Data associated with the paper: Who Tweets with Their Location? Understanding the Relationship Between Demographic Characteristics and the Use of Geoservices and Geotagging on Twitter Luke Sloan & Jeffrey Morgan

The dataset is a part of the survey conducted in Ho Chi Minh City and Dong Nai the Southeast region of Vietnam in 2020 to collect information for research on fertility. The main research purpose is to identify the socioeconomic determinants of low fertility in the Southeast. In total 808 individuals in the main reproductive age were interviewed, including 382 cases from Dong Nai and 426 cases from Ho Chi Minh City, or 273 unmarried persons and 535 married women. Information about family size desires and socio-demographic characteristics of 535 married men were asked when interviewing their spouses. As such, the survey collected information on the family size desires of 1343 individuals. The dataset has been converted to SPSS format (version 26.0). For data analysis, the dataset need to be weighted (WEI variable) as individuals were not selected with equal probability.

Demographic analysis examines and measures the dimensions and dynamics of populations; it can cover whole societies or groups defined by criteria such as education, nationality, religion, and ethnicity. Educational institutions usually treat demography as a field of sociology, though there are a number of independent demography departments. These methods have primarily been developed to study human populations, but are extended to a variety of areas where researchers want to know how populations of social actors can change across time through processes of birth, death, and migration. In the context of human biological populations, demographic analysis uses administrative records to develop an independent estimate of the population

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."

Grandmothers provide key care to their grandchildren in both contemporary and historic human populations. The length of the grandmother-grandchild relationship provides a basis for such interactions, but its variation and determinants have rarely been studied in different contexts, despite changes in age-specific mortality and fertility rates likely having affected grandmotherhood patterns across the demographic transition. Understanding how often and long grandmothers have been available for their grandchildren in different conditions may help explain the large differences between grandmaternal effects found in different societies, and is vital for developing theories concerning the evolution of menopause, post-reproductive longevity, and family living. Using an extensive genealogical dataset from Finland spanning the demographic transition, we quantify the length of grandmotherhood and its determinants from 1790–1959. We found that shared time between grandmothers and grandchildren was consistently low before the demographic transition, only increasing greatly during the 20th century. Whilst reduced childhood mortality and increasing adult longevity had a role in this change, grandmaternal age at birth remained consistent across the study period. Our findings further understanding of the temporal context of grandmother-grandchild relationships, and emphasise the need to consider the demography of grandmotherhood in a number of disciplines, including biology (e.g. evolution of the family), sociology (e.g. changing family structures), population health (e.g. changing age structures), and economics (e.g. workforce retention).

The CFPS baseline survey in 2010 consists of five basic datasets: community, family roster, family, adults, and children. In 2012, the CFPS carried out the first full-scale follow up survey, which targeted all 14,960 families, and 57,155 members from the 2010 family roster, who were considered CFPS gene members. In addition, individuals newly born to the 57,155 gene members would also be considered the CFPS gene members, while individuals newly married to the existing CFPS gene members would be considered the CFPS core members. By design, gene members are followed regardless of their relationships with their original families, whereas core members are followed as long as they maintain their family relations with gene members. The 2012 questionnaires share similar structures to those in 2010, although some specific contents have been modified. For example, no community dataset is available in the 2012 wave since the community survey is scheduled to be carried out in every other wave. A cross-wave individual-level dataset file has been added, listing all the individuals who ever participated in the CFPS, as well as their vital records, survey participation status, respondent type, and family ID in each wave.

The construction of the Swedish CDB and the data collection followed a template developed within the GGP. The template provided detailed guidelines for the collection, preparation, and documentation of the indicators. The database covers 16 main areas: Demography, Economy and Social Aspects, Labour and Employment, Parental Leave, Pension, Childcare, Military, Unemployment, Tax Benefits, Housing, Legal Aspects, Education, Health, Elderly Care, Politics, Culture. Each of these main domains contains more detailed indicators at the national or subregional (Riskområde NUTS2) level. In total, there are 243 indicators. Many of these indicators were calculated using Swedish Register Data. These indicators were not available in publicly accessible statistics and the Swedish CDB is thus currently the only database to provide them. The Swedish CDB offers a rich and unique set of time-series indicators at the national and subregional level.

If you use these data cite the following paper:

- Pappalardo et al., (2019) A public data set of spatio-temporal match events in soccer competitions, Nature Scientific Data 6:236, https://www.nature.com/articles/s41597-019-0247-7

This dataset describes all the soccer teams in seven prominent soccer competitions (Italian, Spanish, German, French and English first divisions, World Cup 2018, European Cup 2016). It consists of the following fields:
- city: the city where the team is located. For national teams it is the capital of the country;
- name: the common name of the team;
- area: information about the geographic area associated with the team;
- wyId: the identifier of the team, assigned by Wyscout;
- officialName: the official name of the team (e.g., Juventus FC);
- type: the type of the team. It is "club" for teams in the competitions for clubs and "national" for the teams in international competitions;

Genomic demography predicts community dynamics in a temperate Montane forest Dataset DOI: 10.5061/dryad.9w0vt4bsx ## Description of the data and file structure SNPs in VCF format for 8 species of trees from the Wind River Forest Dynamics plot in Southwestern Washington, USA. ### Files and variables #### File: WFDP_SNPS.zip Description: We have submitted the population SNPs.vcf (Variant Call Format) file from the de novo assembly performed using the STACK software. This file is the primary dataset utilized for the various analyses described in our article, "Genomic Demography Predicts Community Dynamics in a Temperate Montane Forest." The article investigates the application of genetic estimates of effective population size to predict population fluctuations given a community mean field model. Description of the data and file structure Dataset Overview This Variant Call Format (VCF) file contains Single Nucleotide Polymorphism (SNP) data from 8 species of trees with varying numbers of individuals. Species names and codes are depicted below, along with the number of individuals per species and the number of SNP loci per species. VCF files are named according to the species code. | Species | Code | N | Loci | | :---------------------- | :------- | :---- | :------- | | Thuja plicata | THPL | 93 | 55386 | | Tsuga heterophylla | TSHE | 92 | 8777 | | Cornus nuttalli | CONU | 90 | 6502 | | Acer circinatum | ACCI | 92 | 588 | | Pseudotsuga menziesii | PSME | 92 | 9373 | | Taxus brevifolia | TABR | 93 | 8892 | | Abies amabilis | ABAM | 94 | 24279 | | Abies grandifolia | ABGR | 48 | 7875 | populations.snps.vcf File Details * File Name: CODE.vcf * File Format: VCF (Variant Call Format) * Date: 5/28/2025 * Source Software: Stacks v2.41 Data Description The VCF file includes the following columns standard to the format: * #CHROM: Chromosome number * POS: Position of the SNP on the chromosome * ID: Identifier of the SNP * REF: Reference base * ALT: Alternate base(s) * QUAL: Quality score of the SNP * FILTER: Filter status * INFO: Additional information (e.g., allele frequency, number of samples) * FORMAT: Data format * Sample columns: One per individual, containing genotype information Specific Fields in INFO * NS: Number of samples with data * AF: Allele frequency * DP: Total depth of reads Specific Fields in FORMAT * GT: Genotype * AD: Allele depth * DP: Read depth * GQ: Genotype quality * GL: Genotype likelihood ## Code/software The VCF file can be opened and analyzed using various bioinformatics tools and software. Some of the most common include: * IGV (Integrative Genomics Viewer): Useful for visualizing genomic data. * BCFtools: Command-line tool for working with VCF/BCF files, including filtering, viewing, and converting. * GATK (Genome Analysis Toolkit): Provides tools to analyze high-throughput sequencing data with a focus on variant discovery. * vcftools: Command-line program designed to work specifically with VCF files to perform various types of analyses. Species population sizes fluctuate over time, and these temporal dynamics play a key role in maintaining biodiversity. While multiple modeling approaches have been developed to characterize fluctuations in forest tree species abundances, the data required to parametrize these models from scratch are substantial. Here we introduce a novel approach to modeling population fluctuations on decadal timescales by relating community-level dynamics to population-level patterns encoded in plant genomes. Using a single genomic snapshot to generate contemporary effective population size estimates in a temperate montane forest, we accurately predict fluctuations across three censuses. Our approach opens the door for the use of genomic demography to parametrize multispecies community models in ecology and shows that population genomic data can provide accurate predictions for ecological dynamics.

These transcripts were collected from:2 focus groups conducted in Pontefract, West Yorkshire1 focus group conducted in the Mumbles, Swansea, Wales

Dit deel betreft de bestanden van de provincie Limburg. De bestanden zijn ingedeeld per gemeente. De metadata per bestand (details) bevat het tabelnummer. Het bestand 'tabelnamen' geeft een overzicht van de tabelnummers met de bijbehorende tabelnamen. Dit bestand is beschikbaar gesteld als PDF document en als CSV tekstbestand.

Here is the code from my third column on the spatial demography journal. In this code, I use R to calculate commonly used measures of residential segregation.

This database includes professional/scientific societies for social scientists and humanists in the Arab region. For each professional/scientific society, it presents the thematic and geographic focus, membership type and categories, eligibility criteria for voting membership, main activities, ...

It is one in a series of databases compiled by the Arab Social Science Monitor as part of its mission to document and analyze the infrastructures of social sciences and humanities knowledge production and dissemination in the Arab region.

This database includes all higher education institutions (HEI) in the Arab region granting degrees at the Bachelor's, Master's and/or Doctoral level. For HEIs that offer social sciences and humanities degree programs, it presents the fields of study and highest degree offered, the faculties/schools/institute/center/college offering the degree program, year of establishment of the HEI, language(s) of instruction, ...

It is one in a series of databases compiled by the Arab Social Science Monitor as part of its mission to document and analyze the infrastructures of social sciences and humanities knowledge production and dissemination in the Arab region.

This database includes publishers in the social sciences and humanities in the Arab region. For each publisher, it presents the fields it publishes in, the types and formats of publications, language(s) of publications, ...

It is one in a series of databases compiled by the Arab Social Science Monitor as part of its mission to document and analyze the infrastructures of social sciences and humanities knowledge production and dissemination in the Arab region.

Courses of occupation, job situation and occupation opportunities of social scientists in public administration. Topics: Point in time and reasons for entering public administration; subjects of studies and conclusion of course of study; earned supplemental qualifications; type of preparation for entry or arranging of position; occupation career; content and formal task assigned; changes of main focus areas of occupation in the last few years; requirements for current activity; subject area of predecessor in current position and of immediate superior; judgement on room for action and disposition; type of work supervision and comparison with supervision among other academics; atmosphere at work and teamwork; type of decision-making processes; used sources of information and adequate provision with information to carry out the job; particular problems of social scientists in obtaining information; occupational mobility and interest in a change of position; scientific publication and participation in scientific congresses since taking position; judgement on the study of social science and recommendations for change; assessment of the opportunities actively to direct political processes in the government office; intervention by politicians and special interest groups in the government office; status as employee and salary group; interest in transfer into the civil service; earlier participation in student self-administration committees and political college groups; employment of father in public administration; approval for the study of sociology by one´s own children. Demography: Membership in a party or in associations and functions taken on there; social origins; age; sex; vocational training; professional position; income; state. Berufsverläufe, Arbeitssituation und Berufsmöglichkeiten von Sozialwissenschaftlern in der öffentlichen Verwaltung. Themen: Zeitpunkt und Gründe für den Eintritt in die öffentliche Verwaltung; Studienfächer und Studienabschluß; erworbene Zusatzqualifikationen; Art der Eintrittsvorbereitung bzw. Stellenvermittlung; Berufslaufbahn; inhaltliche und formal zugewiesene Aufgaben; Veränderungen der Tätigkeitsschwerpunkte in den letzten Jahren; Anforderungsprofil für die jetzige Tätigkeit; Fachrichtung des Vorgängers auf der jetzigen Stelle und des unmittelbaren Vorgesetzten; Beurteilung des Handlungs- und Dispositionsspielraums; Art der Arbeitskontrolle und Vergleich mit der Kontrolle bei anderen Akademikern; Betriebsklima und Teamarbeit; Art der Entscheidungsprozesse; benutzte Informationsquellen und ausreichende Versorgung mit Informationen zur Erledigung der Arbeit; besondere Probleme der Sozialwissenschaftler bei der Informationsbeschaffung; berufliche Mobilität und Interesse an einem Stellenwechsel; wissenschaftliche Veröffentlichung und Teilnahme an wissenschaftlichen Kongressen seit Stellenantritt; Beurteilung des sozialwissenschaftlichen Studiums und Vorschläge für eine Veränderung des Studiums; Einschätzung der Möglichkeiten in der Behörde, politische Prozesse aktiv zu steuern; Eingriffe von Politikern und Interessengruppen in die Behörde; Angestelltenverhältnis und Besoldungsgruppe; Interesse an einer Übernahme ins Beamtenverhältnis; frühere Mitarbeit in studentischen Selbstverwaltungsgremien und politischen Hochschulgruppen; Beschäftigung des Vaters in der öffentlichen Verwaltung; Befürwortung eines Soziologiestudiums für die eigenen Kinder. Demographie: Mitgliedschaft in einer Partei oder in Verbänden und dabei übernommene Funktionen; soziale Herkunft; Alter; Geschlecht; Berufsausbildung; berufliche Position; Einkommen; Bundesland.

In 2010, cancer deaths accounted for more than 15% of all deaths worldwide, and this fraction is estimated to rise in the coming years. Increased cancer mortality has been observed in immigrant populations, but a comprehensive analysis by country of birth has not been conducted. We followed all individuals living in Sweden between 1961 and 2009 (7,109,327 men and 6,958,714 women), and calculated crude cancer mortality rates and age-standardized rates (ASRs) using the world population for standardization. We observed a downward trend in all-site ASRs over the past two decades in men regardless of country of birth but no such trend was found in women. All-site cancer mortality increased with decreasing levels of education regardless of sex and country of birth (p for trend

Percent distribution of currently married women and men by their socio demographic characteristics, Jimma zone, Ethiopia 2013.*Protestant and traditional religions.§Data only from wives.**Majority were housewives.

Mortality rate ratios (MRRs) are adjusted for calendar period of follow-up and level of education. The reference group is Sweden-born individuals. MRR values significantly different from 1.0 are highlighted in bold.*Categories with at least five cases of cancer mortality.

Countries weighted by number of births.aEstimates for the 1970s exclude the following countries that are included for subsequent decades: Albania, Armenia, Azerbaijan, Belarus, Croatia, Czech Republic, Estonia, Georgia, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Mongolia, Qatar, Republic of Moldova, Serbia, Sierra Leone, Slovakia, Slovenia, Somalia, Tajikistan, the former Yugoslav Republic of Macedonia, Timor-Leste, and Turkmenistan.