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The National Institute of Statistics (Romania) publishes national level statistical datasets on an annual basis. These datasets inlcude, but are not limited to: construction; domestic trade; education; environment; labour force; population; prices; industry; and energy. Data relating to mineral reserves, resources and production are possibly reported by the National Institute of Statistics (Romania); however, registration is required to access the data.

Website: http://www.insse.ro/cms/en

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French national statistics.

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Material available at:

• http://www.insee.fr/en/themes/

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Topics include:

• Agriculture
• Economic outlook
• Economy
• Education
• Enterprises
• Geography
• Health
• Income - Wages
• Industries - Food Industries - Construction
• Labour - Employment
• Living standards - Society
• National accounts - Public finances
• Population
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The publications and data made available on the current site may be viewed and consulted free of charge; they may be reused, including for commercial purposes, without a license and without payment of royalties, subject only to the following reserves: the user must respect the integrity of the information and data, and mention the source specifically.

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.

The second Survey on Employment and the Informal Sector (EESI 2) is carried out in 2010 by the Cameroon National Institute of Statistics (NIS). This survey is part of the operations chosen in the National Strategy for the Development of Statistics (NSDS) for the follow-up and evaluation of actions undertaken in the framework of the Growth and Employment Strategy Paper (GESP) which integrates the achievement of the Millennium Development Goals (MDGs) as a concern. This Survey on Employment and the Informal Sector (EESI) is a two-phase national statistical survey, the first phase of which aims to capture employment (Survey on the employment) and the second to assess the economic activities of the informal non-agricultural sector (Survey on the informal Sector).

Abstract

From 2014 to 2015, with the aim of collecting data to monitor progress across Rwanda’s health programs and policies, the Government of Rwanda (GOR) conducted the Rwanda Demographic and Health Survey (RDHS) through the Ministry of Health (MOH) and the National Institute of Statistics of Rwanda (NISR) with the members of the national steering committee to the DHS and the technical assistance of ICF International.

The main objectives of the 2014-15 RDHS were to: • Collect data at the national level to calculate essential demographic indicators, especially fertility and infant and child mortality, and analyze the direct and indirect factors that relate to levels and trends in fertility and child mortality • Measure levels of knowledge and use of contraceptive methods among women and men • Collect data on family health, including immunization practices; prevalence and treatment of diarrhea, acute upper respiratory infections, and fever among children under age 5; antenatal care visits; assistance at delivery; and postnatal care • Collect data on knowledge, prevention, and treatment of malaria, in particular the possession and use of treated mosquito nets among household members, especially children under age 5 and pregnant women • Collect data on feeding practices for children, including breastfeeding • Collect data on the knowledge and attitudes of women and men regarding sexually transmitted infections (STIs) and HIV and evaluate recent behavioral changes with respect to condom use • Collect data for estimation of adult mortality and maternal mortality at the national level • Take anthropometric measurements to evaluate the nutritional status of children, men, and women • Assess the prevalence of malaria infection among children under age 5 and pregnant women using rapid diagnostic tests and blood smears • Estimate the prevalence of HIV among children age 0-14 and adults of reproductive age • Estimate the prevalence of anemia among children age 6-59 months and adult women of reproductive age • Collect information on early childhood development • Collect information on domestic violence

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-59

Universe

The survey covered all de jure household members (usual residents), all women age 15-49 years and all men age 15-59 who were usual residents in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The sampling frame used for the 2014-15 RDHS was the 2012 Rwanda Population and Housing Census (RPHC). The sampling frame consisted of a list of enumeration areas (EAs) covering the entire country, provided by the National Institute of Statistics of Rwanda, the implementing agency for the RDHS. An EA is a natural village or part of a village created for the 2012 RPHC; these areas served as counting units for the census.

The 2014-15 RDHS followed a two-stage sample design and was intended to allow estimates of key indicators at the national level as well as for urban and rural areas, five provinces, and each of Rwanda's 30 districts (for some limited indicators). The first stage involved selecting sample points (clusters) consisting of EAs delineated for the 2012 RPHC. A total of 492 clusters were selected, 113 in urban areas and 379 in rural areas.

The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected EAs from July 7 to September 6, 2014, and households to be included in the survey were randomly selected from these lists. Twenty-six households were selected from each sample point, for a total sample size of 12,792 households. However, during data collection, one of the households was found to actually be two households, which increased the total sample to 12,793. Because of the approximately equal sample sizes in each district, the sample is not self-weighting at the national level, and weighting factors have been added to the data file so that the results will be proportional at the national level.

All women age 15-49 who were either permanent residents of the household or visitors who stayed in the household the night before the survey were eligible to be interviewed. In half of the households, all men age 15-59 who either were permanent household residents or were visiting the night before the survey were eligible to be interviewed.

In the subsample of households not selected for the male survey, anemia and malaria testing were performed among eligible women who consented to being tested. With the parent's or guardian's consent, children aged 6-59 months were tested for anemia and malaria in this subsample. Height and weight information was collected from eligible women, and children (age 0-5) in the same subsample. In the subsample of households selected for male survey, blood spot samples were collected for laboratory testing of HIV from eligible women and men who consented. Height and weight information was collected from eligible men. In one-third of the same subsample (or 15 percent of the entire sample), blood spot samples were collected for laboratory testing of children age 0-14 for HIV.

The domestic violence module was implemented in the households selected for the male survey: The domestic violence module for men was implemented in 50 percent of the household selected for male survey and domestic violence for women was conducted in the remaining 50 percent of household selected for male survey (or 25 percent of the entire sample, each).

For further details on sample selection, see Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three types of questionnaires were used in the 2014-15 RDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. They are based on questionnaires developed by the worldwide DHS Program and on questionnaires used during the 2010 RDHS. To reflect relevant issues in population and health in Rwanda, the questionnaires were adapted during a series of technical meetings with various stakeholders from government ministries and agencies, nongovernmental organizations, and international donors. The questionnaires were translated from English into Kinyarwanda.

The Household Questionnaire was used to list all of the usual members and visitors in the selected households as well as to identify women and men eligible for individual interviews. Basic information was collected on the characteristics of each person listed, including relationship to the head of the household, sex, residence status, age, and marital status along with survival status of children’s parents, education, birth registration, health insurance coverage, and tobacco use.

The Woman’s Questionnaire was administered to all women age 15-49 living in the sampled households.

The Man’s Questionnaire was administered to all men age 15-59 living in every second household in the sample. It was similar to the Woman’s Questionnaire but did not include questions on use of contraceptive methods or birth history; pregnancy and postnatal care; child immunization, health, and nutrition; or adult and maternal mortality.

Cleaning operations

The processing of the 2014-15 RDHS data began as soon as questionnaires were received from the field. Completed questionnaires were returned to NISR headquarters. The numbers of questionnaires and blood samples (DBS and malaria slides) were verified by two receptionists. Questionnaires were then checked, and open-ended questions were coded by four editors who had been trained for this task and who had also attended the questionnaire training sessions for the field staff. Blood samples (DBS and malaria slides) with transmittal sheets were sent respectively to the RBC/NRL and Parasitological and Entomology Laboratory to be screened for HIV and tested for malaria.

Questionnaire data were entered via the CSPro computer program by 17 data processing personnel who were specially trained to execute this activity. Data processing was coordinated by the NISR data processing officer. ICF International provided technical assistance during the entire data processing period.

Processing the data concurrently with data collection allowed for regular monitoring of team performance and data quality. Field check tables were generated regularly during data processing to check various data quality parameters. As a result, feedback was given on a regular basis, encouraging teams to continue in areas of high quality and to correct areas of needed improvement. Feedback was individually tailored to each team. Data entry, which included 100 percent double entry to minimize keying errors, and data editing were completed on April 26, 2015. Data cleaning and finalization were completed on May 15, 2015.

Response rate

A total of 6,249 men age 15-59 were identified in this subsample of households. Of these men, 6,217 completed individual interviews, yielding a response rate of 99.5 percent.

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 the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2014-15 Rwanda

STATEC (National Institute of Statistics and Economic Studies of the Grand Duchy of Luxembourg) publishes numerous national level statistical datasets on an annual basis. These inlcude, but are not limited to: labour market; education and training; population; health; national accounts; climate; environment; industry; and agriculture. Data relating to mineral reserves, resources and production do not appear to be reported by STATEC.

Website: http://www.statistiques.public.lu/en/index.html

Financial overview and grant giving statistics of FOUNDATION FOR THE NATIONAL INSTITUTE OF HEALTH INC

Italy ISTAT Forecast: YoY: CL: Unemployment Rate data was reported at 10.800 % in 2018. This records a decrease from the previous number of 11.200 % for 2017. Italy ISTAT Forecast: YoY: CL: Unemployment Rate data is updated yearly, averaging 11.450 % from Dec 2013 (Median) to 2018, with 6 observations. The data reached an all-time high of 12.500 % in 2014 and a record low of 1.100 % in 2013. Italy ISTAT Forecast: YoY: CL: Unemployment Rate data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Italy – Table IT.G030: Employment and Unemployment: Year on Year Growth: Forecast: National Institute of Statistics.

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 Science and Civic Engagement

NIST developed a reference material consisting of synthetic fragments of the SARS-CoV-2 virus RNA, which is the target of molecular diagnostic tests. These RNA fragments can assist in the development and validation of RT-qPCR assays for the detection SARS-CoV-2. The RNA fragments are characterized for concentration using digital PCR methods, may be used to assess limits of detection for SARS-CoV-2 assays, and may calibrate other in-house or commercial SARS-CoV-2 controls. This dataset includes data used for RTGM 10169 SARs-Cov-2 Research Grade Test Material validation. The Illumina and ONT sequence data were used to verify the construct sequence.

Ecuador INEC Projection: Population: 20 to 24 Yrs Old data was reported at 1,515,761.000 Person in 2020. This records an increase from the previous number of 1,496,206.000 Person for 2019. Ecuador INEC Projection: Population: 20 to 24 Yrs Old data is updated yearly, averaging 1,496,206.000 Person from Dec 2018 (Median) to 2020, with 3 observations. The data reached an all-time high of 1,515,761.000 Person in 2020 and a record low of 1,475,955.000 Person in 2018. Ecuador INEC Projection: Population: 20 to 24 Yrs Old 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.G003: Population: Projection: National Institute of Statistics and Census.

Analysis unit

Persons, households, and dwellings Low ages grouped into categories

UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: yes

UNIT DESCRIPTIONS: - Dwellings: Dwelling refers to a room (or set of rooms) that is: regularly dedicated to residential use; separate (i.e. surrounded by walls and covered by a roof); independent (with at least one external access that is either independent or through shared entry areas - road, courtyard, stairs, landings, common balconies, terraces, etc. - access, in other words, does not require passing through other dwellings); incorporated in a building (or constitutes a building). - Households: Group of persons who are cohabiting as usual residents of a dwelling - Group quarters: Collective residential structure refers to facilities used to house large groups of people and/or one or more families. This category includes hotels, hospitals, rest homes for senior citizens and reception centers and institutes of various kinds (religious, healthcare-related, welfare support, educational, etc.).

Universe

All citizens or foreigners registered to stay in Italy

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: National Institute of Statistics

SAMPLE SIZE (person records): 2968065.

SAMPLE DESIGN: 5% sample drawn by national statistics office

Mode of data collection

Face-to-face [f2f]

Research instrument

Two forms for dwellings and persons: a short form (CP.1B) and a long form (CP.1). One third of families in population centers from municipalities with at least 20,000 inhabitants or provincial capitals received the long form. Persons living in cohabitation received a separate form (CP.2).

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

Person, household, and dwelling

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: Yes - Households: Yes - Individuals: Yes - Group quarters: Yes

UNIT DESCRIPTIONS: - Dwellings: A dwelling is a building or independent building unit that is built, adapted or converted so that it may be inhabited by one or more people, either permanently or temporarily. It should have direct or independent access from the street or through public-use spaces, like hallways, patios, or stairs. It is normally separated by walls and a roof so that the people who live in it may separate themselves from others for cooking and eating, sleeping, and protection from the environment. - Households: A household is a person or group of persons, related or not, who occupy all or part of a dwelling. They share at least the main meals and provide for their other basic needs from a common budget - Group quarters: A collective dwelling is intended for habitation by persons, usually without family ties, who are subject to administrative rules and who live together for reasons of education, health, religion, work, or tourism, among others. Among collective dwellings there are 2 varieties: institutional and non-institutional.

Universe

All persons residing in the country.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Institute of Statistics and Computing

SAMPLE DESIGN: Systematic sample was drawn from the 15% stratified sample developed by the statistical office.

SAMPLE UNIT: Household

SAMPLE FRACTION: 10%

SAMPLE SIZE (person records): 2,745,895

Mode of data collection

Face-to-face [f2f]

Research instrument

A single form with three sections for the dwelling, household, and individuals

The National Institute of Mental Health Data Archive (NDA) makes available human subjects data collected from hundreds of research projects across many scientific domains. NDA provides infrastructure for sharing research data, tools, methods, and analyses enabling collaborative science and discovery. De-identified human subjects data, harmonized to a common standard, are available to qualified researchers. Summary data are available to all.

The NDA mission is to accelerate scientific research and discovery through data sharing, data harmonization, and the reporting of research results.

Financial overview and grant giving statistics of National Institute for Direct Instruction

Financial overview and grant giving statistics of National Institute on the Teaching of Psychology

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.

Panama INE Projection: Population: Male data was reported at 2,794,812.000 Person in 2050. This records an increase from the previous number of 2,782,822.000 Person for 2049. Panama INE Projection: Population: Male data is updated yearly, averaging 2,513,211.000 Person from Jun 2018 (Median) to 2050, with 33 observations. The data reached an all-time high of 2,794,812.000 Person in 2050 and a record low of 2,085,950.000 Person in 2018. Panama INE Projection: Population: Male data remains active status in CEIC and is reported by National Institute of Statistics and Census. The data is categorized under Global Database’s Panama – Table PA.G002: Population: Projection: National Institute of Statistics and Census.