The National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) is a national genetics data repository facilitating access to genotypic and phenotypic data for Alzheimer's disease (AD). Data include GWAS, whole genome (WGS) and whole exome (WES), expression, RNA Seq, and CHIP Seq analyses. Data for the Alzheimer’s Disease Sequencing Project (ADSP) are available through a partnership with dbGaP (ADSP at dbGaP). Results are integrated and annotated in the searchable genomics database that also provides access to a variety of software packages, analytic pipelines, online resources, and web-based tools to facilitate analysis and interpretation of large-scale genomic data. Data are available as defined by the NIA Genomics of Alzheimer’s Disease Sharing Policy and the NIH Genomics Data Sharing Policy. Investigators return secondary analysis data to the database in keeping with the NIAGADS Data Distribution Agreement.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household

UNITS IDENTIFIED: - Dwellings: No - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: Yes - Special populations: No

Universe

All persons present in Cameroon at the time of the census, including visitors from other countries.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Institute of Statistics

SAMPLE DESIGN: Systematic sample of every 10th dwelling with a random start, drawn by MPC

SAMPLE UNIT: Household

SAMPLE FRACTION: 10%

SAMPLE UNIVERSE: Systematic sample of every 10th dwelling with a random start, drawn by MPC

SAMPLE SIZE (person records): 736,514

Mode of data collection

Face-to-face [f2f]

Research instrument

Two forms: Dwelling units and collective households

Response rate

UNDERCOUNT: 7%

Industrial Production: Polypropylene data was reported at 316,773.000 Ton in 2023. This records an increase from the previous number of 298,640.000 Ton for 2022. Industrial Production: Polypropylene data is updated yearly, averaging 288,627.000 Ton from Dec 2015 (Median) to 2023, with 9 observations. The data reached an all-time high of 316,773.000 Ton in 2023 and a record low of 201,800.000 Ton in 2020. Industrial Production: Polypropylene data remains active status in CEIC and is reported by National Institute of Statistics and Censuses. The data is categorized under Global Database’s Argentina – Table AR.B016: Industrial Production: National Institute of Statistics and Censuses: Annual.

Industrial Production: Seeders data was reported at 1,680.000 Unit in 2023. This records a decrease from the previous number of 2,716.000 Unit for 2022. Industrial Production: Seeders data is updated yearly, averaging 2,636.000 Unit from Dec 2021 (Median) to 2023, with 3 observations. The data reached an all-time high of 2,716.000 Unit in 2022 and a record low of 1,680.000 Unit in 2023. Industrial Production: Seeders data remains active status in CEIC and is reported by National Institute of Statistics and Censuses. The data is categorized under Global Database’s Argentina – Table AR.B016: Industrial Production: National Institute of Statistics and Censuses: Annual.

Abstract

The 2021-22 Cambodia Demographic and Health Survey (2021-22 CDHS) was implemented by the National Institute of Statistics (NIS) in collaboration with the Ministry of Health (MoH). Data collection took place from September 15, 2021, to February 15, 2022.

The primary objective of the 2021-22 CDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the survey collected information on fertility, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and children, maternal and child health, adult and childhood mortality, women’s empowerment, domestic violence, awareness and behavior regarding HIV/AIDS and other sexually transmitted infections (STIs), and other health-related issues such as smoking.

The information collected through the 2021-22 CDHS is intended to assist policymakers and program managers in evaluating and designing programs and strategies for improving the health of Cambodia’s population. The survey also provides data on indicators relevant to the Sustainable Development Goals (SDGs) for Cambodia.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15 to 49

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, all men age 15-49, and all children aged 0-4 resident in the household.

Kind of data

Sample survey data [ssd]

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four questionnaires were used in the 2021-22 CDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Cambodia. In addition, a self-administered Fieldworker Questionnaire collected information about the survey’s fieldworkers.

Cleaning operations

The processing of the 2021-22 CDHS data began as soon as the fieldwork started. When data collection was completed in each cluster, the electronic data files were transferred via the IFSS to the NIS central office in Phnom Penh. The data files were registered and checked for inconsistencies, incompleteness, and outliers. Errors and inconsistencies were communicated to the field teams for review and correction. Secondary editing, done by NIS data processors, was carried out in the central office and included resolving inconsistencies and coding open-ended questions. The paper Biomarker Questionnaires were collected by field coordinators and then compared with the electronic data files to assess whether any inconsistencies arose during data entry. Data processing and editing were carried out using the CSPro software package. The concurrent data collection and processing offered an advantage because it maximized the likelihood of the data being error-free. Timely generation of field check tables allowed for effective monitoring. The secondary editing of the data was completed in March 2022.

Response rate

A total of 21,270 households were selected for the CDHS sample, of which 20,967 were found to be occupied. Of the occupied households, 20,806 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 19,845 women age 15-49 were identified as eligible for individual interviews. Interviews were completed with 19,496 women, yielding a response rate of 98%. In the subsample of households selected for the male survey, 9,079 men age 15-49 were identified as eligible for individual interviews and 8,825 were successfully interviewed, yielding a response rate of 97%.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors are errors that were made during data collection and data processing such as failure to locate and interview the correct household, misunderstanding of the questions by either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2021-22 Cambodia Demographic and Health Survey (CDHS) to minimize this type of error, nonsampling errors are impossible to eliminate completely and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2021-22 CDHS is only one of many possible samples that could have been selected from the same population, using exactly the same design. Each of those samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2021-22 CDHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the 2021-22 CDHS was an SAS program. This program used the Taylor linearization method for estimate variances for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables

• Household age distribution
• Age distribution of eligible and interviewed women
• Age distribution of eligible and interviewed men
• Age displacement at age 14/15
• Age displacement at age 49/50
• Pregnancy outcomes by years preceding the survey
• Completeness of reporting
• Height and weight data completeness and quality for children
• Height measurements from random subsample of measured children
• Interference in height and weight measurements of children
• Interference in height and weight measurements of women
• Heaping in anthropometric measurements for children (digit preference)
• Observation of handwashing facility
• School attendance by single-year age
• Vaccination cards photographed
• Number of enumeration areas completed by month and province
• Sibship size and sex ratio of siblings
• Pregnancy-related mortality trends
• Pregnancy-related mortality

See details of the data quality tables in Appendix C of the final report.

The primary data consist of allele or haplotype frequencies for N=1036 anonymized U.S. population samples. Additional files are supplements to the associated publications. Any changes to spreadsheets are listed in the "Change Log" tab within each spreadsheet. DOI numbers for associated publications are listed below, under "References".

The World Bank-UNHCR Joint Data Center (JDC) provided his support for a household survey in the Great Kasai area in the Democratic Republic of Congo (DRC) conducted by the UNHCR Sub Office Kananga in collaboration with the National Institute of Statistics (INS). The main objective of the survey was to generate high-quality socioeconomic data to inform decision making and programming of humanitarian and development interventions and policy including UNHCR DRC’s core programing and multi-year strategy implementation as well as UNHCR Angola’s planning of voluntary repatriation. A wide range of stakeholders were consulted and involved from the design stage of the survey tools, including (but not limited to) the World Bank, UNDP, UNICEF, IOM, WFP, FAO, UNFPA, the National Institute of Statistics (INS), the Provincial Ministries of planning, the Protection, Shelter and Health Clusters members and CRIs actors the Grand-Kasai-level.

The data covers the following areas: land ownership, documentation, agro-pastoral activities, conflicts, employment and sources of income, household assets, consumption, savings, and credit, right to housing and habitat, access to basic social services and information, peace, security and peaceful cohabitation, physical and mental health, food insecurity, inclusion, and access to legal resources of the people for whom and with whom UNHCR works.

The Health Statistics and Health Research Database is Estonian largest set of health-related statistics and survey results administrated by National Institute for Health Development. Use of the database is free of charge.

The database consists of eight main areas divided into sub-areas. The data tables included in the sub-areas are assigned unique codes. The data tables presented in the database can be both viewed in the Internet environment, and downloaded using different file formats (.px, .xlsx, .csv, .json). You can download the detailed database user manual here (.pdf).

The database is constantly updated with new data. Dates of updating the existing data tables and adding new data are provided in the release calendar. The date of the last update to each table is provided after the title of the table in the list of data tables.

A contact person for each sub-area is provided under the "Definitions and Methodology" link of each sub-area, so you can ask additional information about the data published in the database. Contact this person for any further questions and data requests.

Read more about publication of health statistics by National Institute for Health Development in Health Statistics Dissemination Principles.

Ecuador Tourist Arrival: Resident: by Country of Origin: Aruba data was reported at 5,972.000 Person in 2023. This records an increase from the previous number of 2,017.000 Person for 2022. Ecuador Tourist Arrival: Resident: by Country of Origin: Aruba data is updated yearly, averaging 617.000 Person from Dec 1997 (Median) to 2023, with 27 observations. The data reached an all-time high of 5,972.000 Person in 2023 and a record low of 0.000 Person in 1999. Ecuador Tourist Arrival: Resident: by Country of Origin: Aruba data remains active status in CEIC and is reported by National Institute of Statistics and Census. The data is categorized under Global Database’s Ecuador – Table EC.Q003: Tourist Arrival: National Institute of Statistics and Census: by Country of Origin.

Financial overview and grant giving statistics of National Institute of Social Sciences

Financial overview and grant giving statistics of National Institute For Pharmaceutical Technology And Education

Industrial Production: Motor Boat data was reported at 537.000 Unit in 2023. This records a decrease from the previous number of 627.000 Unit for 2022. Industrial Production: Motor Boat data is updated yearly, averaging 1,038.500 Unit from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 2,080.000 Unit in 2010 and a record low of 339.000 Unit in 2020. Industrial Production: Motor Boat data remains active status in CEIC and is reported by National Institute of Statistics and Censuses. The data is categorized under Global Database’s Argentina – Table AR.B016: Industrial Production: National Institute of Statistics and Censuses: Annual.

A bilateral study to compare guarded-hot-plate measurements at extended temperatures between laboratories at the National Institute of Standards and Technology (NIST) and the National Physical Laboratory (NPL) is presented. Measurements were conducted in accordance with standardized test methods (ISO 8302 or ASTM C177) over a temperature range from 20 °C to 160 °C (293 K to 433 K). Following a blind round-robin format, specimens of non-woven fibrous glass mat, approximately 22 mm thick and having a nominal bulk density of 200 kg/m3, were prepared and studied. Results of the study show that the thermal conductivity measurements agree over the temperature range of interest to within ±1.0 %, or less. See also related "Data from: Collaborative Guarded-Hot-Plate Tests between the Laboratoire national de métrologie et d'essais and the National Institute of Standards and Technology," accessible at https://doi.org/10.18434/T4XK5G

Financial overview and grant giving statistics of National Institute for Jewish

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Collective quarters, household, and population

Universe

All the population in the national territory at the moment the census is carried out. This includes everyone (of any nationality) that spent the night of November 16-17 in any Argentine diplomatic embassy abroad; all the sailors or fishermen that spent the night of November 16-17 in ships with an Agentine flag or a foreign one docked in Argentine waters; and all Argetine workers that are abroad performing missions for the national government.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Argentine National Institute of Statistics and Censuses (INDEC)

SAMPLE DESIGN: Systematic sample of every 10th private household and collective quarters with a random start. The sample was elaborated by INDEC from the microdata of 100 percent of households.

SAMPLE UNIT: Household

SAMPLE FRACTION: 10%

SAMPLE UNIVERSE: 100% of the population and households enumerated.

SAMPLE SIZE (person records): 3,626,103

Mode of data collection

Face-to-face [f2f]

Research instrument

(1) Household questionnaire (2) Population questionnaire (both questionnaires are part of the same booklet).

Response rate

COVERAGE: 97.25%

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling

UNITS IDENTIFIED: - Dwellings: No - Vacant units: Yes - Households: Yes - Individuals: Yes - Group quarters: Yes

UNIT DESCRIPTIONS: - Dwellings: Any independent premises within the total installation that has been equipped to lodge persons and permits them to reside there for many reasons (they are watchpersons or guards of an industry for example). - Group quarters: Those places, buildings and houses in which the sick, police, prisoners for various crimes, young or children delinquents, workers, students, religious persons, the elderly or other groups that carry out or live together under the same roof. These places, buildings or houses in which groups of persons live without family ties between them, or that is, who being NON FAMILY groups, have been designated by the government, by a private company or other institution, to resolve problems or social necessities like health, discipline, security, social adaptation, work in places far from the family dwelling, old age, being orphaned, poverty, study or religious life, etc.

Universe

All live individuals at midnight June 25, 1995

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Institute of Statistics and Censuses

SAMPLE DESIGN: Systematic sample of every 10th household with a random start, drawn by the Minnesota Population Center

SAMPLE UNIT: Household

SAMPLE FRACTION: 10%

SAMPLE SIZE (person records): 435,728

Mode of data collection

Face-to-face [f2f]

Research instrument

A single enumeration form requested information on the dwelling and household, and a second enumeration form requested information of the individuals.

National Institute of Standards and Technology (NIST) public data inventory is a catalog of digital products generated from the NIST enterprise data inventory (EDI). The catalog is dynamically updated in coordination with mission goals for the dissemination of information for discovery and access. It includes digital products derived from multiple disciplines of scientific, engineering and technology areas of research and operation. This inventory is provided as a data.json file format, based on the DCAT-US Schema v1.1 standard definition.

Apportionment file 11382953 retrieved from OMB public records

Ecuador Tourist Arrival: Resident: by Country of Origin: El Salvador data was reported at 4,099.000 Person in 2023. This records an increase from the previous number of 2,272.000 Person for 2022. Ecuador Tourist Arrival: Resident: by Country of Origin: El Salvador data is updated yearly, averaging 793.000 Person from Dec 1997 (Median) to 2023, with 27 observations. The data reached an all-time high of 10,986.000 Person in 2013 and a record low of 0.000 Person in 1998. Ecuador Tourist Arrival: Resident: by Country of Origin: El Salvador data remains active status in CEIC and is reported by National Institute of Statistics and Census. The data is categorized under Global Database’s Ecuador – Table EC.Q003: Tourist Arrival: National Institute of Statistics and Census: by Country of Origin.

Data for multi-site, multi-platform comparison of magnetic resonance imaging (MRI) T1 measurement using the International Society of Magnetic Resonance in Medicine/National Institute of Standards and Technology (ISMRM/NIST) system phantom. Includes data sets for T1 measurement by inversion recovery (IR) and variable flip angle (VFA) methods at 1.5 tesla and 3 tesla. At 1.5 T, data is from 2 different vendor systems, 9 total MRI machines. At 3 T, data is from 3 different vendor systems, 18 total MRI machines.