Open Data Network

Hospital Cost Report Audited Data: 2012

This version of the Institutional Cost Report (ICR) has been audited by a Certified Public Accounting Firm. The ICR is a uniform report completed by New York State hospitals to report income, expenses, assets, liabilities, and statistics to the the Department of Health (DOH). Under DOH regulations, (Part 86-1.2), Article 28 hospitals are required to file financial and statistical data with DOH annually. The data filed is part of the ICR and is received electronically through a secured network. This data is used to develop Medicaid rates, assist in the formulation of reimbursement methodologies, and analyze trends. For more information, check out: http://www.health.ny.gov/facilities/hospital/index.htm.

2010 Bond Spending Summary - FY 2015 Q1

The table provides spending details on the City’s voter-approved bond programs. The information summarizes spending by fiscal year quarter starting with FY 13 Q3. Please see the Capital Planning Office website, www.austintexas.gov/cip, for more information about the City’s voter-approved bond programs. The fiscal year begins October 1 and ends September 30. The first fiscal quarter is October through December; the second quarter is January through March; the third fiscal quarter is April through June; and the fourth fiscal quarter is July through September. The following are definitions of terms used in the table. Allocated: The amount of funds designated by the City of Austin Budget Office to be spent per reporting category or proposition. Allocated funds are tied to bond sales, which must be performed in $5,000 increments. Appropriated: City Council authorizes the appropriation of funds, which gives staff the legal authority to expend the funds for a specific purpose. City Council may approve multiple installments of funding throughout the project’s phases. Available: The amount of funds allocated minus the amount encumbered and expended. Encumbered: Commitments made to unperformed contracts for goods or services. Expenditure: Funds that have been paid for goods or services.

WA-APCD Quality and Cost Summary Report: County Cost

WA-APCD - Washington All-Payer Claims Database The WA-APCD is the state’s most complete source of health care eligibility, medical claims, pharmacy claims, and dental claims insurance data. It contains claims from more than 50 data suppliers, spanning commercial, Medicaid, and Medicare managed care. The WA-APCD has historical claims data for five years (2013-2017), with ongoing refreshes scheduled quarterly. Workers' compensation data from the Washington Department of Labor & Industries will be added in fall 2018. Download the attachment for the data dictionary and more information about WA-APCD and the data.

MD iMAP: Maryland Protected Lands - Rural Legacy Properties

This is a MD iMAP hosted service. Find more information at http://imap.maryland.gov. In 1997 - the Maryland General Assembly approved the Rural Legacy Program as a major component of Governor Glendening's Smart Growth and Neighborhood Conservation Initiative. The purpose of the Rural Legacy Program is to protect Maryland's best remaining rural landscapes and natural areas through the purchase of land or conservation easements. Funds are awarded by grants to sponsors to purchase fee simple interests or easements on property within a Rural Legacy Area. This file consists of properties that have been protected using Rural Legacy funds. Last Updated: 12/9/2015Feature Service Link:http://geodata.md.gov/imap/rest/services/Environment/MD_ProtectedLands/FeatureServer/1 ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

Hospital Cost Report Edited Data: 2009

The Institutional Cost Report (ICR) is a uniform report completed by New York hospitals to report income, expenses, assets, liabilities, and statistics to the Department of Health (DOH). Under DOH regulations, (Part 86-1.2), Article 28 hospitals are required to file financial and statistical data with DOH annually. The data filed is part of the ICR and is received electronically through a secured network. This data is used to develop Medicaid rates, assist in the formulation of reimbursement methodologies, and analyze trends. The ICR is a comprehensive compilation of exhibits that have been modified over time that users should consider when using the ICR dataset. It is possible that data is updated subsequent to posting on this website; therefore the data could become obsolete. To get the details related to the exhibits and data elements, please refer to the blank ICR form, the ICR Table of Contents, the ICR Instructions and the Glossary of Terms, Acronyms, and Abbreviations which are in the Supporting Information section of this site. The data posted as edited contains desk edit adjustments by DOH personnel. In 2009, this information was not audited; however effective with the 2010 ICR, all ICRs will be audited by a Certified Public Accounting Firm annually.

Restaurant Licenses

Current Common Victualer (Restaurant), Alcohol, Motor Vehicle Reseller, Amusement, Coin Operated Devices, Pool Tables, Second Hand Goods, Hawker/Peddler licenses issued by the Inspectional Services department.

SAFARI 2000 Vegetation Cover Characteristics, Kalahari Transect, Wet Season 2000

Vegetation cover and composition, including species types and richness assessments, were measured at four locations along the Kalahari Transect in Botswana (Pandamatenga, Maun, Okwa River, and Tshane) during the SAFARI 2000 wet season field campaign. The sites visited showed interesting degrees of variability despite the apparent homogeneity of the Kalahari sands and predominantly semi-arid savanna shrub-woodlands vegetation cover (Ringrose et al., 2003).At each site, twelve individual locations were chosen by random stratified techniques within a 30-km radius at each location, based on differences in topography, soils, and known disturbance, to help determine local variability (Huennecke et al., 2001). Data collection methods were identical at each location (Ringrose et al., 1996; 1998): (1) identification and enumeration of all species along 3 x 90-m transects, spaced 45-m apart; (2) visual estimation (tape measure and pacing) of canopy diameter along each transect; and (3) visual estimation of percent live and dead herbaceous cover, litter, and bare soil using 3 x 50 m2 quadrats spaced at 30-m intervals along each transect. In addition, vegetation components were calculated for each site comprising woody vegetation cover, green herbaceous cover in terms of grass and forbs, dead herbaceous cover, plant litter, and bare soil. Species richness was calculated as the actual number of species per three transects (270 m2) at each site (Kent and Coker, 1996).The data set consists of two data files (ASCII tables) in comma-delimited format (.csv) with descriptive header records.

Nimbus-5 Electrically Scanning Microwave Radiometer (ESMR) Imagery of Brightness Temperature on 70 mm Film V001

The ESMRN5IM data product consists of daily brightness temperature images on 70-mm photofacsimile film. Each frame contains a geographic grid and two groups of three parallel strips of imagery, each containing one-half the orbital data. The spatial coverage is identical in each group, but each strip has a different dynamic range for its gray scale: 100-200 K, 190-270 K, and 250-300 K, respectively. The spatial resolution is 25 x 25 km near nadir, degrading to 160 km cross-track by 45 km down-track at the ends of the scan. The images are saved as JPEG 2000 digital files. About 2 weeks of images are archived into a TAR file. Additional information can be found in "The Nimbus 5 User's Guide." The primary objectives of the Nimbus 5 Electrically Scanning Microwave Radiometer (ESMR) were: (1) to derive the liquid water content of clouds from brightness temperatures over oceans, (2) to observe differences between sea ice and the open sea over the polar caps, and (3) to test the feasibility of inferring surface composition and soil moisture. To accomplish these objectives, the ESMR was capable of continuous global mapping of the 1.55-cm (19.36 GHz) microwave radiation emitted by the earth/atmosphere system, and could function even in the presence of cloud conditions that block conventional satellite infrared sensors. The ESMR experiment made measurements from Dec. 11, 1972 until May 16, 1977.These images can be used to supplement the radiance data files from the ESMRN5L2 data product.

Hawaii Farmer's Markets map

TRMM Precipitation Radar (PR) Level 2 Surface Cross-Section Product (TRMM Product 2A21) V7

The Tropical Rainfall Measuring Mission (TRMM) is a joint U.S.-Japan satellite mission to monitor tropical and subtropical precipitation and to estimate its associated latent heating. The primary objective of the 2A21 is to compute the path integrated attenuation (PIA), using the surface reference technique (SRT). The SRT relies on the assumption that the difference between the measurements of the normalized surface cross section within and outside the rain provides a measure of the PIA. Two types of non-rain surface cross section (sigma-zero) reference estimates are used: spatial and temporal. In the spatial surface reference data set, the mean and standard deviation of the surface cross sections are calculated over a running window of Ns fields of view before rain is encountered. These operations are performed separately for each of the 49+2 incidence angles of TRMM (corresponding to the cross-track scan from -17 degrees to + 17 degrees with respect to nadir). The two additional angle bins (making the total 51 rather than 49) are to account for non-zero pitch/roll angles that can shift the incidence angle with respect to nadir outside the normal range. For the temporal surface reference data set, the running mean and standard deviation are computed over a 1 degree x 1 degree (latitude, longitude) grid. Within each 1 degree x 1 degree grid cell, the data are further categorized into incidence angle categories (26). The number of observations in each category, Nt, are also recorded. Note that, for the temporal reference data set, no distinction is made between the port and starboard incidence angles. So, instead of 49 incidence angles, there are only 25 + 1, where the additional bin corresponds to angles greater than the normal range. When rain is encountered, the mean and standard deviations of the reference sigma-zero values are retrieved from the spatial and temporal surface reference data sets. To determine which reference measurement is to be used, the algorithm checks whether Nt >= Ntmin and Ns >= Nsmin, where Ntmin and Nsmin are the minimum number of samples that are needed to be considered a valid reference estimate for the temporal and spatial reference data sets, respectively. (Presently, Ntmin = 50 and Nsmin = 8). If neither condition is satisfied, no estimate of the PIA is made and the flags are set accordingly. If only one condition is met, then the surface reference data which corresponds to this is used. If both conditions are satisfied, the surface reference data is taken from that set which has the smaller standard deviation. If a valid surface reference data set exists (i.e., either Nt >= Ntmin or Ns >= Nsmin or both) then the 2-way path attenuation (PIA) is estimated from the equation: PIA = <sigma-zero(reference value)> - sigma-zero(in rain) where sigma-zero(in rain) is the value of the surface cross section over the rain volume of interest and <sigma-zero(reference value)> is the mean value obtained from either the temporal or spatial reference data sets, the choice of which depends on the considerations discussed above. To obtain information as to the reliability of this PIA estimate we consider the difference between the PIA, as derived in the above equation, and the standard deviation as calculated from the no-rain sigma-zero values and stored in the reference data set. Labeling this as std dev(reference value), then the reliability factor of the PIA estimate is obtained from: reliabFactor = PIA - std dev(reference value) When this quantity is large, the reliability is considered high and conversely. This is the basic...