This dataset is used to produce the School Performance Profile scores found at http://paschoolperformance.org. It is for School Year 2015. School Performance Profile scores are calculated for all open public schools in Pennsylvania. These include regular schools, charter schools, cyber charter schools, and full-time career and technical education centers. The scores reflect one of many indicators of a school’s academic performance.

The dataset provides at a location level, the number of funded Pennsylvania Pre-K Counts (PKC) and Head Start Supplemental Assistance Program (HSSAP) slots. The dataset begins in program year 2014-15 and will be updated quarterly to reflect the current program year funding.

This dataset contains information on the number of doses given for Naloxone throughout the Commonwealth of Pennsylvania by County. If the Incident County FIPS Code column is blank it means Not Recorded, as this field was blank by the Patient Care Report (PCR) vendor or the EMS Provider. Data is updated Quarterly starting with the first Quarter of Calendar Year 2018.

This data is pulled from the U.S. Census website. This data is for years Calendar Years 2009-2014.
Product: SAHIE File Layout Overview
Small Area Health Insurance Estimates Program - SAHIE
Filenames: SAHIE Text and SAHIE CSV files 2009 – 2014
Source: Small Area Health Insurance Estimates Program, U.S. Census Bureau.
Internet Release Date: May 2016
Description: Model‐based Small Area Health Insurance Estimates (SAHIE) for Counties and States File Layout and Definitions

The Small Area Health Insurance Estimates (SAHIE) program was created to develop model-based estimates of health insurance coverage for counties and states. This program builds on the work of the Small Area Income and Poverty Estimates (SAIPE) program. SAHIE is only source of single-year health insurance coverage estimates for all U.S. counties.

For 2008-2014, SAHIE publishes STATE and COUNTY estimates of population with and without health insurance coverage, along with measures of uncertainty, for the full cross-classification of:
•5 age categories: 0-64, 18-64, 21-64, 40-64, and 50-64

•3 sex categories: both sexes, male, and female

•6 income categories: all incomes, as well as income-to-poverty ratio (IPR) categories 0-138%, 0-200%, 0-250%, 0-400%, and 138-400% of the poverty threshold

•4 races/ethnicities (for states only): all races/ethnicities, White not Hispanic, Black not Hispanic, and Hispanic (any race).

In addition, estimates for age category 0-18 by the income categories listed above are published.

Each year’s estimates are adjusted so that, before rounding, the county estimates sum to their respective state totals and for key demographics the state estimates sum to the national ACS numbers insured and uninsured.

This program is partially funded by the Centers for Disease Control and Prevention's (CDC), National Breast and Cervical Cancer Early Detection ProgramLink to a non-federal Web site (NBCCEDP). The CDC have a congressional mandate to provide screening services for breast and cervical cancer to low-income, uninsured, and underserved women through the NBCCEDP. Most state NBCCEDP programs define low-income as 200 or 250 percent of the poverty threshold. Also included are IPR categories relevant to the Affordable Care Act (ACA). In 2014, the ACA will help families gain access to health care by allowing Medicaid to cover families with incomes less than or equal to 138 percent of the poverty line. Families with incomes above the level needed to qualify for Medicaid, but less than or equal to 400 percent of the poverty line can receive tax credits that will help them pay for health coverage in the new health insurance exchanges.

We welcome your feedback as we continue to research and improve our estimation methods. The SAHIE program's age model methodology and estimates have undergone internal U.S. Census Bureau review as well as external review. See the SAHIE Methodological Review page for more details and a summary of the comments and our response.

The SAHIE program models health insurance coverage by combining survey data from several sources, including:
•The American Community Survey (ACS)
•Demographic population estimates
•Aggregated federal tax returns
•Participation records for the Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamp program
•County Business Patterns
•Medicaid
•Children's Health Insurance Program (CHIP) participation records
•Census 2010

Margin of error (MOE). Some ACS products provide
an MOE instead of confidence intervals. An MOE is the
difference between an estimate and its upper or lower
confidence bounds. Confidence bounds can be created
by adding the margin of error to the estimate (for the
upper bound) and subtracting the margin of error from
the estimate (for the lower bound). All published ACS
margins of error are based on a 90-percent confidence
level.

The dataset describes a current state of mail ballot requests for the 2020 General Election. It’s a snapshot in time of the current volume of ballot requests across the Commonwealth.

State House boundaries within Pennsylvania attributed with names of legislators and party affiliations. Purpose: Public information and support for transportation planning, design and development. (2020-01)

Constraints: The user shall indemnify, save harmless, and, if requested, defend the COMMONWEALTH, their officers, agents, and employees from and against any suits, claims, or actions for injury, death, or property damage arising out of the use of or any defect in the FILES or any accompanying documentation.

The COMMONWEALTH excludes any and all implied warranties, including warranties or merchantability and fitness for a particular purpose.

The COMMONWEALTH makes no warranty or representation, either express or implied, with respect to the FILES or accompanying documentation, including its quality, performance, merchantability, or fitness for a particular purpose. The FILES and documentation are provided "as is" and the USER assumes the entire risk as to its quality and performance.

The COMMONWEALTH will not be liable for any direct, indirect, special, incidental, or consequential damages arising out of the use or inability to use the FILES or any accompanying documentation.

The USER is granted permission to translate and add value to the FILES for the use of the FILES on its computer hardware; provided, however, that the USER annually notify the UNIVERSITY / COMMONWEALTH of any customizing or value-adding work done.

Any customized or value added versions of the files will contain the following disclaimer:

THIS IS NOT A PENNSYLVANIA DEPARTMENT OF TRANSPORTATION APPROVED FILE. THE DEPARTMENT OF TRANSPORTATION RETAINS THE MASTER FILES.

THE USER AGREES AND UNDERSTANDS THAT IT MAY NOT FURTHER DISTRIBUTE THE FILES TO A THIRD PARTY.

This dataset contains summary information on opioid drug seizures and arrests made by Pennsylvania State Police (PSP) personnel, stationed statewide, on a quarterly basis. Every effort is made to collect and record all opioid drug seizures and arrests however, the information provided may not represent the totality of all seizures and opioid arrests made by PSP personnel.
Data is currently available from January 1, 2013 through most current data available.
Seizure
Opioids seized as a result of undercover buys, search warrants, traffic stops and other investigative encounters.
An incident is a Pennsylvania State Police (PSP) recorded violation of the Controlled Substance Act and an entry into the PSP Statistical Narcotics System.
By regulation, entry is made by the PSP as stated in PSP Administrative Regulation 9-6:
When violations of The Controlled Substance, Drug, Device and Cosmetic Act are reported, the required statistical information concerning the incident shall be entered into the Statistical Narcotic Reporting System (SNRS).
Incidents may include undercover buys, search warrants, traffic stops and other investigative encounters
So, an “incident” is not based on any arrest, but on a reported violation, though it often can include arrests.
The incidents that are selected and forwarded to the portal are those that include a record of one or more seizures of the opioid drugs. In turn, a subset of those selected incidents also contains a record of one or more arrests.
This is PSP data only, it would not include any Federal case/incident data.

This is a connection to the Dauphin County GIS Data Portal.
The following categories are available:
Boundaries
Election
Hydrology
Tax Assessment
Transportation
Elevation

The following Applications are available:
Mobile Parcel Viewer - provides the general public and other interested parties access to searchable and interactive information such as property tax and assessment information or the locations of water access points.

MDJ (Magisterial District Judges) Locator - Identifies Magisterial District Judge and Municipality

Dauphin County Homicides - Application showing Dauphin County homicides in 2015 and 2016

Parcel Viewer - Search for a Parcel, Property Information, Tax Assessment, Municipality, Assessed Land or Building Value, Acres, etc.

Digital Data is distributed as a countywide dataset in ESRI shapefile format. Aerial imagery is available as a countywide dataset either through Dauphin County GIS or downloaded from PA Spatial Data Access (PASDA also available on the Commonwealth Open Data portal)

The effects of the opioid epidemic on the criminal justice system are visible in arrests and convictions involving distribution of opioids and reported use of opioids among inmates entering state prisons. Tracking the number of arrests and convictions involving opioids provides a picture of the opioid epidemic across our counties and by age and gender. Likewise, the impact of the epidemic can be seen in the number of incarcerated people who report use of opioids.

View annual counts of Accidental or Undetermined overdose deaths for 2012 forward, including provisional estimates of annual counts of overdose deaths for recent years, as noted with an asterisk and the month the data was pulled.
NOTE: Finalized death records for overdose deaths are often delayed by 3-6 months. Counties labeled “no value” have data suppressed because the counts are between 1 and 9.

Overdose Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are identified using underlying cause-of-death codes X40–X44, and Y10–Y14, and include the following:

- R99 when the Injury Description indicates an overdose death.

- X49 when literal COD is Mixed or Combined or Multiple Substance Toxicity, as these are likely drug overdoses

- X47 when substance indicated is difluoroethane, alone or in combination with other drugs

Source Pennsylvania Prescription Drug Monitoring Program*

* These data were supplied by the Bureau of Health Statistics and Registries, Harrisburg, Pennsylvania. The Bureau of Health Statistics and Registries specifically disclaims responsibility for any analyses, interpretations or conclusions.

- Estimates are broken down by type of drugs involved in the overdose

- Any Drug Overdose Death - all drug overdose deaths, regardless of type of drug involved, excluding alcohol only deaths

- Opioid Overdose Death - any overdose death involving opioids, prescription or illegal