDP data is updated yearly, averaging 4.864 % from Sep 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 9.063 % in 1967 and a record low of 2.908 % in 1999. United States US: Military Expenditure: % of GDP 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.; Weighted average; Data for some countries are based on partial or uncertain data or rough estimates.

This dataset list the total number of military and civilian personnel from 2001-2017. The dataset is separated in the following categories: gender, regular forces, reserve forces, officer and non-commissioned member (NCM).

The VIERS Military History service provides Veteran military history information that is consolidated across multiple data sources. This consolidated data is provided as part of the VRM initiative to improve the speed, accuracy and efficiency with which information is exchanged between Veterans and VA. This information is exposed to the VIERS Consumers via a SOAP based web service. It queries the VA/DoD Identity Repository (VADIR) and Corporate Database (CorpDB) repositories to retrieves electronic copies of military service information including periods of service, periods of captivity, and military pay. The VRM VIERS Military History Service also provides the capability to update the VA data repositories with unverified periods of service and unverified periods of captivity. Service provides a view of all military history to date(historical, current, retirement, Line of Duty/WII) for a partiular person such as branch, entry dates, separation dates, discharge characters. Provide definitive view of Veterans Military Service Information- Read access to veteran military service information (electronic DD-214/215)- Current member DoD affiliation status and information (Active duty, Guard/Reserve, Retired, Dependent)- DoD Eligibility and Entitlement (Insurance, Education)- DFAS Military Payments (severance, separation, retirement)- Supports submission by veterans of supplemental evidence of service (Vietnam Era)- Medals, awards

About this dataset

Context

The dataset tabulates the population of Soldiers Grove by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Soldiers Grove. The dataset can be utilized to understand the population distribution of Soldiers Grove by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Soldiers Grove. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Soldiers Grove.

Key observations

Largest age group (population): Male # 15-19 years (43) | Female # 10-14 years (39). 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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Soldiers Grove population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Soldiers Grove is shown in the following column.
• Population (Female): The female population in the Soldiers Grove is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Soldiers Grove for each age group.

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 Soldiers Grove Population by Gender. You can refer the same here

Analysis of ‘Female Active Duty Military Personnel, Officers and Enlisted, 1945-2015’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/beb86177-834e-4463-bc18-72de5d42c500 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

NOTE: 2001-2013 enlisted totals include "cadets-midshipmen" so officer+enlisted=total. This may not be the correct assumption, but the historical tables only have "officer" and "enlisted" totals.

--- Original source retains full ownership of the source dataset ---

Est. Date of completion => 31.03.2021

Collection of various Military Tanks worldwide and their specifications. Thanks to military-today.com & wikipedia.org for providing the necessary information.

The dataset contains a collection of various military war tanks along with their specifications. If you have any suggestion to make, please contact me at antoreepjana@yahoo.in