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SBIR/STTR Programs
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:22:21.000Z<p>The NASA SBIR and STTR programs fund the research, development, and demonstration of innovative technologies that fulfill NASA needs as described in the annual Solicitations and have significant potential for successful commercialization. If you are a small business concern (SBC) with 500 or fewer employees or a non-profit RI such as a university or a research laboratory with ties to an SBC, then NASA encourages you to learn more about the SBIR and STTR programs as a potential source of seed funding for the development of your innovations.</p><p><strong>The SBIR and STTR programs have 3 phases</strong>:</p><ul><li><strong>Phase I</strong> is the opportunity to establish the scientific, technical, and commercial feasibility of the proposed innovation in fulfillment of NASA needs.</li><li><strong>Phase II</strong> is focused on the development, demonstration and delivery of the proposed innovation.</li></ul><p>The SBIR and STTR Phase I contracts last for 6 months with a maximum funding of $125,000, and Phase II contracts last for 24 months with a maximum funding of $750,000 - $1.5 million.</p><ul><li><strong>Phase III</strong> is the commercialization of innovative technologies, products, and services resulting from either a Phase I or Phase II contract. Phase III contracts are funded from sources other than the SBIR and STTR programs and may be awarded without further competition.</li></ul><p><strong>Opportunity for Continued Technology Development Post-Phase II</strong>:</p><p>The NASA SBIR/STTR Program currently has in place two initiatives for supporting its small business partners past the basic Phase I and Phase II elements of the program that emphasize opportunities for commercialization. Specifically, the NASA SBIR/STTR Program has the Phase II Enhancement (Phase II-E) and Phase II eXpanded (Phase II-X) contract options.&nbsp;</p><p><strong>Please review the links below to obtain more information on the SBIR/STTR programs.</strong></p><ul><li><strong><a target="_blank" href="http://sbir.gsfc.nasa.gov/sites/default/files/ParticipationGuide.pdf">Participation Guide</a></strong></li></ul><p>Provides an overview of the SBIR and STTR programs as implemented by NASA</p><ul><li><strong><a href="http://sbir.gsfc.nasa.gov/solicitations">Program Solicitations</a></strong></li></ul><p>Provides access to the annual SBIR/STTR Solicitations containing detailed information on the program eligibility requirements, proposal instructions and research topics and subtopics</p><ul><li><strong><a href="http://sbir.gsfc.nasa.gov/prg_sched_anncmnt">Schedule and Awards</a></strong></li></ul><p>Schedule and links for the SBIR/STTR solicitations and selection announcements</p><ul><li><strong><a href="http://sbir.gsfc.nasa.gov/content/additional-sources-assistance">Sources of Assistance</a></strong></li></ul><p>Federal and non-Federal sources of assistance for small business</p><ul><li><strong><a href="http://sbir.gsfc.nasa.gov/abstract_archives">Awarded Abstracts</a></strong></li></ul><p>Search our complete archive of awarded project abstracts to learn about what NASA has funded</p><ul><li><strong><a href="http://sbir.gsfc.nasa.gov/content/frequently-asked-questions">Frequently Asked Questions</a></strong></li></ul><p>&nbsp;Still have questions? Visit the program FAQs</p>
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2016 NYC School Survey
data.cityofnewyork.us | Last Updated 2022-05-09T22:24:23.000ZNew York City Department of Education 2016 School Survey. Every year, all parents, all teachers, and students in grades 6 - 12 take the NYC School Survey. The survey ranks among the largest surveys of any kind ever conducted nationally. Survey results provide insight into a school's learning environment and contribute a measure of diversification that goes beyond test scores on the Progress Report. NYC School Survey results contribute 10% - 15% of a school's Progress Report grade (the exact contribution to the Progress Report is dependant on school type). Survey questions assess the community's opinions on academic expectations, communication, engagement, and safety and respect. School leaders can use survey results to better understand their own school's strengths and target areas for improvement
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SBUV2/NOAA-11 Ozone (O3) Profile and Total Column Ozone Monthly L3 Global 5.0deg Lat Zones V1
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:54:41.000ZThe Solar Backscattered Ultra Violet (SBUV) from NOAA-11 Level-3 monthly zonal mean (MZM) product (SBUV2N11L3zm) is derived from the Level-2 retrieved ozone profiles. Ozone retrievals are generated from the v8.6 SBUV algorithm. A Level-3 MZM file computes zonal means covering 5 degree latitude bands for each calendar month. For this product there are 147 months of data from January 1989 through March 2001. There are a total of 36 latitudinal bands, 18 in each hemisphere. Profile data are provided at 21 layers from 1013.25, 639.318, 403.382,254.517, 160.589, 101.325,63.9317, 40.3382, 25.4517, 16.0589, 10.1325, 6.39317,4.03382, 2.54517, 1.60589, 1.01325,0.639317, 0.403382, 0.254517, 0.160589 and 0.101325 hPa (measured at bottom of layer). NOTE: Some profiles have 20 layers and do not report the top most layer. Mixing ratios are reported at 15 layers from 0.5, 0.7, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 7.0, 10.0, 15.0, 20.0, 30.0, 40.0 and 50.0 hPa (measured at middle of layer). The MZM product averages retrievals that meet the criteria for a good retrieval as determined by error flags in the Level 2 data. A good retrieval is defined as satisfying the following conditions: 1) Profile Error Flag = 0 or 1 (0 = good retrieval; 1 = solar zenith angle > 84 deg.) 2) Total Error Flags = 0, 1, 2 or 5 (0 = good retrieval; 1 = not used; 2 = solar zenith angle > 84 deg; large discrepancy between profile total and best total ozone) NOTE - Total error flag = 5 is anomalously applied at high latitudes and high solar zenith angle where B-Pair total ozone estimate is not as reliable as profile under these conditions. This error flag may be removed in future version of algorithm. The zonal means computed for each month are screened according to the following statistical criteria: 1) number of good retrievals for the month greater than or equal to 2/3 of the samples for a nominal month. 2) mean latitude of good retrievals less than or equal to 1 degree from center of latitude band. 3) mean time of good retrievals less than or equal to 4 days from center of month (i.e., day = 15)
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Population Exposure Estimates in Proximity to Nuclear Power Plants, Country-Level Aggregates
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:36:37.000ZThe Population Exposure Estimates in Proximity to Nuclear Power Plants, Country-Level Aggregates data set consists of country-level estimates of total, urban, and rural populations and land area, country-wide, that are in proximity to a nuclear power plant. This data set was created using a global data set of point locations of nuclear power plants, with buffer zones at 30km, 75km, 150km, 300km, 600km, and 1200km, and the Global Population Count Grid Time Series Estimates, Version 1 to estimate the population within each buffer zone for the years 1990, 2000, and 2010. Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) Land and Geographic Unit Area Grids were used to estimate land area within each buffer zone. The GRUMPv1 Urban Extents Grid was used to further delineate population and land area estimates within urban and rural areas. All grids used for population, land area, and urban mask were of 1 km (30 arc-second) resolution.
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RICAPS On-road Transportation Emissions roll-up
datahub.smcgov.org | Last Updated 2018-06-13T15:39:17.000ZData by city showing transportation contribution to greenhouse gas emissions in the County. This data is part of the Regionally Integrated Climate Action Planning Suite (RICAPS) program. The majority of cities used the “in-boundary” methodology that relies on data from the Highway Performance Monitoring System. The inventories for South San Francisco and Unincorporated County use the “origin-destination” methodology from that relies on data from Metropolitan Transportation Commission (MTC). So, directly comparing vehicle miles traveled (VMT) across all cities is not statistically possible. Each city in San Mateo County has the opportunity to develop its own Climate Action Plan (CAP) using tools developed by C/CAG in conjunction with DNV KEMA https://www.dnvgl.com/ and Hara. http://www.verisae.com/default.aspx. This project was funded by grants from the Bay Area Air Quality Management District (BAAQMD) and Pacific Gas and Electric Company (PG&E). Climate Action Plans developed from these tools will meet BAAQMD's California Environmental Quality Act (CEQA) guidelines for a Qualified Greenhouse Gas Reduction Strategy. For more information, please see the RICAPS site: http://www.smcenergywatch.com/progress_report.html
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Northern Hemisphere Snow Cover Monthly Statistics at 1 Degree Resolution V001 (NHSNOWM) at GES DISC
data.nasa.gov | Last Updated 2022-01-17T05:45:22.000ZThis product is Snow Cover Statistics. The dataset was prepared by Dr. Peter Romanov at Cooperative Institute for Climate Studies(CICS) of the University of Maryland for Northern Eurasia Earth Science Partnership Initiative (NEESPI) program. The product includes the monthly snow statistics (frequency of occurrence) for Northern Hemisphere at 1x1 degree spatial resolution. The dataset covers the time period from January 2000 to November 2014. Monthly data were derived from daily snow cover charts produced at NOAA/NESDIS within Interactive Multisensor Ice Mapping System (IMS).
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AtOrAboveProficient
datahub.smcgov.org | Last Updated 2016-08-30T23:34:30.000ZSTAR Third Grade Reading Scores as a Percentage of Economically Disadvantaged Students classified by the State of California Department of Education as being "At or Above Proficient" reading level for 2013 school year. Hillsborough Unified School District reported a third grade enrollment of 183 students, with 1 student tested. Test results cannot be reported due to identity protection requirements. Las Lomitas Elementary School District reported a third grade enrollment of 170 with 3 students tested. Test results cannot be reported due to identity protection requirements. Menlo Park City Elementary District reported a third grade enrollment of 352 with 6 students tested. Test results cannot be reported due to identity protection requirements. Portola Valley Elementary School District reported a third grade enrollment of 80 with 3 students tested. Test results cannot be reported due to identity protection requirements. Woodside School District reported a third grade enrollment of 51 with 2 students tested. Test results cannot be reported due to identity protection requirements.
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2011-2012 School Closure Discharge Reporting Ethnicity - School
data.cityofnewyork.us | Last Updated 2022-05-09T22:22:32.000ZIn June 2012, 7 New York City public schools closed for poor performance. This report provides data regarding students enrolled in these schools during the 2011-2012 school year, according to the guidelines set by Local Law 2011/043
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SBUV2/NOAA-16 Ozone (O3) Profile and Total Column Ozone 1 Month Zonal Mean L3 Global 5.0 degree Latitude Zones V1 (SBUV2N16L3zm) at GES DISC
data.nasa.gov | Last Updated 2022-01-17T05:51:01.000ZThe Solar Backscattered Ultraviolet (SBUV) from NOAA-16 Level-3 monthly zonal mean (MZM) product (SBUV2N16L3zm) is derived from the Level-2 retrieved ozone profiles. Ozone retrievals are generated from the v8.6 SBUV algorithm. A Level-3 MZM file computes zonal means covering 5 degree latitude bands for each calendar month. For this product there are 154 months of data from October 2000 through July 2013. There are a total of 36 latitudinal bands, 18 in each hemisphere. Profile data are provided at 21 layers from 1013.25, 639.318, 403.382,254.517, 160.589, 101.325,63.9317, 40.3382, 25.4517, 16.0589, 10.1325, 6.39317,4.03382, 2.54517, 1.60589, 1.01325,0.639317, 0.403382, 0.254517, 0.160589 and 0.101325 hPa (measured at bottom of layer). NOTE: Some profiles have 20 layers and do not report the top most layer. Mixing ratios are reported at 15 layers from 0.5, 0.7, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 7.0, 10.0, 15.0, 20.0, 30.0, 40.0 and 50.0 hPa (measured at middle of layer). The MZM product averages retrievals that meet the criteria for a good retrieval as determined by error flags in the Level 2 data. A good retrieval is defined as satisfying the following conditions: 1) Profile Error Flag = 0 or 1 (0 = good retrieval; 1 = solar zenith angle > 84 degrees). 2) Total Error Flags = 0, 1, 2 or 5 (0 = good retrieval; 1 = not used; 2 = solar zenith angle > 84 degrees; large discrepancy between profile total and best total ozone). NOTE - Total error flag = 5 is anomalously applied at high latitudes and high solar zenith angles where the B-Pair total ozone estimate is not as reliable as the ozone profile under these conditions. This error flag may be removed in future version of algorithm. The zonal means computed for each month are screened according to the following statistical criteria: 1) Number of good retrievals for the month greater than or equal to 2/3 of the samples for a nominal month. 2) Mean latitude of good retrievals less than or equal to 1 degree from center of latitude band. 3) Mean time of good retrievals less than or equal to 4 days from center of month (i.e., day = 15).
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Contribution to High Asia Runoff from Ice and Snow (CHARIS) Melt Model Output, 2001 - 2014, Version 1
data.nasa.gov | Last Updated 2022-01-17T05:15:59.000ZThis data set contains input and output data for temperature index (TI) model runs completed for the Contributions to High Asia Runoff from Ice and Snow (CHARIS) project at NSIDC in 2018 and 2019. The input data are the area of snow on land, snow on ice, and exposed glacier ice as well as surface air temperature. These inputs are used to model the volumes of melt runoff from the snow on land, snow on ice, and exposed glacier ice in certain areas of High Mountain Asia.