This table presents data on first-time kindergartners' approaches to learning, interpersonal skills, and self-control scale scores, by selected child, family, and school characteristics: Fall 2010, spring 2011, spring 2012, and spring 2013. __Connected to SDG indicator 4.2.1 - Proportion of children under 5 years of age who are developmentally on track in health, learning and psychosocial well-being, by sex__ Internet Archive URL: https://web.archive.org/web/2017*/https://nces.ed.gov/programs/digest/d15/tables/dt15_220.45.asp?current=yes

Colleges and Universities in the United StatesThis feature layer, utilizing data from Homeland Infrastructure Foundation-Level Data (HIFLD), displays colleges and universities in the U.S. and its territories. According to HIFLD, this feature layer "is composed of all Post Secondary Education facilities as defined by the Integrated Post Secondary Education System (IPEDS, https://nces.ed.gov/ipeds/), National Center for Education Statistics (NCES, https://nces.ed.gov/), US Department of Education for the 2019-2020 school year. Included are Doctoral/Research Universities, Masters Colleges and Universities, Baccalaureate Colleges, Associates Colleges, Theological seminaries, Medical Schools and other health care professions, Schools of engineering and technology, business and management, art, music, design, Law schools, Teachers colleges, Tribal colleges, and other specialized institutions."Washington and Lee University & Virginia Military InstituteData currency: This cached Esri service is checked monthly for updates from its source (Colleges and Universities).Data modification: noneFor more information: U.S. Department of Education; National Center for Education Statistics; Integrated Postsecondary Education Data SystemFor feedback, please contact: ArcGIScomNationalMaps@esri.comHomeland Infrastructure Foundation-Level Data (HIFLD)Per HIFLD, "The Homeland Infrastructure Foundation-Level Data (HIFLD) Subcommittee was established…to address improvements in collection, processing, sharing, and protection of homeland infrastructure geospatial information across multiple levels of government, and to develop a common foundation of homeland infrastructure data to be used for visualization and analysis on all classification domains."

Transport for NSW provides projections of employment at the small area (Travel Zone or TZ) level for NSW. The latest version is Travel Zone Projections 2022 (TZP22), released November 2022. This new version TZP22 is an update on the previously published [TZP19](https://opendata.transport.nsw.gov.au/dataset/employment-projections/resource/77e880c1-0073-42bd-850a-ddf974e26cd6) and aligns with the [NSW Government Common Planning Assumptions](https://www.treasury.nsw.gov.au/information-public-entities/common-planning-assumptions). TZP22 Employment Projections are for employed persons by place of work. They are provided by Industry using two breakdowns: * 33 industry categories (equivalent to the ABS 1-digit Australia and New Zealand Standard Industrial Classification (ANZSIC) codes with the exception of Manufacturing which is at 2-digit level). * 4 Broad Industry Categories (groupings of the above) The projections in this release, TZP22 are presented annually 2016 to 2026 and five-yearly from 2026 to 2066 and are in TZ16 geography. Please note, TZP22 is based on best available data as at early to mid 2022. It includes the impacts from the Covid-19 pandemic and does not include results from the ABS 2021 Census as the relevant data had not been released at the time of TZP22 production. **Key Data Inputs used:** * TZP22 Workforce Projections * Census Journey to Work 2016 dataset by Destination Zone - ABS * State-level Employment projections – NSW Treasury * Employment by industry projections - Victoria University * Future Employment Development Database (FEDD) - a custom dataset compiled by TfNSW in late 2019 and updated in mid-2022, that presents the number of jobs expected from major projects based on publicly available documents. For a summary of the TZP22 Projections method please refer to the [TZP22 Factsheet](https://opendata.transport.nsw.gov.au/dataset/employment-projections/resource/cabdece8-98a2-4004-b2bc-30e4d153a2da) For more detail on the projection process please refer to the [TZP22 Technical Guide](https://opendata.transport.nsw.gov.au/dataset/employment-projections/resource/ca2fcd4d-fcaf-412a-b761-e5c86af6f570) Additional land use information for [population](https://opendata.transport.nsw.gov.au/dataset/population-projections) and [workforce](https://opendata.transport.nsw.gov.au/dataset/workforce-projections) as well as [Travel Zone boundaries for NSW](https://opendata.transport.nsw.gov.au/dataset/travel-zones-2016) are also available for download on the Open Data Hub. A visualisation of the employment projections is available on the Transport for NSW Website under [Reference Information.](https://www.transport.nsw.gov.au/data-and-research/reference-information/travel-zone-explorer-visualisation) **Cautions** The TZP22 dataset represents one view of the future aligned with the NSW Government Common Planning Assumptions and population and economic projections. The projections are not based on specific assumptions about future new transport infrastructure, but do take into account known land-use developments underway or planned, and strategic plans. * TZP22 is a strategic state-wide dataset and caution should be exercised when considering results at detailed breakdowns. * The TZP22 outputs represent a point in time set of projections (as at early to mid 2022). * The projections are not government targets. * Travel Zone (TZ) level outputs are projections only and should be used as a guide. As with all small area data, aggregating of travel zone projections to higher geographies leads to more robust results. * As a general rule, TZ-level projections are illustrative of a possible future only. * More specific advice about data reliability for the specific variables projected is provided in the “Read Me” page of the Excel format summary spreadsheets on the TfNSW Open Data Hub. * Caution is advised when comparing TZP22 with the previous set of projections (TZP19) due to addition of new data sources for the most recent years, and adjustments to methodology. **Further cautions and notes can be found in the TZP22 Technical Guide.**

Data from the National Center for Eduction Statistics. Table 220.40: Fall 2010 first-time kindergartners' reading, mathematics, and science scale scores, by selected child, family, and school characteristics: Fall 2010, spring 2011, spring 2012, and spring 2013 SDG indicator 4.2.1 - Proportion of children under 5 years of age who are developmentally on track in health, learning and psychosocial well-being, by sex. Source: Early Childhood Longitudinal Study, Kindergarten Class of 2010-11 (ECLS-K:2011). Internet Archive URL: https://web.archive.org/web/2017*/http://nces.ed.gov/programs/digest/d15/tables/dt15_220.40.asp?current=yes

The mission of FNS is to provide children and needy families better access to food and a more healthful diet through its food assistance programs and comprehensive nutrition education efforts. These dataset provides a summary of all the FNS School Food Program combined into one dataset. It contains cash payments and commodity costs for the National School Lunch Program, School Breakfast Program and the Special Milk Program. (format: html, xls)

Global Precipitation Measurement Core Observatory Educational Poster Includes satellite mission overview and classroom activities about global precipitation patterns and satellite data.

Explore Saudi Arabia's government final consumption expenditure dataset with detailed information on sectors such as education, health, defense, and more. Gain insights into the country's social service spending and economic services. Other Community & Social Services, Education, Other Purposes, Economic Services, Social Security & Welfare Services, Total, Housing & Community Amenities, Defence, Health, General Public Service, housing, education, health, Defence, social, service, economic, SAMA Annual Saudi Arabia Follow data.kapsarc.org for timely data to advance energy economics research..2020: Provisional 

HE providers currently submit an annual data return with information about their estates. The data relates to the academic year 1 August to 31 July and is submitted in the winter following the end of the academic year. We quality assure and process the data which we then publish in the following spring/summer. Published tables cover buildings and spaces, energy, emissions and waste, transport and environment, and finances and people.

Most intense, most fatal and most damaging global earthquakes from 2150 BCE to present. This layer represents earthquakes with at least one of the following criteria: Magnitude 8.5 or greater Modified Mercalli Intensity XI or XII 1,001 or more fatalities $25 million or more in damage Data source: National Geophysical Data Center / World Data Service (NGDC/WDS): Significant Earthquake Database. National Geophysical Data Center, NOAA. doi:10.7289/V5TD9V7K

A schematic of stratigraphic column of the marcellus shale with basic information about the fracking process. It is simple, but good reference for people who are new to hydraulic fracturing technology and research.

The Children's Environmental Health Initiative (CEHI) at Rice University provided access to blood lead data from the North Carolina Childhood Lead Poisoning Prevention Program surveillance registry; data on end-of-grade standardized achievement tests in reading and mathematics from the North Carolina Education Research Data Center (NCERDC); and birth certificate data from the North Carolina Department of Health and Human Services. Test score, blood lead, and birth certificate data were linked using a common child identifier created by CEHI for matching purposes. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: The data was made available by the Children's Environmental Health Initiative (CEHI) at Rice University. Contact Claire Osgood (ceo1@rice.edu), CEHI's Data Manager, to learn how the data can be accessed. Format: The Children's Environmental Health Initiative (CEHI) at Rice University provided access to blood lead data from the North Carolina Childhood Lead Poisoning Prevention Program surveillance registry; data on end-of-grade standardized achievement tests in reading and mathematics from the North Carolina Education Research Data Center (NCERDC); and birth certificate data from the North Carolina Department of Health and Human Services. Test score, blood lead, and birth certificate data were linked using a common child identifier created by CEHI for matching purposes. Citation information for this dataset can be found in the EDG's Metadata Reference Information section and Data.gov's References section.

This table presents the percentage of 3-, 4-, and 5-year-old children enrolled in preprimary programs, by level of program, attendance status, and selected child and family characteristics: 2014. Preprimary programs include kindergarten and preschool (or nursery school) programs. __Connected to SDG indicator 4.2.2 - Participation rate in organized learning (one year before the official primary entry age), by sex__ Internet Archive URL: https://web.archive.org/web/2017*/https://nces.ed.gov/programs/digest/d15/tables/dt15_202.20.asp?current=yes

The PIAAC U.S. public use file contains individual unit record data including both responses to the background questionnaire and the cognitive assessment from the original U.S. PIAAC data collection completed in 2012. __ Connected to SDG indicator 4.6.1 - Percentage of population in a given age group achieving at least a fixed level of proficiency in functional (a) literacy and (b) numeracy skills, by sex __ Internet Archive URL: https://web.archive.org/web/2017*/https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2014045rev