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.

The dataset is derived from Google Earth data, collected 3,000 remotely sensed images from more than 40 military scenarios within Asia, North America and Europe, and 32,626 military vehicle targets were acquired from the remotely sensed images. The spatial resolution of the image is 0.3m and the size is 640× 640. The dataset consists of remotely sensed images and corresponding labeled files, and the targets were manually selected and classified by experts through the interpretation of high-resolution optical images. The granular categories in the dataset are divided into five categories based on vehicle size and military function: Small Military Vehicles (SMV), Large Military Vehicles (LMV), Armored Fighting Vehicles (AFV), Military Construction Vehicles (MCV), and Civilian Vehicles (CV). Military Construction Vehicles (MCV), Civilian Vehicles (CV). The geographic environments of the samples include cities, plains, mountains and deserts.

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.

Although, in many countries, the military is the most trusted state institution, we know little about public trust in the military outside the United States. We argue that, for the military, trust is grounded in its legitimation as, and aspiration to be, non-partisan. From this insight, we develop hypotheses regarding the relationship between trust in the military and other institutions, the military’s centrality to political power, intrastate conflict, and recruitment format. Using cross-national data (2006–2021), we find support for these hypotheses. Falling trust in partisan state institutions benefits the armed forces. When the military exercises influence over politics, at odds with its legitimation, it is judged by the usual standards of government performance. Civil wars convert the military into a factional actor, and public trust falls. When militaries recruit via selective conscription, confidence suffers. These findings have important implications for civil-military relations, military effectiveness, and democratic stability.

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.

This dataset was updated April, 2024.This ownership dataset was generated primarily from CPAD data, which already tracks the majority of ownership information in California. CPAD is utilized without any snapping or clipping to FRA/SRA/LRA. CPAD has some important data gaps, so additional data sources are used to supplement the CPAD data. Currently this includes the most currently available data from BIA, DOD, and FWS. Additional sources may be added in subsequent versions. Decision rules were developed to identify priority layers in areas of overlap.Starting in 2022, the ownership dataset was compiled using a new methodology. Previous versions attempted to match federal ownership boundaries to the FRA footprint, and used a manual process for checking and tracking Federal ownership changes within the FRA, with CPAD ownership information only being used for SRA and LRA lands. The manual portion of that process was proving difficult to maintain, and the new method (described below) was developed in order to decrease the manual workload, and increase accountability by using an automated process by which any final ownership designation could be traced back to a specific dataset.The current process for compiling the data sources includes: Clipping input datasets to the California boundary Filtering the FWS data on the Primary Interest field to exclude lands that are managed by but not owned by FWS (ex: Leases, Easements, etc) Supplementing the BIA Pacific Region Surface Trust lands data with the Western Region portion of the LAR dataset which extends into California. Filtering the BIA data on the Trust Status field to exclude areas that represent mineral rights only. Filtering the CPAD data on the Ownership Level field to exclude areas that are Privately owned (ex: HOAs) In the case of overlap, sources were prioritized as follows: FWS > BIA > CPAD > DOD As an exception to the above, DOD lands on FRA which overlapped with CPAD lands that were incorrectly coded as non-Federal were treated as an override, such that the DOD designation could win out over CPAD.In addition to this ownership dataset, a supplemental _source dataset is available which designates the source that was used to determine the ownership in this dataset.Data Sources: GreenInfo Network's California Protected Areas Database (CPAD2023a). https://www.calands.org/cpad/; https://www.calands.org/wp-content/uploads/2023/06/CPAD-2023a-Database-Manual.pdf US Fish and Wildlife Service FWSInterest dataset (updated December, 2023). https://gis-fws.opendata.arcgis.com/datasets/9c49bd03b8dc4b9188a8c84062792cff_0/explore Department of Defense Military Bases dataset (updated September 2023) https://catalog.data.gov/dataset/military-bases Bureau of Indian Affairs, Pacific Region, Surface Trust and Pacific Region Office (PRO) land boundaries data (2023) via John Mosley John.Mosley@bia.gov Bureau of Indian Affairs, Land Area Representations (LAR) and BIA Regions datasets (updated Oct 2019) https://biamaps.doi.gov/bogs/datadownload.htmlData Gaps & Changes:Known gaps include several BOR, ACE and Navy lands which were not included in CPAD nor the DOD MIRTA dataset. Our hope for future versions is to refine the process by pulling in additional data sources to fill in some of those data gaps. Additionally, any feedback received about missing or inaccurate data can be taken back to the appropriate source data where appropriate, so fixes can occur in the source data, instead of just in this dataset.24_1: Input datasets this year included numerous changes since the previous version, particularly the CPAD and DOD inputs. Of particular note was the re-addition of Camp Pendleton to the DOD input dataset, which is reflected in this version of the ownership dataset. We were unable to obtain an updated input for tribral data, so the previous inputs was used for this version.23_1: A few discrepancies were discovered between data changes that occurred in CPAD when compared with parcel data. These issues will be taken to CPAD for clarification for future updates, but for ownership23_1 it reflects the data as it was coded in CPAD at the time. In addition, there was a change in the DOD input data between last year and this year, with the removal of Camp Pendleton. An inquiry was sent for clarification on this change, but for ownership23_1 it reflects the data per the DOD input dataset.22_1 : represents an initial version of ownership with a new methodology which was developed under a short timeframe. A comparison with previous versions of ownership highlighted the some data gaps with the current version. Some of these known gaps include several BOR, ACE and Navy lands which were not included in CPAD nor the DOD MIRTA dataset. Our hope for future versions is to refine the process by pulling in additional data sources to fill in some of those data gaps. In addition, any topological errors (like overlaps or gaps) that exist in the input datasets may thus carry over to the ownership dataset. Ideally, any feedback received about missing or inaccurate data can be taken back to the relevant source data where appropriate, so fixes can occur in the source data, instead of just in this dataset.

The Pluralistic Memories Project (PMP) has been funded in 2014 for a period of 6 years. Through a mixed methodology, PMP gathered personal memories of events related to past conflicts that happened in Burundi, Palestine and Sri Lanka, three former colonies that have been struggling with violent civil conflicts. PMP aims to document the diversity of memories about these past conflicts, to examine the processes through which war narratives become official or fall into oblivion, and to support local researchers who study collective memories in conflict-torn societies. The project brings together Burundian, Sri Lankan, Palestinian, Swiss and other international researchers from different scientific disciplines who are guided by a common question: Can the preservation of a plurality of living memories make communities more resilient in face of the exploitation of yesterday’s trauma by tomorrow’s warmongers? PMP data is of multiple type. First, PMP conducted approximately 180+ semi-directive interviews. These interviews were done in the field by local PMP researchers that all shared a common thematic and methodology. Most of these interviews were then transcribed, anonymized, translated into english and documented. In Sri Lanka and Palestine, PMP also gathered data through two quantitative surveys (+ 2 pilots) that were conducted in the field. Particular attention was made to find representative samples that could reflect the diversity of memories. A last, PMP did 2 web surveys in Burundi, that were focused on the Burundian diaspora (so people of Burundi that live, or lived, outside Burundi). Most of the anonymized data that was gathered by PMP is now available here under various licenses (depending on the sensitiveness of the data and the level of consent of participants). Actually, most of PMP data could still be sensitive in some contexts or for some uses. This more sensitive data is only available after the acceptance of a research project proposed by the requester.

Community and Identity in the Roman Seventh Legio: Digitally mapping funerary monuments referring to Legio VII servicemen and related members of the military community in Roman Dalmatia

Abstract

This database was designed to facilitate and supplement archaeological and epigraphical research conducted as part of a Master of Research thesis submitted in December 2020. The project builds upon and digitises the robust catalogic work of scholars local to the modern region, such as Domagoj Tončinić's 'Monuments of Legio VII in the Roman Province of Dalmatia'. This database stores various types of geographical, epigraphical, visual, and historical data related to Roman funerary and sacral inscriptions belonging to, or commemorating, servicemen or veterans of the Roman Seventh Legion (Legio VII) in the province of Dalmatia (the modern Eastern Adriatic coastline and hinterland). This project, and the related thesis 'Fratres Romani in Dalmatia’, investigated the social dynamics of Legio VII, as well as processes of identity and community construction within the unit. It is hoped that this dataset will facilitate future research into military life in Dalmatia, as well as investigations of other corpora of Roman funerary stelae, as the general form of the dataset is transplantable onto epigraphical material from different regions of the Roman world.

Period

Early Roman Empire (30 BCE – 259 CE)

Potential Applications of the Data

The dataset has been collated to facilitate further research into the seventh legion in Dalmatia and their monuments. The structure of this dataset has also been designed to best capture the types of epigraphical data which are key for investigating the social dynamics of a Roman community through their inscribed monuments, and it is hoped that future researchers can adapt this database structure onto other Roman epigraphic datasets.

Support

This research was supported by the Croatian Studies Foundation (CSF) 2020 Community, Culture and Research Scheme, and the Macquarie University Research Excellence Scholarship Scheme (MQRES).

Related Publications

Coopey, E. (2020), ‘Fratres Romani in Dalmatia: The Social Dynamics of Legio VII and the Construction of Community and Identity through Roman Funerary Monuments’, MRes Thesis, Macquarie University. Accessible via: http://hdl.handle.net/1959.14/1280183

Current Disposition of the Physical Collection

The monuments are either 1) lost, 2) in states of secondary use in modern structures, or 3) are held in museums across Croatia and Bosnia Hercegovina:

• Arheološka zbirka Franjevačkog samostana u Sinju/Archaeological collection of the Franciscan Monastery in Sinj
• Arheološka zbirka Marka Matijevića u Solinu/The Archaeological collection of Marko Matijević in Solin
• Arheološki muzej u Splitu/Archaeological Museum in Split
• Arheološki muzej u Zadru/Archaeological Museum in Zadar
• Basilica of Santa Maria, Porto
• Muzej Cetinske krajina/Museum of Cetina region
• Muzej Triljskog kraja/Trilj Regional Museum
• Muzej grada Trogira/Trogir City Museum
• Muzej u Humcu (Franjevački samostan u Humcu)/Museum of Humac (Franciscan monastery of Humac)
• Zemaljski muzej Bosne i Hercegovine/The National Museum of Bosnia and Herzegovina

License

CC-BY-SA 4.0 International

Map of files

(descriptions in parentheses where required)

/BromansCoopey/

• analysis/ (example analysis csvs)
• data/ (data for this database in csvs)
• DB-SQL/ (files related to the database such as bibliogrpahies, the database, building/exporting shell commands)
• original_source_data/ (original data csvs)
• thesis/ (thesis which database is related to)
• publication_files/ (various files related to publication of this database to OCD https://opencontext.org/)

Methodological Notes

This database began with organising the epigraphic data catalogued in Tončinić, D. (2011) Spomenici VII. legije na području rimske provincije Dalmacije / Monuments of Legio VII in the Roman Province of Dalmatia. The data concerning the monuments catalogued within this work was then corroborated with that which available online on the EDCS (http://db.edcs.eu/epigr/epi.php?s_sprache=en) and EDH (https://edh-www.adw.uni-heidelberg.de/). Geographical data was then sourced from Trismegistos (https://www.trismegistos.org/geo/), Pleiades (https://pleiades.stoa.org/) and Google Maps (https://www.google.com/maps), with archaeological and analytical data sourced from various pieces of scholarly literature (for bibliography see RIS/BIB in DB-SQL/). The aforementioned databases were also used to find comparanda as well as source data concerning relevant monuments which were not recorded in Tončinić (2011). When using online databases, the primary means of navigation was through their linked open data, however their search functions were also used with varying success.

The database has been roughly normalised to third normal form, even though it is intended as an analytical database rather than a transactional database. Data was hand-entered through automatic shell-scripted conversion of CSV datafiles with no intentions of supporting a front-end application. As such, no lookup tables were constructed. Views were created to strongly differentiate analytical outputs from the data sources they drew upon. Better constrained vocabulary enforcement, more thorough annotations with linked open data, and a more robust geospatial layer are all intended improvements for future iterations of this database as time and technology permits. Version control was used from the start, and this paper describes the version at release 1.0.0.

Data was not always taken from online sources ‘as is’ and was assessed for accuracy where appropriate. For instance, personal judgements were made about the dating provided for certain monuments on online, as were certain pieces of geographic data. Sometimes, the author would contact the authors/organisers of the online resource with suggested changes.

File metadata

• Table Field Descriptions: Provided in data/README.md and analysis/README.md.
• Provide “Keys”: Provided in data/README.md and analysis/README.md.
• Controlled Vocabularies (“Standards”): Provided in data/README.md and analysis/README.md.

Current Release v.1.0.4 deployed the GitHub Repo onto Zenodo. Zenodo will now provide this release, and any others from here on in, a DOI. See https://help.zenodo.org/#github

analyze the current population survey (cps) annual social and economic supplement (asec) with r the annual march cps-asec has been supplying the statistics for the census bureau's report on income, poverty, and health insurance coverage since 1948. wow. the us census bureau and the bureau of labor statistics ( bls) tag-team on this one. until the american community survey (acs) hit the scene in the early aughts (2000s), the current population survey had the largest sample size of all the annual general demographic data sets outside of the decennial census - about two hundred thousand respondents. this provides enough sample to conduct state- and a few large metro area-level analyses. your sample size will vanish if you start investigating subgroups b y state - consider pooling multiple years. county-level is a no-no. despite the american community survey's larger size, the cps-asec contains many more variables related to employment, sources of income, and insurance - and can be trended back to harry truman's presidency. aside from questions specifically asked about an annual experience (like income), many of the questions in this march data set should be t reated as point-in-time statistics. cps-asec generalizes to the united states non-institutional, non-active duty military population. the national bureau of economic research (nber) provides sas, spss, and stata importation scripts to create a rectangular file (rectangular data means only person-level records; household- and family-level information gets attached to each person). to import these files into r, the parse.SAScii function uses nber's sas code to determine how to import the fixed-width file, then RSQLite to put everything into a schnazzy database. you can try reading through the nber march 2012 sas importation code yourself, but it's a bit of a proc freak show. this new github repository contains three scripts: 2005-2012 asec - download all microdata.R down load the fixed-width file containing household, family, and person records import by separating this file into three tables, then merge 'em together at the person-level download the fixed-width file containing the person-level replicate weights merge the rectangular person-level file with the replicate weights, then store it in a sql database create a new variable - one - in the data table 2012 asec - analysis examples.R connect to the sql database created by the 'download all microdata' progr am create the complex sample survey object, using the replicate weights perform a boatload of analysis examples replicate census estimates - 2011.R connect to the sql database created by the 'download all microdata' program create the complex sample survey object, using the replicate weights match the sas output shown in the png file below 2011 asec replicate weight sas output.png statistic and standard error generated from the replicate-weighted example sas script contained in this census-provided person replicate weights usage instructions document. click here to view these three scripts for more detail about the current population survey - annual social and economic supplement (cps-asec), visit: the census bureau's current population survey page the bureau of labor statistics' current population survey page the current population survey's wikipedia article notes: interviews are conducted in march about experiences during the previous year. the file labeled 2012 includes information (income, work experience, health insurance) pertaining to 2011. when you use the current populat ion survey to talk about america, subract a year from the data file name. as of the 2010 file (the interview focusing on america during 2009), the cps-asec contains exciting new medical out-of-pocket spending variables most useful for supplemental (medical spending-adjusted) poverty research. confidential to sas, spss, stata, sudaan users: why are you still rubbing two sticks together after we've invented the butane lighter? time to transition to r. :D

Interned: Torrens Island, 1914-1915 In August 1914 war broke out across Europe. Within days ‘enemy subjects’ in Australia were required to register with the authorities. Most gave their ‘parole’ …Show full description##Interned: Torrens Island, 1914-1915 In August 1914 war broke out across Europe. Within days ‘enemy subjects’ in Australia were required to register with the authorities. Most gave their ‘parole’ and went on with their lives in the community, but internment started with sailors taken off enemy ships and enemy reservists, and went on to include enemy subjects suspected of ‘disloyal or unsatisfactory’ behaviour. Later, some naturalised British subjects and even natural-born British subjects were interned. In the course of the war over 6,000 enemy subjects were interned across Australia. This dataset contains information about individuals interned during the First World War from South Australia (Military District 4). Most of those interned between October 1914 and August 1915, some 400 men, were held on Torrens Island, in the Port River estuary, north-west of Adelaide. The data set also includes those from South Australia who were interned in New South Wales after Torrens Island internment camp closed in August 1915. The data was compiled by History SA staff from two archival series in the National Archives of Australia: A367 C18000 Part 1, War Internees and Deportees 1914-1919 and D2286, Nominal Roll of prisoners of war interned at Torrens Island concentration camp 1915. Data fields include: Name, Also recorded as (alternative name), Date interned, Interned (at), Nationality, Date of birth/age, Remarks, and Notes. The data has been produced by identifying individuals who appear in both series and combining information from both series into this data set, using the A367 data as the primary series. This involved interpreting the data, in particular, making an assessment of whether or not entries in the two series with similar names represent the same person. Further research may reveal some of these assessments to be inaccurate. The dataset was produced as part of research for an exhibition at the Migration Museum and the Wakefield Press publication Interned: Torrens Island, 1914-15. http://migration.historysa.com.au/events/2014/interned-torrens-island-1914-1915 http://www.wakefieldpress.com.au/product.php?productid=1201

Since 1996, the Center for Military History and Social Sciences of the Bundeswehr (ZMSBw) has conducted a representative survey of the German population on defense and security policy issues on behalf of the Federal Ministry of Defense. In 1996, this study was continued. For this purpose, N = 2568 persons were interviewed on various issues. The present survey focused in particular on Security and threat perception, attitudes toward security policy, foreign deployments of the Federal Armed Forces, tasks of the Federal Armed Forces, the role of conscription, and military cooperation in Europe. Perception of security and threats: personal feeling of security; personal significance of various aspects of security (e.g. job security, military security, social security, security of income, ecological security, etc.) Interest in politics in general, in foreign policy, in security and defence policy as well as interest in the Federal Armed Forces; security policy interest at the beginning of the 1980s; security policy strategy of ´deterrence´ as a guarantee for peace in Europe, necessary Realpolitik or a threat to humanity; advocacy or rejection of military force; change in personal attitude towards military force; Reasons for change of attitude; reasons for not changing attitudes; personal relationship to the peace movement in the early 1980s and today; opinion on pacifism; opinion on the extent of public debate on security policy issues and on the Federal Armed Forces; future development of the number of international conflicts after the end of the Cold War; likelihood of a military threat to Germany; feeling threatened by: environmental destruction, violence, hatred, crime, unemployment, world wars, right-wing extremism, financial problems, new technologies, diseases and population growth; threat to world peace from various countries and regions (Islamic states, Third World, Russia, Central/Eastern Europe, USA, Western Europe, Germany, Middle East, China); current that will prevail worldwide in the future (national or nationalist thinking vs. voluntary cooperation and interdependence); assessment of nationalist thinking; assessment of voluntary cooperation; suitability of various institutions and instruments to protect Germany against military risks (NATO membership, other/ new treaties with neighbouring countries, United Nations (UN), European Union (EU), Federal Armed Forces, European Army, general disarmament, Organisation for Security and Cooperation in Europe (OSCE)). 2. Security policy attitudes, foreign missions of the Federal Armed Forces: Germany´s role in the world: preference for a rather active vs. rather passive international policy of Germany; approved or rejected measures for Germany´s international action (e.g. aid with food and medicine, aid of a financial and economic nature, technical aid by civil organisations, peacekeeping mission of the Federal Armed Forces within the framework of a UN mission, etc.); opinion on the peace-keeping mission of the Federal Armed Forces in various countries and regions (Eastern Europe, Russia, the Middle East, South-East Asia, Africa, NATO states, Western Europe; opinion on the future role of a state´s military power; opinion on the future staffing level of the Federal Armed Forces; assessment of Germany´s defence expenditure; general attitude towards the Federal Armed Forces. 3. Evaluation of public institutions: Institutional trust (Federal Constitutional Court, other courts, police, Bundesrat, state government, Federal Armed Forces, Bundestag, television, press, churches, trade unions, federal government, education, political parties); reliance on the Federal Armed Forces. 4. Attitude towards compulsory military service: Military service or alternative civilian service more important for society; decision for or against various community services (care of the sick, care of the elderly, military service/defence, care of the disabled, environmental protection/remedy of environmental damage, care of children in need of help, service with the police, border guards or fire brigade); community service which the interviewee would be most likely to opt for social service most likely to be refused; general attitude towards military service; opinion on the right to conscientious objection; frequency of different reasons for conscientious objection (religious reasons, military service as time lost, political reasons, military service not compatible with conscience, civilian service as a more convenient way, economic reasons, civilian service with greater benefit to society); general compulsory military service retained vs. conversion into a voluntary army; future of the Federal Armed Forces (Federal Armed Forces should be abolished, citizen´s army based on the Swiss model, purely voluntary army, current mix of conscripts, professional and temporary soldiers should be retained, fewer professional and temporary soldiers more military exercises for former soldiers); preference for the future of the Federal Armed Forces. 5. Tasks of the Federal Armed Forces: Preferences with regard to the tasks of the Federal Armed Forces (tasks of international arms control, fight against international terrorism, fight against international drug trafficking, border security against illegal immigrants, tasks in the field of environmental protection, international disaster relief, humanitarian aid and rescue services, reconstruction and development aid, international military advice, Combat operations on behalf of and under the control of the UN or other international organisations, peacekeeping operations on behalf of and under the control of the UN or international organisations, protection of the constitutional order in Germany, participation in celebrations and ceremonies, education and character building, defence of Germany, defence of allies, aid for threatened friendly nations); evaluation of the deployment of German soldiers in various UN missions with regard to: care of the suffering population, promotion of the international community, integration of Germany, strengthening of German national interests, stabilisation of world peace, strengthening of the reputation of the Federal Armed Forces, enforcement of human rights, establishment of democracy in the country of deployment, protection of the population in the country of deployment; assessment of the armament and equipment of the Federal Armed Forces; assessment of leadership training in the Federal Armed Forces; assessment of ´soldiering´ as a profession; personal acquaintance with a Federal Armed Forces soldier; personal advice to a relative or friend when considering volunteering for the Federal Armed Forces; importance of co-determination in civilian enterprises; importance of co-determination for soldiers in peacetime; preferences for voluntary service by women in the Federal Armed Forces (women do not belong in the Federal Armed Forces, only in unarmed service, all uses should be open to women); opinion on the complete withdrawal of US troops from Germany; opinion on the complete withdrawal of the Federal Armed Forces from the region; agreement on various possibilities for a new German security policy (extension of NATO security guarantees to Eastern Europe, common European foreign and security policy, restructuring of the military, return to national German interests, strengthening of political cooperation); the importance for Germany of a permanent seat on the UN Security Council; attitudes towards citizens of various neighbouring countries (Belgians, Danes, French, Dutch, Austrians, Poles, Swiss, Czechs and Luxemburgers); the most positive attitudes and the most negative attitudes towards neighbours; a feeling of belonging as West Germans, East Germans, Germans, Europeans or world citizens. 6. Military cooperation in Europe: familiarity of various associations with soldiers from different nations (e.g. German-French Brigade, Eurocorps, German-American Corps, German-Dutch Corps); opinion on military cooperation with various countries (USA, France, Netherlands, England, Belgium, Denmark, Italy); opinion on the creation of a European army; opinion on the political unification of Europe; opinion on the introduction of a common European currency, the Euro; evaluation of the performance of the Federal Armed Forces with regard to reunification in comparison to other institutions (trade unions, churches, political parties, employers´ associations, sports associations and media); opinion on the future NATO deployment of Federal Armed Forces combat troops. Demography: Sex; age (year of birth); education; additional vocational training; occupation; occupational group; net household income; marital status; denomination; residential environment (degree of urbanisation); city size; federal state; household size; number of persons in household aged 16 and over; Left-Right Self-Placement. Additionally coded: Respondent ID; age (categorised); West/East; weight.

Here are a few use cases for this project:

1. Military Strategic Planning: The "Infraded" model can be used by military strategists or defense agencies for identifying and pinpointing enemy equipment in a region. It could help them understand the type and quantity of military arsenal their enemies possess, enabling them to structure their strategies better.

2. Security and Surveillance: With the use of surveillance drones, the model can be used in real-time to detect and monitor movement of military equipment. This can help to anticipate potential threats and prepare for possible counter-strikes.

3. Research and Development: Defense organizations or think-tanks could use this model to analyze trends in military equipment usage around the globe. This can allow them to observe technology advancements in military equipment and enhance their own research and development efforts.

4. National Defense Administration: The model can be utilized to keep an inventory of a nation's military equipment, ensuring accurate records and enabling effective management of resources.

5. AI Warfare Simulation: The "Infraded" model can be used in creating realistic AI-based war game simulations for training military personnel. By recognizing the various military equipment classes, it can put them into a virtual war scenario, providing a more practical and immersive training experience.

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).

These data were automated to provide an accurate high-resolution historical shoreline of Bay Area of CA, San Francisco Peninsula (Military), CA suitable as a geographic information system (GIS) data layer. These data are derived from shoreline maps that were produced by the NOAA National Ocean Service including its predecessor agencies which were based on an office interpretation of imagery and/or field survey. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://www.fisheries.noaa.gov/inport/item/39808

Here are a few use cases for this project:

1. Military Surveillance: The "camou detection" model can be utilized in military surveillance systems for increased war zone safety. It can automatically detect potential threats such as M1_abram_tank or soldiers from the surveillance data to alert the authorities.

2. Battlefield Analysis: The computer vision model can be used to analyze battlefield scenarios in real-time or from recorded footages. It can assist in assessing the military strength of enemy forces, based on the number and type of military equipment.

3. Unmanned Aerial Vehicles (UAVs): The model can be integrated into UAVs to identify and classify different targets during reconnaissance missions. It can contribute to more detailed and effective intelligence reports.

4. Peacekeeping Missions: UN peacekeeping forces can use this model to distinguish between soldiers, civilians, and vehicles. This can help in minimizing civilian casualties during conflict and create better situational awareness for the forces on the ground.

5. Video Game Development: In realistic military simulation games, the model can be used to create an intricate detection system for various entity classes that would enhance the gaming experience by introducing more realistic scenarios and environments.

KAV 10224 cover memo. Visit https://dataone.org/datasets/sha256%3A97ad163f992af56957261f298ff57dd15167c75f237dd0799b24582d36c314f9 for complete metadata about this dataset.

This updated version of a global dataset covers the time period 1800-2019, with yearly observations for all countries that have been independent at any point in time since WWII. Within the category of democracies, we first make a distinction between republics and monarchies. Republics are then classified into presidential, semi-presidential, and parliamentary systems. Within the category of monarchies, most systems are parliamentary but a few countries are conferred to the category semi-monarchies. Autocratic countries are classified into the following main categories: absolute monarchy, military rule, party-based rule, personalist rule, and oligarchy. Within the categories party-based rule and oligarchy a number of subcategories are also identified.

Abstract copyright UK Data Service and data collection copyright owner. The aim of this database is to provide an insight into the sociology of the guerrilla movement that fought Napoleon Bonaparte in Spain between 1808 and 1814. Although a phenomenon that is both well known and accorded considerable importance in the history of the period, the participants in this struggle have never been the subject of detailed study. Many assumptions have been made about them – that the clergy figured disproportionately among their leadership, that many of the rank and file were deserters, etc. – but it has been impossible to test out these ideas. By amassing details of c.3,000 of the individuals involved in the struggle, this data base remedies this deficiency, and at the same time allows important conclusions to be drawn about the nature and extent of popular resistance to the French in Napoleonic Spain. Main Topics: This database contains personal details relating to c.3,000 participants in the guerrilla war which assailed the French in Spain in the period 1808-14. In elaborating the project, the ideal was to build up a complete picture of each individual – age in 1808; place of birth; place of residence; occupation; social class; previous military service; military experience 1808-14; history post-1814, etc. The data from which the database was put together being extremely fragmentary, it has not proved possible to find all the information that would have been desirable, but sufficient material exists in most categories for the data base to be interrogated on a selective basis.

KAV 8559 cover memo. Visit https://dataone.org/datasets/sha256%3A4c2ab42a717dd5ab3df55308d38ee8185145d02205b29023b185f4cc1a6c9533 for complete metadata about this dataset.

Interned: Torrens Island, 1914-1915 In August 1914 war broke out across Europe. Within days ‘enemy subjects’ in Australia were required to register with the authorities. Most gave their ‘parole’ and went on with their lives in the community, but internment started with sailors taken off enemy ships and enemy reservists, and went on to include enemy subjects suspected of ‘disloyal or unsatisfactory’ behaviour. Later, some naturalised British subjects and even natural-born British subjects were interned. In the course of the war over 6,000 enemy subjects were interned across Australia. This dataset contains information about individuals interned during the First World War from South Australia (Military District 4). Most of those interned between October 1914 and August 1915, some 400 men, were held on Torrens Island, in the Port River estuary, north-west of Adelaide. The data set also includes those from South Australia who were interned in New South Wales after Torrens Island internment camp closed in August 1915. The data was compiled by History SA staff from two archival series in the National Archives of Australia: A367 C18000 Part 1, War Internees and Deportees 1914-1919 and D2286, Nominal Roll of prisoners of war interned at Torrens Island concentration camp 1915. Data fields include: Name, Also recorded as (alternative name), Date interned, Interned (at), Nationality, Date of birth/age, Remarks, and Notes. The data has been produced by identifying individuals who appear in both series and combining information from both series into this data set, using the A367 data as the primary series. This involved interpreting the data, in particular, making an assessment of whether or not entries in the two series with similar names represent the same person. Further research may reveal some of these assessments to be inaccurate. The dataset was produced as part of research for an exhibition at the Migration Museum and the Wakefield Press publication Interned: Torrens Island, 1914-15. http://migration.historysa.com.au/events/2014/interned-torrens-island-1914-1915 http://www.wakefieldpress.com.au/product.php?productid=1201