Educational Technology in Public Schools, 2008 (FRSS 92), is a study that is part of the Fast Response Survey System (FRSS) program; program data is available since 1998-99 at . FRSS 92 (https://nces.ed.gov/surveys/frss/) is a sample survey that provides national estimates on the availability and use of educational technology in public elementary and secondary schools during fall 2008. This is one of a set of three surveys (at the district, school, and teacher levels) that collected data on a range of educational technology resources. The study was conducted using mailed questionnaires and respondents had the option of completing the survey via the web. Schools were sampled. The study's weighted response rate was 79 percent. Key statistics produced from FRSS 92 were information on computer hardware and internet access, availability of staff to help integrate technology into instruction and provide timely technical support, and perceptions of educational technology issues at the school and district levels. Respondents reported the number of instructional computers within their schools, by type, mobility, and location. The survey also asked respondents about the types of operating systems or platforms used on instructional computers. Data on the number of handheld devices provided to school personnel and students, and the number of other technology devices provided for instructional purposes were also collected. Respondents indicated the extent to which technology staff provided assistance with technology support and integration and the response times for obtaining such support. Respondents gave opinions on statements related to using educational technology in their schools.

This dataset is a polygon coverage of counties limited to the extent of the Pocahontas No. 3 coal bed resource areas and attributed with statistics on the thickness of the Pocahontas No. 3 coal bed, its elevation, and overburden thickness, in feet. The file has been generalized from detailed geologic coverages found elsewhere in Professional Paper 1625-C.

Datasets excerpts from the Labour Force Survey provided by Statistics Canada. The data in these tables have additional details compared to datasets available on the Statistics Canada website. All data provided is on an annual basis. Data is available up to 2024 and current as of March 2025. Note: Files require the Beyond 20/20 Professional Browser. Information on Beyond 20/20 can be found here: https://www.statcan.gc.ca/en/public/beyond20-20. Several Canadian University sites have detailed guides and other resources for users of Beyond 20/20. Source: Statistics Canada, Labour Force Survey, March 2025. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada.

Datasets excerpts from the Labour Force Survey provided by Statistics Canada. The data in these tables have additional details compared to datasets available on the Statistics Canada Website. All data provided is on an annual basis. Data is available up to 2024 and current as of April 2025. Note: Files require the Beyond 20/20 Professional Browser. Information on Beyond 20/20 can be found here: https://www.statcan.gc.ca/en/public/beyond20-20. Several Canadian University sites have detailed guides and other resources for users of Beyond 20/20. Source: Statistics Canada, Labour Force Survey (LFS), April 2025. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada.

Self-reported data from approximately 380 public libraries, First Nation public libraries and contracting organizations. The data includes: general information including address financial information holdings information staffing information facilities information activities information including typical week data partnership information (2011 onwards) Data from 2011 and onwards is from a refreshed database. New fields were added for: provincial funding types project grant types special collections holdings circulation of E-resources including E-books lending laptops program types readers advisory transactions information technology support In 2012, new fields were added for: E-readers requests for accessible format materials business and economic partnerships. In 2013 more fields were added for social media visits and other professional staff. In 2016 a field was added for indigenous language training and retention, while circulating and reference holdings information was combined. In 2017 fields were added for e-learning services, students hired for a summer or semester, circulating wireless hot spots, and library service visits to residence-bound people. In 2019 fields were added for Facility Rentals and Bookings, ‘Pop-up’ Libraries, Extended Services and Facilities, Government Services Partnerships, and Business and Economic Sector Partnerships. The database uses the common name "LibStats".

Through its Employment and Financial Services (EFS) division, Assisted Living and Social Services (ALSS) programs form a strong foundation of support to help many Albertans find and keep jobs. The ministry provides financial support, employment services, career resources, referrals, information on job fairs and workshops, and local labor market information. The goal is to help individuals and families gain independence by providing opportunities to enhance their skills to get jobs. The alis.alberta.ca website provides employment resources to help Albertans enhance their employability, plan for education and training, make informed career choices, and connect to and be successful in the labour market. This dataset provides information on web traffic statistics for the alis website, including information on pageviews and web sessions, demographic information for web sessions, and traffic information for the alis YouTube channel at: https://www.youtube.com/user/ALISwebsite.

This dataset is a polygon coverage of counties limited to the extent of the Pond Creek coal bed resource areas and attributed with statistics on the thickness of the Pond Creek coal zone, its elevation, and overburden thickness, in feet. The file has been generalized from detailed geologic coverages found elsewhere in Professional Paper 1625-C.

This dataset is a polygon coverage of counties limited to the extent of the Lower Kittanning coal bed resource areas and attributed with statistics on these coal quality parameters: ash yield (percent), sulfur (percent), SO2 (lbs per million Btu), calorific value (Btu/lb), arsenic (ppm) content and mercury (ppm) content. The file has been generalized from detailed geologic coverages found elsewhere in Professional Paper 1625-C. The attributes were generated from public data found in the geochemical dataset found in Chap. E, Appendix 2, Disc 1, as well as some additional proprietary data. Please see the metadata file found in Chap. E, Appendix 3, Disc 1, for more detailed information on the geochemical attributes. The county statistical data used for this data set are found in Tables 2-3, 12-13 and 25-26 in Chap. E, Disc 1. Additional county geochemical statistics for other parameters are found in Tables 14-24, Chap. E, Disc 1.

Ready-reference guide for human resources (HR) professionals. Contains demographic statistics along with other valuable employee data for full time permanent (FTP) and part time permanent (PTP) SSA employees.

This dataset is a polygon coverage of counties limited to the extent of the Fire Clay coal zone resource areas and attributed with statistics on the thickness of the Fire Clay coal bed, its elevation, and overburden thickness, in feet. The file has been generalized from detailed geologic coverages found elsewhere in Professional Paper 1625-C. This resource model for the Fire Clay coal zone must be considered provisional, because the correlation of the zone continues to be evaluated in West Virginia.

Through its Employment and Financial Services (EFS) division, Assisted Living and Social Services (ALSS) programs form a strong foundation of support to help many Albertans find and keep jobs. The ministry provides financial support, employment services, career resources, referrals, information on job fairs and workshops, and local labor market information. The goal is to help individuals and families gain independence by providing opportunities to enhance their skills to get jobs. The alis.alberta.ca website provides employment resources to help Albertans enhance their employability, plan for education and training, make informed career choices, and connect to and be successful in the labour market. This dataset provides information on web traffic statistics for the alis website, including information on pageviews and web sessions, demographic information for web sessions, and traffic information for the alis YouTube channel at: https://www.youtube.com/user/ALISwebsite.

This dataset is a polygon coverage of counties limited to the extent of the Pittsburgh coal bed resource areas and attributed with statistics on these coal quality parameters: ash yield (percent), sulfur (percent), SO2 (lbs per million Btu), calorific value (Btu/lb), arsenic (ppm) content and mercury (ppm) content. The file has been generalized from detailed geologic coverages found elsewhere in Professional Paper 1625-C. The attributes were generated from public data found in the geochemical dataset found in Chap. C, Appendix 8, Disc 1, as well as some additional proprietary data. Please see the metadata file found in Chap. C, Appendix 9, Disc 1, for more detailed information on the geochemical attributes. The county statistical data used for this data set are found in Tables 2-5 and 17-18, Chap. C, Disc 1. Additional county geochemical statistics for other parameters are found in Tables 6-16, Chap. C, Disc 1.

This dataset is a polygon coverage of counties limited to the extent of the Pond Creek coal zone resource areas and attributed with statistics on these coal quality parameters: ash yield (percent), sulfur (percent), SO2 (lbs per million Btu), calorific value (Btu/lb), arsenic (ppm) content and mercury (ppm) content. The file has been generalized from detailed geologic coverages found elsewhere in Professional Paper 1625-C. The attributes were generated from public data found in geochemical dataset found in Chap. G, Appendix 7, Disc 1. Please see the detailed information on the geochemical attributes. The county statistical data used for this data set are found in Tables 2-5 and 17-18, Chap. G, Disc 1. Additional county geochemical statistics for other parameters are found in Tables 6-16, Chap. G, Disc 1.

• Annual exchange rates of Standard Local Currency Units (SLC) per US dollar are available for 213 countries and territories from 1970 to calendar year (t-1).

• Annual exchange rates of Local Currency Units (LCU) per US dollar are available for 219 countries and territories from 1970 to calendar year (t-1).

• Monthly exchange rates of Local Currency Units (LCU) per US dollar are available for 217 countries and territories from January 1970 to the most recent available monthly data in year t for every country.

Data revision: 2024-09-27

Supplemental Information:

Unit of measure: * Standard Local Currency unit (SLC) per US dollar.* Local Currency unit (LCU) per US dollar.

Time coverage: 1970-2024

More detailed information on this dataset is provided in the FAOSTAT metadata.

Citation:

FAO. [YYYY (year of last update)]. [Name of database: Name of dataset OR Name of database]. [Accessed on [DD Month YYYY]]. [URL] Licence: CC-BY-4.0

Contact points:

Resource Contact: FAO Statistics Division (ESS), Social and Economic Statistics Team

Metadata Contact: FAO Statistics Division (ESS), Social and Economic Statistics Team

Data lineage:

Source data

• UNSD National Accounts Estimates of Analytical Main Aggregates (AMA) is the main data source of Annual exchange rates of Standard Local Currency Units (SLC) per US dollar from 1970 to year (t-2) but the year (t-1) data are captured from IMF Macroeconomic & Financial Data. * IMF Macroeconomic & Financial Data is the main data source of Annual and Monthly exchange rates of Local Currency Units (LCU) per US dollar from 1970 to year (t-1) for Annual exchange rates and to the most recent available monthly exchange rates.* The link to the sources are: http://unstats.un.org/unsd/snaama/dnlList.asp'', http://data.imf.org/?sk=af1819f1-9b6c-43ec-bee4-b1b55fa54cf7&sId=1390030341854.

Data collection method: Annual and Monthly exchange rates are harvested from UNSD and IMF through API's.

Base period: Not applicable

More information on data validation, imputation, regional aggregation, use of statistical classifications, data revision policies and practices are provided in the FAOSTAT metadata.

Resource constraints:

User access: In line with FAO’s Statistics Code of Practice, data are disseminated on FAO's website respecting professional independence and in an objective, professional and transparent manner in which all users are treated equitably. |FAO Statistical Database Terms of Use This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0). In addition to this license, some database specific terms of use are listed: Terms of Use of Datasets.

Online resources:

The INE (Instituto Nacional de Estadística) Statistical Inventory is a vital resource offering detailed and up-to-date statistical data on various aspects of Spain's real estate market and broader economic indicators. It includes advanced search capabilities, historical consultations, and methodological insights, making it an indispensable tool for researchers, policymakers, and real estate professionals. The inventory covers a wide range of data points, including property statistics, classifications, and ongoing plans, providing a holistic view of the market dynamics in Spain.

Users of the INE Statistical Inventory range from government agencies and urban planners to private sector analysts and academic researchers. The data supports informed decision-making, market forecasting, and regulatory compliance, helping stakeholders understand trends and patterns in property development, ownership, and usage. Its comprehensive nature and official backing ensure high reliability and accuracy.

In the Spanish market, where real estate plays a crucial role in the economy, having access to such a centralized and authoritative data source is invaluable. The inventory aids in transparency, supports investment decisions, and enhances the efficiency of the property market by providing clear, accessible, and well-structured statistical information. Its integration with other national statistical operations further enriches its value for demographic and economic analysis.

Food Balance Sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply and its utilization. The total quantity of foodstuffs produced in a country added to the total quantity imported and adjusted to any change in stocks that may have occurred since the beginning of the reference period gives the supply available during that period. On the utilization side a distinction is made between the quantities exported, fed to livestock, used for seed, put to manufacture for food use and non-food uses, losses during storage and transportation, and food supplies available for human consumption. The per caput supply of each such food item available for human consumption is then obtained by dividing the respective quantity by the related data on the population actually partaking of it. Data on per caput food supplies are expressed in terms of quantity and - by applying appropriate food composition factors for all primary and processed products - also in terms of caloric value and protein and fat content.

Data revision: 2020-07-29

Supplemental Information:

Reference area: All countries of the world – with some minor exceptions – and geographical aggregates according to the United Nations M49 list.

Notes on geographical coverage:

(1) Data of Iraq do not include Kurdistan region.

(2) Since 2007 France data include French Guiana, Martinique, Guadeloupe, Reunion territories but they exclude French Polynesia and New Caledonia territories.

(3) Information provided by the Russian Federation includes statistical data for the Autonomous Republic of Crimea and the city of Sevastopol, Ukraine, temporarily occupied by the Russian Federation and is presented without prejudice to relevant UN General Assembly and UN Security Council resolutions, including UN General Assembly resolution 68/262 of 27 March 2014 and UN Security Council resolution 2202 (2015) of 17 February 2015, which reaffirm the territorial integrity of Ukraine. Information provided by Ukraine excludes statistical data concerning the Autonomous Republic of Crimea, the city of Sevastopol and certain areas of the Donetsk and Luhansk regions. The information is presented without prejudice to relevant UN General Assembly and UN Security Council resolutions, including UN General Assembly resolution 68/262 of 27 March 2014 and UN Security Council resolution 2202 (2015) of 17 February 2015, which reaffirm the territorial integrity of Ukraine.

Unit of measure:

• Domestic supply quantity: 1000 tonnes [1000 t]

• Export Quantity: 1000 tonnes [1000 t]

• Fat supply quantity; Grams per capita per day [g/cap/d]

• Feed: 1000 tonnes [1000 t]

• Food: 1000 tonnes [1000 t]

• Food supply: Kilograms per capita per day [kcal/cap/d]

• Food supply quantity: Kilograms per capita per year [kg/cap/y]

• Import Quantity: 1000 tonnes [1000 t]

• Other Util: 1000 tonnes [1000 t]

• Processed: 1000 tonnes [1000 t]

• Production Quantity: 1000 tonnes [1000 t]

• Protein supply quantity: Grams per capita per day [g/cap/d]

• Seed: 1000 tonnes [1000 t]

• Stock Variation: 1000 tonnes [1000 t]

• Total Population - Both sexes [1000]

Time coverage: 1961 - 2017

More detailed information on this dataset is provided in the FAOSTAT metadata.

Citation:

FAO. [YYYY (year of last update)]. [Name of database: Name of dataset OR Name of database]. [Accessed on [DD Month YYYY]]. [URL] Licence: CC-BY-4.0

Contact points:

Resource Contact: FAO Statistics Division (ESS), Economic Statistics Team

Metadata Contact: FAO Statistics Division (ESS), Economic Statistics Team

Data lineage:

Source data

The main source is official statistics from FAO member countries. Exceptionally, unofficial data are also used as well as estimated/imputed data. In both cases this is "flagged". Data are recorded as countries report them, except for eliminating obvious errors. The source data can originate from surveys, administrative data and estimates based on expert observations. Which type of source is used by countries affect significantly reliability and comparability of data..

Data collection method: Sample surveys are generally used but there are also cases where administrative records are used, see further country specific metadata.

Base period: N.a.

More information on data validation, imputation, regional aggregation, use of statistical classifications, data revision policies and practices are provided in the FAOSTAT metadata.

Resource constraints:

User access: In line with FAO's Statistics Code of Practice data are disseminated on FAO's website respecting professional independence and in an objective, professional and transparent manner in which all users are treated equitably. Terms of use:. This work is made available under the Creative Commons Attribution 4.0 International license. In addition to this license, some database specific terms of use are listed: Terms of Use of Datasets.

Online resources:

Download data from FAOSTAT

FAOSTAT metadata source

This dataset is a polygon coverage of counties limited to the extent of the Upper Freeport coal bed resource areas and attributed with statistics on these coal quality parameters: ash yield (percent), sulfur (percent), SO2 (lbs per million Btu), calorific value (Btu/lb), arsenic (ppm) content and mercury (ppm) content. The file has been generalized from detailed geologic coverages found elsewhere in Professional Paper 1625-C. The attributes were generated from public data found in the geochemical dataset found in Chap. D, Appendix 8, Disc 1, as well as some additional proprietary data. Please see the metadata file found in Chap. D, Appendix 9, Disc 1, for more detailed information on the geochemical attributes. The county statistical data used for this data set are found in Tables 2-5 and 17-18, Chap. D, Disc 1. Additional county geochemical statistics for other parameters are found in Tables 6-16, Chap. D, Disc 1.

Statistics Canada, in collaboration with the Public Health Agency of Canada and Natural Resources Canada, is presenting selected Census data to help inform Canadians on the public health risk of the COVID-19 pandemic and to be used for modelling analysis. The data provided here show the counts of the population in nursing homes and/or residences for senior citizens by broad age groups (0 to 79 years and 80 years and over) and sex, from the 2016 Census. Nursing homes and/or residences for senior citizens are facilities for elderly residents that provide accommodations with health care services or personal support or assisted living care. Health care services include professional health monitoring and skilled nursing care and supervision 24 hours a day, 7 days a week, for people who are not independent in most activities of daily living. Support or assisted living care services include meals, housekeeping, laundry, medication supervision, assistance in bathing or dressing, etc., for people who are independent in most activities of daily living. Included are nursing homes, residences for senior citizens, and facilities that are a mix of both a nursing home and a residence for senior citizens. Excluded are facilities licensed as hospitals, and facilities that do not provide any services (which are considered private dwellings).

This dataset is a polygon coverage of counties limited to the extent of the Pocahontas No. 3 coal bed resource areas and attributed with statistics on these coal quality parameters: ash yield (percent), sulfur (percent), SO2 (lbs per million Btu), calorific value (Btu/lb), arsenic (ppm) content and mercury (ppm) content. The file has been generalized from detailed geologic coverages found elsewhere in Professional Paper 1625-C. The attributes were generated from public data found in the geochemical dataset found in Chap. H, Appendix 2, Disc 1. Please see the metadata file found in Chap. H, Appendix 3, Disc 1, for more detailed information on the geochemical attributes. The county statistical data used for this data set are found in Tables 6-9 and 21-22 in Chap. H, Disc 1. Additional county geochemical statistics for other parameters are found in Tables 10-20, Chap. H, Disc 1.

This dataset is a polygon coverage of counties limited to the extent of the Upper Freeport coal bed resource areas and attributed with statistics on the thickness of the Upper Freeport coal bed, its elevation, and overburden thickness, in feet. The file has been generalized from detailed geologic coverages found elsewhere in Professional Paper 1625-C.