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recreation - The Recreation category contains data, from across the Open Data Network™ of publishers, related to recreation, parks, art, boating, and libraries.

API
Nano Dust Analyzer Project
data.nasa.gov | Last Updated 2020-01-29T04:54:41.000Z
 We propose to develop a new highly sensitive instrument to confirm the existence of the so-called nano-dust particles, characterize their impact parameters, and measure their chemical composition. Simultaneous theoretical studies will be used to derive the expected&nbsp; mass and velocity ranges of these putative particles to formulate science and measurement requirements for the future deployment of&nbsp; the proposed Nano-Dust Analyzer (NDA)&nbsp; Early dust instruments onboard Pioneer 8 and 9 and Helios spacecraft detected a flow of submicron sized dust particles coming from the direction of the Sun. These particles originate in the inner solar system from mutual collisions among meteoroids and move on&nbsp; hyperbolic orbits that leave the Solar System under the prevailing radiation pressure force. Later dust instruments with higher&nbsp; sensitivity had to avoid looking toward the Sun because of interference from the solar wind and UV radiation and thus contributed&nbsp; little to the characterization of the dust stream. The one exception is the Ulysses dust detector that observed escaping dust particles&nbsp; high above the solar poles, which confirm the suspicion that charged nanometer sized dust grains are carried to high heliographic&nbsp; latitudes by electromagnetic interactions with the Interplanetary Magnetic Field (IMF). Recently, the STEREO WAVES instruments&nbsp; recorded a large number of intense electric field signals, which were interpreted as impacts from nanometer sized particles striking the&nbsp; spacecraft with velocities of about the solar wind speed. This high flux and strong spatial and/or temporal variations of nanometer&nbsp; sized dust grains at low latitude appears to be uncorrelated with the solar wind properties. This is a mystery as it would require that&nbsp; the total collisional meteoroid debris inside 1 AU is cast in nanometer sized fragments. The observed fluxes of inner-source pickup ions&nbsp; also point to the existence of a much enhanced dust population in the nanometer size range.&nbsp; This new heliospherical phenomenon of nano-dust streams may have consequences throughout the planetary system, but as of yet no dust instrument exists that could be used to shed light on their properties. &nbsp;We propose to develop a dust analyzer capable to detect and&nbsp; analyze these mysterious dust particles coming from the solar direction and to embark upon complementary theoretical studies to&nbsp; understand their characteristics. The instrument is based on the Cassini Dust Analyzer (CDA) that has analyzed the composition of&nbsp; nanometer sized dust particles emanating from the Jovian and Saturnian systems but could not be pointed towards the Sun. By&nbsp; applying technologies implemented in solar wind instruments and coronagraphs a highly sensitive dust analyzer will be developed and&nbsp; tested in the laboratory. The dust analyzer shall be able to characterize impact properties (impact charge and energy distribution of&nbsp; ions from which mass and speed of the impacting grains may be derived) and chemical composition of individual nanometer sized&nbsp; particles while exposed to solar wind and UV radiation. The measurements will enable us to identify the source of the dust by&nbsp; comparing their elemental composition with that of larger micrometeoroid particles of cometary and asteroid origin and will reveal&nbsp; interaction of nano-dust with the interplanetary medium by investigating the relation of the dust flux with solar wind and IMF&nbsp; properties.&nbsp; Complementary theoretically studies will be performed to understand the characteristics of nano-dust particles at 1 AU to answer the&nbsp; following questions:&nbsp; - What is the speed range at which nanometer sized particles impact
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Parks Stats
performance.franklintn.gov | Last Updated 2023-08-23T15:31:51.000Z
Data consisting of Parks and Recreation Statistics from Franklin, Tennessee - including parks acreage, Healthy City rankings, and Tree City USA.
API
Recreation & Parks Program Totals: Fall 2015 - Summer 2016
opendata.howardcountymd.gov | Last Updated 2018-12-10T14:53:26.000Z
Data encompasses the number of participants enrolled in Howard County Recreation & Parks programs (I.e. Sports, Fitness, Nature & Environment, Camps etc...), by Season.
API
Vital Signs: Time in Congestion - Corridor (Updated October 2018)
data.bayareametro.gov | Last Updated 2018-10-24T00:31:33.000Z
VITAL SIGNS INDICATOR Time Spent in Congestion (T7) FULL MEASURE NAME Time Spent in Congestion LAST UPDATED October 2018 DATA SOURCE MTC/Iteris Congestion Analysis No link available CA Department of Finance Forms E-8 and E-5 http://www.dof.ca.gov/Forecasting/Demographics/Estimates/E-8/ http://www.dof.ca.gov/Forecasting/Demographics/Estimates/E-5/ CA Employment Division Department: Labor Market Information http://www.labormarketinfo.edd.ca.gov/ CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Time spent in congestion measures the hours drivers are in congestion on freeway facilities based on traffic data. In recent years, data for the Bay Area comes from INRIX, a company that collects real-time traffic information from a variety of sources including mobile phone data and other GPS locator devices. The data provides traffic speed on the region’s highways. Using historical INRIX data (and similar internal datasets for some of the earlier years), MTC calculates an annual time series for vehicle hours spent in congestion in the Bay Area. Time spent in congestion is defined as the average daily hours spent in congestion on Tuesdays, Wednesdays and Thursdays during peak traffic months on freeway facilities. This indicator focuses on weekdays given that traffic congestion is generally greater on these days; this indicator does not capture traffic congestion on local streets due to data unavailability. This congestion indicator emphasizes recurring delay (as opposed to also including non-recurring delay), capturing the extent of delay caused by routine traffic volumes (rather than congestion caused by unusual circumstances). Recurring delay is identified by setting a threshold of consistent delay greater than 15 minutes on a specific freeway segment from vehicle speeds less than 35 mph. This definition is consistent with longstanding practices by MTC, Caltrans and the U.S. Department of Transportation as speeds less than 35 mph result in significantly less efficient traffic operations. 35 mph is the threshold at which vehicle throughput is greatest; speeds that are either greater than or less than 35 mph result in reduced vehicle throughput. This methodology focuses on the extra travel time experienced based on a differential between the congested speed and 35 mph, rather than the posted speed limit. To provide a mathematical example of how the indicator is calculated on a segment basis, when it comes to time spent in congestion, 1,000 vehicles traveling on a congested segment for a 1/4 hour (15 minutes) each, [1,000 vehicles x ¼ hour congestion per vehicle= 250 hours congestion], is equivalent to 100 vehicles traveling on a congested segment for 2.5 hours each, [100 vehicles x 2.5 hour congestion per vehicle = 250 hours congestion]. In this way, the measure captures the impacts of both slow speeds and heavy traffic volumes. MTC calculates two measures of delay – congested delay, or delay that occurs when speeds are below 35 miles per hour, and total delay, or delay that occurs when speeds are below the posted speed limit. To illustrate, if 1,000 vehicles are traveling at 30 miles per hour on a one mile long segment, this would represent 4.76 vehicle hours of congested delay [(1,000 vehicles x 1 mile / 30 miles per hour) - (1,000 vehicles x 1 mile / 35 miles per hour) = 33.33 vehicle hours – 28.57 vehicle hours = 4.76 vehicle hours]. Considering that the posted speed limit on the segment is 60 miles per hour, total delay would be calculated as 16.67 vehicle hours [(1,000 vehicles x 1 mile / 30 miles per hour) - (1,000 vehicles x 1 mile / 60 miles per hour) = 33.33 vehicle hours – 16.67 vehicle hours = 16.67 vehicle hours]. Data sources listed above were used to calculate per-capita and per-worker statistics. Top congested corridors are ranked by total vehicle hours of delay, meaning that the highlighted corridors reflect a combination of slow speeds and heavy t
API
State Park Facility Points with Playgrounds
data.ny.gov | Last Updated 2019-12-30T17:25:09.000Z
The New York State Office of Parks, Recreation and Historic Preservation (OPRHP) oversees more than 250 state parks, historic sites, recreational trails, golf courses, boat launches and more, encompassing nearly 350,000 acres, that are visited by 74 million people annually. These facilities contribute to the economic vitality and quality of life of local communities and directly support New York’s tourism industry. Parks also provide a place for families and children to be active and exercise, promoting healthy lifestyles. The agency is responsible for the operation and stewardship of the state park system as well as advancing a statewide parks, historic preservation, and open space mission.
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State Nature Centers
data.ny.gov | Last Updated 2020-12-07T23:14:16.000Z
The New York State Office of Parks, Recreation and Historic Preservation (OPRHP) oversees more than 250 state parks, historic sites, recreational trails, golf courses, boat launches and more, encompassing nearly 350,000 acres, that are visited by 74 million people annually. These facilities contribute to the economic vitality and quality of life of local communities and directly support New York’s tourism industry. Parks also provide a place for families and children to be active and exercise, promoting healthy lifestyles. The agency is responsible for the operation and stewardship of the state park system as well as advancing a statewide parks, historic preservation, and open space mission. The New York State Office of Parks, Recreation and Historic Preservation operates several nature centers throughout the state. Visitors to our nature centers learn about the abundance of natural resources to be found in state parks. Our state parks and historic sites are hosts to scenic viewsheds, geologic features and both common and rare flora and fauna. For more information, visit http://nysparks.com/environment/nature-centers/default.aspx
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State Park Trails
data.ny.gov | Last Updated 2024-04-24T19:08:18.000Z
The New York State Office of Parks, Recreation and Historic Preservation (OPRHP) oversees more than 250 state parks, historic sites, recreational trails, golf courses, boat launches and more, encompassing nearly 350,000 acres, that are visited by 74 million people annually. These facilities contribute to the economic vitality and quality of life of local communities and directly support New York’s tourism industry. Parks also provide a place for families and children to be active and exercise, promoting healthy lifestyles. The agency is responsible for the operation and stewardship of the state park system as well as advancing a statewide parks, historic preservation, and open space mission. This dataset is a shapefile of the mapped trails in NYS Parks.
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Car, Boat, and Snowmobile Dealerships Across NYS Map
data.ny.gov | Last Updated 2024-04-08T21:01:55.000Z
Data set containing information on the facilities licensed by DMV in accordance with Vehicle and Traffic Law.
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Queens Libraries (Map)
data.cityofnewyork.us | Last Updated 2023-12-13T02:09:57.000Z
Map of Queens Public Libraries with Hours and Locations
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E-Rate Open Competitive Bidding: Basic Information (FCC Form 470 and Related Information)
datahub.usac.org | Last Updated 2024-04-28T09:40:43.000Z
This dataset contains information from the basic information section of each FCC Form 470, including applicant details such as contact information, application number, Billed Entity Number (BEN), and funding year, and related information from the E-Rate Productivity Center (EPC).