The World Religion Project (WRP) aims to provide detailed information about religious adherence worldwide since 1945. It contains data about the number of adherents by religion in each of the states in the international system. These numbers are given for every half-decade period (1945, 1950, etc., through 2010). Percentages of the states' populations that practice a given religion are also provided. (Note: These percentages are expressed as decimals, ranging from 0 to 1, where 0 indicates that 0 percent of the population practices a given religion and 1 indicates that 100 percent of the population practices that religion.) Some of the religions (as detailed below) are divided into religious families. To the extent data are available, the breakdown of adherents within a given religion into religious families is also provided.

The project was developed in three stages. The first stage consisted of the formation of a religion tree. A religion tree is a systematic classification of major religions and of religious families within those major religions. To develop the religion tree we prepared a comprehensive literature review, the aim of which was (i) to define a religion, (ii) to find tangible indicators of a given religion of religious families within a major religion, and (iii) to identify existing efforts at classifying world religions. (Please see the original survey instrument to view the structure of the religion tree.) The second stage consisted of the identification of major data sources of religious adherence and the collection of data from these sources according to the religion tree classification. This created a dataset that included multiple records for some states for a given point in time. It also contained multiple missing data for specific states, specific time periods and specific religions. The third stage consisted of cleaning the data, reconciling discrepancies of information from different sources and imputing data for the missing cases.

The Global Religion Dataset: This dataset uses a religion-by-five-year unit. It aggregates the number of adherents of a given religion and religious group globally by five-year periods.

World Religions Across Regions

Analyzing Adherence Across Regions, States and the Global System

By Correlates of War Project [source]

About this dataset

The World Religion Project (WRP) is an ambitious endeavor to conduct a comprehensive analysis of religious adherence throughout the world from 1945 to 2010. This cutting-edge project offers unparalleled insight into the religious behavior of people in different countries, regions, and continents during this time period. Its datasets provide important information about the numbers and percentages of adherents across a multitude of different religions, religion families, and non-religious affiliations.

The WRP consists of three distinct datasets: the national religion dataset, regional religion dataset, and global religion dataset. Each is focused on understanding individually specific realms for varied analysis approaches - from individual states to global systems. The national dataset provides data on number of adherents by state as well as percentage population practicing a given faith group in five-year increments; focusing attention to how this number evolves from nation to nation over time. Similarly, regional data is provided at five year intervals highlighting individual region designations with one modification – Pacific Ocean states have been reclassified into their own Oceania category according to Country Code Number 900 or above). Finally at a global level – all states are aggregated in order that we may understand a snapshot view at any five-year interval between 1945‐2010 regarding relationships between religions or religio‐families within one location or transnationally.

This project was developed in three stages: firstly forming a religions tree (a systematic classification), secondly collecting data such as this provided by WRP according to that classification structure – lastly cleaning the data so discrepancies may be reconciled and imported where needed with gaps selected when unknown values were encountered during collection process . We would encourage anyone wishing details undergoing more detailed reading/analysis relating various use applications for these rich datasets - please contact Zeev Maoz (University California Davis) & Errol A Henderson _(Pennsylvania State University)

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How to use the dataset

The World Religions Project (WRP) dataset offers a comprehensive look at religious adherence around the world within a single dataset. With this dataset, you can track global religious trends over a period of 65 years and explore how they’ve changed during that time. By exploring the WRP data set, you’ll gain insight into cross-regional and cross-time patterns in religious affiliation around the world.

Research Ideas

• Analyzing historical patterns of religious growth and decline across different regions
• Creating visualizations to compare religious adherence in various states, countries, or globally
• Studying the impact of governmental policies on religious participation over time

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: WRP regional data.csv | Column name | Description | |:-----------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------| | Year | Reference year for data collection. (Integer) | | Region | World region according to Correlates Of War (COW) Regional Systemizations with one modification (Oceania category for COW country code ...

This dataset describes the world’s religious makeup in 2020 and 2010. We focus on seven categories: Christians, Muslims, Hindus, Buddhists, Jews, people who belong to other religions, and those who are religiously unaffiliated. This analysis is based on more than 2,700 sources of data, including national censuses, large-scale demographic surveys, general population surveys and population registers. For more information about this data, see the associated Pew Research Center report "How the Global Religious Landscape Changed From 2010 to 2020."

Initial data source was UNESCO web site, supplemented by individual work on different countires/regions;A database of cultural heritage sites assembled by volunteers at the Archaeological Computing Laboratory, University of Sydney

This folder consists of files for a case study of the methods used by Pew Research Center to make direct and indirect estimates for our report on The Religious Composition of the World's Migrants. Two subfolders demonstrate the procedures of the algorithm using two statistical programs, which mirror one another.

This dataset includes demographic, behavioral, and religiosity data from eight different populations from around the world. The samples were drawn from: (1) Coastal and (2) Inland Tanna, Vanuatu; (3) Hadzaland, Tanzania; (4) Lovu, Fiji; (5) Pointe aux Piment, Mauritius; (6) Pesqueiro, Brazil; (7) Kyzyl, Tyva Republic; and (8) Yasawa, Fiji. The materials documents includes: a) a codebook for variable definitions, b) images of experimental conditions, and c) data set updates and corrigenda. Also included is a script for R that highlights analyses from Purzycki, et al. (2016). Moralistic Gods, Supernatural Punishment and the Expansion of Human Sociality. Nature, 530(7590): 327-330.

This repository contains historical data collected in the digital humanities project Dhimmis & Muslims – Analysing Multireligious Spaces in the Medieval Muslim World. The project was funded by the VolkswagenFoundation within the scope of the Mixed Methods initiative. The project was a collaboration between the Institute for Medieval History II of the Goethe University in Frankfurt/Main, Germany, and the Institute for Visualization and Interactive Systems at the University of Stuttgart, and took place there from 2018 to 2021. The objective of this joint project was to develop a novel visualization approach in order to gain new insights on the multi-religious landscapes of the Middle East under Muslim rule during the Middle Ages (7th to 14th century). In particular, information on multi-religious communities were researched and made available in a database accessible through interactive visualization as well as through a pilot web-based geo-temporal multi-view system to analyze and compare information from multiple sources. The code for this visualization system is publicly available on GitHub under the MIT license. The data in this repository is a curated database dump containing data collected from a predetermined set of primary historical sources and literature. The core objective of the data entry was to record historical evidence for religious groups in cities of the Medieval Middle East. In the project, data was collected in a relational PostgreSQL database, the structure of which can be reconstructed from the file schema.sql. An entire database dump including both the database schema and the table contents is located in database.sql. The PDF file database-structure.pdf describes the relationship between tables in a graphical schematic. In the database.json file, the contents of the individual tables are stored in JSON format. At the top level, the JSON file is an object. Each table is stored as a key-value pair, where the key is the database name, and the value is an array of table records. Each table record is itself an object of key-value pairs, where the keys are the table columns, and the values are the corresponding values in the record. The dataset is centered around the evidence, which represents one piece of historical evidence as extracted from one or more sources. An evidence must contain a reference to a place and a religion, and may reference a person and one or more time spans. Instances are used to connect evidences to places, persons, and religions; and additional metadata are stored individually in the instances. Time instances are connected to the evidence via a time group to allow for more than one time span per evidence. An evidence is connected via one or more source instances to one or more sources. Evidences can also be tagged with one or more tags via the tag_evidence table. Places and persons have a type, which are defined in the place type and person type tables. Alternative names for places are stored in the name_var table with a reference to the respective language. For places and persons, references to URIs in other data collections (such as Syriaca.org or the Digital Atlas of the Roman Empire) are also stored, in the external_place_uri and external_person_uri tables. Rules for how to construct the URIs from the fragments stored in the last-mentioned tables are controlled via the uri_namespace and external_database tables. Part of the project was to extract historical evidence from digitized texts, via annotations. Annotations are placed in a document, which is a digital version of a source. An annotation can be one of the four instance types, thereby referencing a place, person, religion, or time group. A reference to the annotation is stored in the instance, and evidences are constructed from annotations by connecting the respective instances in an evidence tuple.

Census: Population: by Religion: Christian: Lakshadweep: Male data was reported at 286.000 Person in 03-01-2011. This records a decrease from the previous number of 422.000 Person for 03-01-2001. Census: Population: by Religion: Christian: Lakshadweep: Male data is updated decadal, averaging 354.000 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 422.000 Person in 03-01-2001 and a record low of 286.000 Person in 03-01-2011. Census: Population: by Religion: Christian: Lakshadweep: Male data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAE004: Census: Population: by Religion: Christian.

The European Values Study (EVS) and the World Values Survey (WVS) are two large-scale, cross-national and longitudinal survey research programmes. They include a large number of questions on moral, religious, social, political, occupational and family values which have been replicated since the early eighties.

Both organizations agreed to cooperate in joint data collection from 2017. EVS has been responsible for planning and conducting surveys in European countries, using the EVS questionnaire and EVS methodological guidelines. WVSA has been responsible for planning and conducting surveys in countries in the world outside Europe, using the WVS questionnaire and WVS methodological guidelines. Both organisations developed their draft master questionnaires independently. The joint items define the Common Core of both questionnaires.

The Joint EVS/WVS is constructed from the two EVS and WVS source datasets: - European Values Study 2017 Integrated Dataset (EVS 2017), ZA7500 Data file Version 5.0.0, doi:10.4232/1.13897 (https://doi.org/10.4232/1.13897). Haerpfer, C., Inglehart, R., Moreno,A., Welzel,C., Kizilova,K., Diez-Medrano J., M. Lagos, P. Norris, E. Ponarin & B. Puranen et al. (eds.). 2024. World Values Survey: Round Seven–Country-Pooled Datafile. Madrid, Spain & Vienna, Austria: JD Systems Institute & WVSA Secretariat. Version. 6.0.0, doi:10.14281/18241.24.
1. Perceptions of life: importance of family, friends, leisure time, politics, work, and religion; feeling of happiness; self-assessment of state of health; satisfaction with life; internal or external control; importance of educational goals: desirable qualities of children; membership in voluntary organisations (religious organisations, cultural activities, trade unions, political parties or groups, conservation, environment, ecology, animal rights, professional associations, sports, recreation, consumer groups, or other groups); membership in humanitarian or charitable organisation, self-help group or mutual aid; tolerance towards minorities (people of a different race, heavy drinkers, immigrants/ foreign workers, drug addicts, homosexuals - social distance); trust in people; protecting the environment vs. economic growth.

1. Work: attitude towards work (people who don’t work turn lazy, work is a duty towards society, work always comes first); job scarce: men should have more right to a job than women (3-point scale and 5-point scale), employers should give priority to (nation) people than immigrants (3-point scale and 5-point scale).

2. Religion and morale: religious denomination; current frequency of religious services attendance; frequency of prayer (WVS7); pray to God outside of religious services (EVS5); self-assessment of religiousness; belief in God, life after death, hell, and heaven; importance of God in one´s life; morale attitudes (scale: claiming government benefits without entitlement, avoiding a fare on public transport, cheating on taxes, accepting a bribe, homosexuality, prostitution, abortion, divorce, euthanasia, suicide, having casual sex, political violence, death penalty).

3. Family: attitude towards traditional understanding of one´s role of man and woman in occupation and family (gender roles); homosexual couples are as good parents as other couples; duty towards society to have children; it is child´s duty to take care of ill parent; one of main goals in life has been to make own parents proud.

4. Politics and society: most important aims of the country for the next ten years (first choice, second choice), aims of the respondent (first choice, second choice)); post-materialist index 4-item; willingness to fight for the country; expectation of future development (less importance placed on work and greater respect for authority); political interest; political participation (political action: signing a petition, joining in boycotts, attending lawful/ peaceful demonstrations, joining unofficial strikes); self positioning in political scale; equal incomes vs. incentives for individual effort; private vs. state ownership of business and industry; individual vs. government responsibility for providing; competition good vs. harmful for people; confidence in institutions (churches, armed forces, the press, labour unions, the police, parliament, the civil services, major regional organisations (combined from country-specific), the European Union, the government, the political parties, major companies, the environmental protection movement, justice system/ courts, the United Nations); satisfaction with the political system in the country; preferred type of political system (strong leader, expert decisions, army should rule the country, or democracy); party the respondent would vote for: first choice (WVS); political party with the most appeal (ISO 3166-1) (EVS5); essential characteristics of democracy; importance of democracy for the respondent; rating democracy in own country; vote in elections on local level and on...

Pew Research Center conducted random, probability-based surveys among 13,122 adults (ages 18 and older) across six South and Southeast Asian countries: Cambodia, Indonesia, Malaysia, Singapore, Sri Lanka and Thailand. Interviewing was carried out under the direction of Langer Research Associates. In Malaysia and Singapore, interviews were conducted via computer-assisted telephone interviewing (CATI) using mobile phones. In Cambodia, Indonesia, Sri Lanka and Thailand, interviews were administered face-to-face using tablet devices, also known as computer-assisted personal interviewing (CAPI). All surveys were conducted between June 1 and Sept. 4, 2022.

This project was produced by Pew Research Center as part of the Pew-Templeton Global Religious Futures project, which analyzes religious change and its impact on societies around the world. Funding for the Global Religious Futures project comes from The Pew Charitable Trusts and the John Templeton Foundation (grant 61640). This publication does not necessarily reflect the views of the John Templeton Foundation.

As of July 2024, one report has been published that focuses on the findings from this data: Buddhism, Islam and Religious Pluralism in South and Southeast Asia: https://www.pewresearch.org/religion/2023/09/12/buddhism-islam-and-religious-pluralism-in-south-and-southeast-asia/

"Between October 2011 and November 2012, Pew Research Center, with generous funding from The Pew Charitable Trusts and the John Templeton Foundation, conducted a public opinion survey involving more than 30,000 face-to-face interviews in 26 countries in Africa, Asia, the Middle East and Europe. The survey asked people to describe their religious beliefs and practices, and sought to gauge respondents; knowledge of and attitudes toward other faiths. It aimed to assess levels of political and economic satisfaction, concerns about crime, corruption and extremism, positions on issues such as abortion and polygamy, and views of democracy, religious law and the place of women in society.

"Although the surveys were nationally representative in most countries, the primary goal of the survey was to gauge and compare beliefs and attitudes of Muslims. The findings for Muslim respondents are summarized in the Religion & Public Life Project's reports The World's Muslims: Unity and Diversity and The World's Muslims: Religion, Politics and Society, which are available at www.pewresearch.org. [...] This dataset only contains data for Muslim respondents in the countries surveyed. Please note that this codebook is meant as a guide to the dataset, and is not the survey questionnaire." (2012 Pew Religion Worlds Muslims Codebook)

Pew Research Center conducted random probability-based surveys among a total of 10,390 adults (ages 18 and older) in five places: Hong Kong, Japan, South Korea, Taiwan and Vietnam. Interviewing in Japan, South Korea and Taiwan was carried out under the direction of Langer Research Associates, and interviewing in Hong Kong and Vietnam was carried out under the direction of D3 Systems. In Hong Kong, Japan, South Korea and Taiwan, interviews were conducted via computer-assisted telephone interviewing (CATI). In Vietnam, interviews were administered face-to-face using tablet devices, also known as computer-assisted personal interviewing (CAPI). All surveys were conducted between June 2 and Sept. 17, 2023.

This project was produced by Pew Research Center as part of the Pew-Templeton Global Religious Futures project, which analyzes religious change and its impact on societies around the world. Funding for the Global Religious Futures project comes from The Pew Charitable Trusts and the John Templeton Foundation (grant 62287). This publication does not necessarily reflect the views of the John Templeton Foundation.

As of June 2024, one report has been published that focuses on the findings from this data: Religion and Spirituality in East Asian Societies: https://www.pewresearch.org/religion/2024/06/17/religion-and-spirituality-in-east-asian-societies

A cross-national data set of 21 variables was assembled for 212 countries from three sources (Barro and Lee 1994; Gordon 2005; CIA World Fact Book 2005). Our data set includes several proxy measures for national wealth, cultural diversity, social instability (both at national and international levels), and demography. Separate diversity measures were calculated for three different cultural domains, namely language, religion and ethnic groups . In addition, wealth variables (per capita GDP, and GINI, the coefficient of income inequality) were assembled, along with indicators of societal functioning drawn from the literature (especially Barro and Lee 1994), including indices of political rights (PRIGHTSB), revolutions and coups d'états (REVCOUP), and political instability (PINSTAB). Measures of international conflict were extracted from the social science literature, and the following were used: the proportion of the time between 1960-85 the country was involved in an external war (WARTIME), the number of international disputes in which the country was involved (TOTINTDISP), and an index of total military expenditure (TOTMILITEXP). Possible confounding variables such as population size (POPSIZE) and the number of international borders (NBINTBORDERS) were also included.

Census: Population: by Religion: Christian: Maharashtra: Male data was reported at 531,916.000 Person in 03-01-2011. This records an increase from the previous number of 530,975.000 Person for 03-01-2001. Census: Population: by Religion: Christian: Maharashtra: Male data is updated decadal, averaging 531,445.500 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 531,916.000 Person in 03-01-2011 and a record low of 530,975.000 Person in 03-01-2001. Census: Population: by Religion: Christian: Maharashtra: Male data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAE004: Census: Population: by Religion: Christian.

The increase in religiously motivated hate on social media is clear and ongoing. These platforms have become fertile ground for the dissemination of hate speech directed at religious communities, resulting in tangible repercussions in the real world. Much of the current research concerning the automated identification of hateful content on social media focuses on English-language content. There is comparatively less exploration in low-resource languages such as Hindi. As social media users increasingly utilize their regional languages for expression, it becomes crucial to dedicate appropriate research efforts to hate speech detection in these languages.

Hence, this work aims to fill this research void by introducing a meticulously curated and annotated dataset of YouTube comments in Hindi-English code-mixed language, specifically designed to identify instances of religious hate.

Citation: Sharma, D., Singh, A., & Singh, V. K. (2024). THAR-Targeted Hate Speech Against Religion: A high-quality Hindi-English code-mixed Dataset with the Application of Deep Learning Models for Automatic Detection. ACM Transactions on Asian and Low-Resource Language Information Processing. (https://doi.org/10.1145/3653017)

In December 2009, Pew Research Center released "Global Restrictions on Religion," the first in a series of annual reports on a data-coding project that seeks to measure levels of government restrictions on religion and social hostilities involving religion around the world. As of February 2015, Pew Research had published six reports on global restrictions on religion, analyzing a total of seven years' worth of data (the first two reports covered a total of three years, from 2007 to 2009). [...] In order to provide social science researchers and the general public with easier access to the data, Pew Research Center has released the full dataset.

The data are presented as a long-format dataset, in which each row is a country-year observation (for example, "Afghanistan, 2007"). The columns contain all of the variables presented in Pew Research Center's annual reports on restrictions on religion, as well as some additional variables analyzed in separate studies. The dataset contains data from 2007 through 2013; as additional years of data are coded, the dataset will be updated.

The codebook proceeds in three parts. First, it explains the methodology and coding procedures used to collect the data. Second it discusses the Government Restrictions Index and Social Hostilities Index, including what they measure and how they are calculated. Finally, it describes each of the variables included in the dataset, along with answer values and definitions of key terms.

This study assessed the effects of male inmate religiosity on post-release community adjustment and investigated the circumstances under which these effects were most likely to take place. The researcher carried out this study by adding Federal Bureau of Investigation criminal history information to an existing database (Clear et al.) that studied the relationship between an inmate's religiousness and his adjustment to the correctional setting. Four types of information were used in this study. The first three types were obtained by the original research team and included an inmate values and religiousness instrument, a pre-release questionnaire, and a three-month post-release follow-up phone survey. The fourth type of information, official criminal history reports, was later added to the original dataset by the principal investigator for this study. The prisoner values survey collected information on what the respondent would do if a friend sold drugs from the cell or if inmates of his race attacked others. Respondents were also asked if they thought God was revealed in the scriptures, if they shared their faith with others, and if they took active part in religious services. Information collected from the pre-release questionnaire included whether the respondent attended group therapy, religious groups with whom he would live, types of treatment programs he would participate in after prison, employment plans, how often he would go to church, whether he would be angry more in prison or in the free world, and whether he would be more afraid of being attacked in prison or in the free world. Each inmate also described his criminal history and indicated whether he thought he was able to do things as well as most others, whether he was satisfied with himself on the whole or felt that he was a failure, whether religion was talked about in the home, how often he attended religious services, whether he had friends who were religious while growing up, whether he had friends who were religious while in prison, and how often he participated in religious inmate counseling, religious services, in-prison religious seminars, and community service projects. The three-month post-release follow-up phone survey collected information on whether the respondent was involved with a church group, if the respondent was working for pay, if the respondent and his household received public assistance, if he attended religious services since his release, with whom the respondent was living, and types of treatment programs attended. Official post-release criminal records include information on the offenses the respondent was arrested and incarcerated for, prior arrests and incarcerations, rearrests, outcomes of offenses of rearrests, follow-up period to first rearrest, prison adjustment indicator, self-esteem indicator, time served, and measurements of the respondent's level of religious belief and personal identity. Demographic variables include respondent's faith, race, marital status, education, age at first arrest and incarceration, and age at incarceration for rearrest.

The Standard Cross-Cultural Sample of Religion is a product of the Database of Religious History (DRH). The DRH is a qualitative-quantitative encyclopedic database of historical religious data across time and space. Data are contributed to the project by academic experts and overseen by a panel of editors. The data take the form of answers (provided by experts) to a long list of standard questions grounded in time and space.

The Standard Cross-Cultural Sample of Religion is “standard” in a different way than its namesake, The Standard Cross-Cultural Sample (SCCS). The SCCS was designed to control for region and cultural relatedness. Because of our mostly bottom-up, expert-driven data gathering method, DRH data is heavily overweighted in certain time/space regions. Analysts will have to control for this as they see fit.

On the other hand, DRH data is “standard” in the sense that whatever Group, Place of Text is being portrayed, experts are answering a standardized set of questions, allowing a degree of comparison and quantitative analysis that has simply never been possible before. As the DRH grows, top-down data-gathering pushes will be targeted at underrepresented regions of the world, with the goal of making future versions of the SCCSR more and more comprehensive.

The Standard Cross-Cultural Sample of Religion (SCCSR.v2) is provided under CC-BY-4.0 license.

India Census: Population: by Religion: Muslim: Urban data was reported at 68,740,419.000 Person in 2011. This records an increase from the previous number of 49,393,496.000 Person for 2001. India Census: Population: by Religion: Muslim: Urban data is updated yearly, averaging 59,066,957.500 Person from Mar 2001 (Median) to 2011, with 2 observations. The data reached an all-time high of 68,740,419.000 Person in 2011 and a record low of 49,393,496.000 Person in 2001. India Census: Population: by Religion: Muslim: Urban data remains active status in CEIC and is reported by Census of India. The data is categorized under India Premium Database’s Demographic – Table IN.GAE001: Census: Population: by Religion.

A computerized data set of demographic, economic and social data for 227 countries of the world. Information presented includes population, health, nutrition, mortality, fertility, family planning and contraceptive use, literacy, housing, and economic activity data. Tabular data are broken down by such variables as age, sex, and urban/rural residence. Data are organized as a series of statistical tables identified by country and table number. Each record consists of the data values associated with a single row of a given table. There are 105 tables with data for 208 countries. The second file is a note file, containing text of notes associated with various tables. These notes provide information such as definitions of categories (i.e. urban/rural) and how various values were calculated. The IDB was created in the U.S. Census Bureau''s International Programs Center (IPC) to help IPC staff meet the needs of organizations that sponsor IPC research. The IDB provides quick access to specialized information, with emphasis on demographic measures, for individual countries or groups of countries. The IDB combines data from country sources (typically censuses and surveys) with IPC estimates and projections to provide information dating back as far as 1950 and as far ahead as 2050. Because the IDB is maintained as a research tool for IPC sponsor requirements, the amount of information available may vary by country. As funding and research activity permit, the IPC updates and expands the data base content. Types of data include: * Population by age and sex * Vital rates, infant mortality, and life tables * Fertility and child survivorship * Migration * Marital status * Family planning Data characteristics: * Temporal: Selected years, 1950present, projected demographic data to 2050. * Spatial: 227 countries and areas. * Resolution: National population, selected data by urban/rural * residence, selected data by age and sex. Sources of data include: * U.S. Census Bureau * International projects (e.g., the Demographic and Health Survey) * United Nations agencies Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/08490