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The 2005-06 Private School Universe Survey (PSS 2005-06) is a study that is part of the Private School Universe program. PSS 2005-06 (http://nces.ed.gov/surveys/pss/) is a cross-sectional survey that collects data on private elementary and secondary schools, including religious orientation, level of school, length of school year, length of school day, total enrollment (K-12), race/ethnicity of students, number of high school graduates, number of teachers employed, program emphasis, and existence and type of kindergarten program. The study was conducted using mail questionnaires and telephone follow-up of all private schools in the United States. The PSS universe consists of a diverse population of schools. It includes both schools with a religious orientation (e.g., Catholic, Lutheran, or Jewish) and nonsectarian schools with programs ranging from regular to special emphasis and special education. The study�s unweighted and weighted response rates were both 94 percent. Key statistics produced from PSS 2005-06 are on the growth of religiously affiliated schools, the number of private high school graduates, the length of the school year for various private schools, and the number of private school students and teachers.

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Source: Behavioral Risk Factor Surveillance System (BRFSS), 2012.

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press release from DOJ on a director of university of South Carolina's center for Manufacturing and technology pleading guilty to fraud

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This coverage includes arcs, polygons, and polygon labels that describe the Total Petroleum System boundaries of the natural gas resources of Bangladesh. This resource assessment was completed jointly by the U.S. Geological Survey and Petrobangla.

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The purpose of this agreement is to assist the U.S. Department of Education in its obligation to ensure that applicants for student financial assistance under Title IV of the Higher Education Act of 1965, satisfy eligibility requirements. SSA will provide SSN verification and citizenship status as recorded in SSA records, and death indicators to ED.

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Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create the elevation data representing the terrain environment of a watershed and/or floodplain. Terrain data requirements allow for flexibility in the types of information provided as sources used to produce final terrain deliverables. Once this type of data is provided, FEMA will be able to account for the origins of the flood study elevation data. (Source: FEMA Guidelines and Specifications, Appendix N, Section N.1.2).

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The Hydrologic Sub-basins of Greenland data set contains Geographic Information System (GIS) polygon shapefiles that include 293 hydrologic sub-basins of the Greenland Ice Sheet, as created by Lewis and Smith (2009). Five km Digital Elevation Models (DEMs) of ice-surface and bedrock topography (Bamber et al. 2001) were used to estimate the hydraulic potentiometric surface for Greenland, which accounts for the effects of ice overburden pressure, such as hydrostatic pressure, surface topography, and underlying bedrock topography (Paterson 1994). Using the 5 km potentiometric grid, a modeled basin network for Greenland's ice sheet was created using the hydrological tools within ESRI ArcGIS (ArcInfo 9.2). Although the GIS initially generated more than 293 basins, basins less than 100 km2 in size, as well as basins located completely outside of the ice sheet extent, were removed from the data set. Data are available via FTP, and can be read in any GIS software. The following journal article provides documentation for this data set: Lewis, Sarah and Laurence Smith. 2009. Hydrologic Drainage of the Greenland Ice Sheet. Hydrological Processes DOI: 10.1002/hyp.7343. This journal article can be accessed from the Documentation link at the top of this Web page.

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The 2011 Toxics Release Inventory (TRI) dataset contains the most current TRI data available and reflects toxic chemical releases and pollution prevention activities that occurred at TRI facilities during the 2011 calendar year. You can use this dataset to find out what TRI-covered toxic chemicals are being produced and used at industrial facilities in your local area and how they are being managed. Please note that this dataset will change as the TRI Program continues to process TRI submissions. The TRI Program provides this dataset annually in late July to give the public an opportunity to see the most recent TRI information prior to the publication of the TRI National Analysis report in December. To view National Analysis reports from previous years, please consult TRI's archive of National Analysis data at http://www.epa.gov/tri/.

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The Disability Research File (DRF) contains ten years' worth of Title II and Title XVI disability information extracted from a wide variety of sources. Based on calendar-year cohorts of disability applications, the DRF contains claim outcomes at every adjudicative level as well as claim details for each of the approximately 2.5 million individual claims each year in that ten-year period.

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The U.S. Geological Survey developed this dataset as part of the Colorado Front Range Infrastructure Resources Project (FRIRP). One goal of the FRIRP was to provide information on the availability of those hydrogeologic resources that are either critical to maintaining infrastructure along the northern Front Range or that may become less available because of urban expansion in the northern Front Range. This dataset extends from the Boulder-Jefferson County line on the south, to the middle of Larimer and Weld Counties on the North. On the west, this dataset is bounded by the approximate mountain front of the Front Range of the Rocky Mountains; on the east, by an arbitrary north-south line extending through a point about 6.5 kilometers east of Greeley. This digital geospatial dataset consists of digitized contours of unconsolidated-sediment thickness (depth to bedrock).

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The Seismicity Catalog Collection is a compilation data on over four million earthquakes dating from 2150 BC to 1996 AD from NOAA's National Geophysical Data Center and U.S. Geological Survey's National Earthquake Information Center. The data include information on epicentral time of origin, location, magnitudes, depth and other earthquake-related parameters. This database is static and is no longer being updated.

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Contains information about the enumeration process.

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This data set includes soil temperature data from boreholes located at five stations in Russia: Yakutsk, Verkhoyansk, Pokrovsk, Isit', and Churapcha. The data have been compiled into five Microsoft Excel files, one for each station. Each Excel file contains three worksheets: G02189info worksheet: Contains the same content in each Excel file - lat/lon info and notes on the stations Jan soil & surface temp worksheet: Contains winter (January) soil temperature and air temperature (except for the Churapcha Excel file that only contains soil temperature - air temperature was not available) Jul soil & surface temp worksheet: Contains summer (July) soil temperature and air temperature (except for the Churapcha Excel file) There are two different versions of the Excel files: a complete version and a subsetted version. Both versions exist for each of the five stations for a total of 10 files. The complete versions of the files reside in the directory called complete and have the word full in their filename. These files contain borehole temperature data at all available standard depths: 0.2 m, 0.4 m, 0.6 m, 0.8 m, 1.2 m, 1.6 m, 2.0 m, 2.4 m, and 3.2 m. The subsetted versions of the files reside in the subset directory and have subset in their filename. These files contain data from the 0.8 m and 3.2 m depths only. Missing data are indicated by the value -999.0. The complete version is more applicable to scientific investigation. The subset version is provided for K-12 teachers and is featured in a classroom activity called "How Permanent is Permafrost?"We have included air temperature measured at these five stations when it is available. There are two sources for the surface air temperature data: NCAR World Monthly Surface Station Climatology, 1738-cont and NOAA Global Historical Climatology Network (GHCN) Monthly data set. These two sources both draw on the same single original source: data from the World Meteorological Organization (WMO) station network. The complete files have data from one or both sources, while the subset files only include data from the source with the most complete record.These data are being offered as is. NOAA@NSIDC believes these data to be of value but is unable to research and document these data as we do most data sets we publish.

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This map layer portrays the linear federally-owned land features (i.e., national parkways, wild and scenic rivers, etc.) of the United States, Puerto Rico, and the U.S. Virgin Islands. The map layer was created by extracting linear federal land features from the 1:2,000,000-scale individual State DLG files produced by the U.S. Geological Survey. These files were then merged into a single map layer. This is a revised version of the September 2005 map layer.

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<p>This research project is evaluating an innovative technique that uses fiber optic strain sensors to measure structural deformations and full field strains. An inverse finite element method (iFEM) analysis reconstructs a deformed structural shape based on the strain measurement data simulated by FEM analysis to represent the <em>in-situ</em> strain measurements. By mapping the iFEM displacement solution onto a full FEM model, without the applied loading, the complete fields of displacement, strain, and stress are reconstructed to a high degree of accuracy. This project supports the work on multiple flight research projects at NASA Armstrong.</p><p><strong>Work to date</strong>: The team has completed and validated a 1-dimensional beam element test using a compliant slider mechanism.</p><p><strong>Looking ahead</strong>: Future plans involve developing and validating the algorithm on a full size flight test article.</p><p><strong>Benefits</strong></p><ul><li><strong>Accurate</strong>: Algorithm is capable of accurate full-field structural shape and strain measurement</li><li><strong>Economical</strong>: Uses a minimum number of sensors to recreate the full-field structural deformations and strains</li><li><strong>Improves safety</strong>: Enables more efficient health monitoring of control surfaces and flexible structures</li></ul><p><strong>Applications</strong></p><ul><li>Aircraft wing flaps</li><li>Helicopter blades</li><li>Motor vehicles</li><li>Trains</li><li>Ships and submersibles</li><li>Wind turbines</li></ul>

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NSF's IT Policy Archive provides information on the general IT policies at NSF.

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The Remote Sensing Division is responsible for providing data to support the Coastal Mapping Program, Emergency Response efforts, and the Aeronautical Survey Program through the use of remotely sensed data. NOAA Coastal Mapping Remote Sensing Data includes metric-quality aerial photographs from film and digital cameras, orthomosaics, and Light Detection and Ranging (lidar). The predecessors to the Remote Sensing Division began using single-lens aerial photography in 1943. The single-lens and digital aerial photographs are maintained by the National Geodetic Survey. The applications include shoreline delineation, mapping water depths, topographic mapping, mapping seabed characteristics, locating features or obstructions to ensure the safety of marine and air navigation, and to support NOAA's homeland security and emergency response requirements. Orthomosaics and lidar data sets are available from the NOAA Office for Coastal Management's DigitalCoast. The National Geodetic Survey acquires remotely sensed data in the coastal realm including the Great Lakes and their connecting navigable waterways and select areas to support homeland security and emergency response.

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Chemical, physical and profile oceanographic data were collected aboard the CAPE HATTERAS in the Gulf of Mexico from 2010-09-04 to 2010-09-15 in response to the Deepwater Horizon Oil Spill event on April 20, 2010, by the Subsurface Monitoring Unit (SMU), which consisted of multiple government and corporate agencies. These data include CDOM fluorescence, conductivity, dissolved oxygen, fluorescence, hydrostatic pressure, salinity, sound velocity, temperature and water density. The instruments used to collect these data included CTD, fluorometer and oxygen meter along with other physical sampling devices. More specific information about each data set is located in their individual metadata records. The CTD data underwent preliminary quality assurance and control procedures at the National Coastal Data Development Center (NCDDC). Cruise level information consisting of data management documents, cruise reports and plans, videos and pictures, and other miscellaneous documentation were gathered by the data managers. (NODC Accession 0069059)

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The goal of this study was to predict the global distribution of plant rooting depths based on data about global aboveground vegetation structure and climate. Vertical root distributions influence the fluxes of water, carbon, and soil nutrients and the distribution and activities of soil fauna. Roots transport nutrients and water upwards, but they are also pathways for carbon and nutrient transport into deeper soil layers and for deep water infiltration. Roots also affect the weathering rates of soil minerals. For calculating such processes on a global scale, data on vertical root distributions are needed as inputs to global biogeochemistry and vegetation models. In the Project for Intercomparison of Land Surface Parameterization Schemes (PILPS), rooting depth and vertical soil characteristics were the most important factors explaining scatter for simulated transpiration among 14 land-surface models. Recently, the Terrestrial Observation Panel for Climate of the Global Climate Observation System (GCOS) identified the 95% rooting depth as a key variable needed to quantify the interactions between the climate, soil, and plants, stating that the main challenge was to find the correlation between rooting depth and soil and climate features (GCOS/GTOS Terrestrial Observation Panel for Climate 1997). In response to this challenge, a data set of vertical rooting depths was collected from the literature in order to construct maps of global ecosystem rooting depths.The parameters included in these data sets are estimates for the soil depths containing 50% and 95% of all roots, termed 50% and 95% rooting depths (D50 and D95, respectively). Together, these variables can be used to calculate estimates for vertical root distributions, using a logistic equation provided in this documentation. The data represent mean ecosystem rooting depths for 1 by 1 degree grid cells. Related data sets: The ORNL DAAC offers related data sets by Jackson et al. (2003), Gordon and Jackson (2003), Schenk and Jackson (2003), and Gill and Jackson (2003).This data set is one of the products of the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) data collection which contains 50 global time series data sets for the ten-year period 1986 to 1995. Selected data sets span even longer periods. ISLSCP II is a consistent collection of data sets that were compiled from existing data sources and algorithms, and were designed to satisfy the needs of modelers and investigators of the global carbon, water and energy cycle. The data were acquired from a number of U.S. and international agencies, universities, and institutions. The global data sets were mapped at consistent spatial (1, 0.5 and 0.25 degrees) and temporal (monthly, with meteorological data at finer (e.g., 3-hour)) resolutions and reformatted into a common ASCII format. The data and documentation have undergone two peer reviews.ISLSCP is one of several projects of Global Energy and Water Cycle Experiment (GEWEX) [http://www.gewex.org/] and has the lead role in addressing land-atmosphere interactions -- process modeling, data retrieval algorithms, field experiment design and execution, and the development of global data sets.

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This dataset is provided as an example of XML metadata that can be used to create a records in ServCat for GIS datasets.

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The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the Michigan South Stateplane projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at scales of 1:6,000, 1:12,000, and 1:24,000.

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Source for national data: National Occupant Protection Use Survey (NOPUS), 2012. Source for state data: State Observational Survey of Seat Belt Use, 2012.

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Apollo 11 Drive Tubes: Dissection and description by Judith H. Allton

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The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the State Plane projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12000.

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Collection of as much information as possible about the maritime world; the places and their activities within the maritime industry