Note: Reporting of new COVID-19 Case Surveillance data will be discontinued July 1, 2024, to align with the process of removing SARS-CoV-2 infections (COVID-19 cases) from the list of nationally notifiable diseases. Although these data will continue to be publicly available, the dataset will no longer be updated.

Authorizations to collect certain public health data expired at the end of the U.S. public health emergency declaration on May 11, 2023. The following jurisdictions discontinued COVID-19 case notifications to CDC: Iowa (11/8/21), Kansas (5/12/23), Kentucky (1/1/24), Louisiana (10/31/23), New Hampshire (5/23/23), and Oklahoma (5/2/23). Please note that these jurisdictions will not routinely send new case data after the dates indicated. As of 7/13/23, case notifications from Oregon will only include pediatric cases resulting in death.

This case surveillance public use dataset has 12 elements for all COVID-19 cases shared with CDC and includes demographics, any exposure history, disease severity indicators and outcomes, presence of any underlying medical conditions and risk behaviors, and no geographic data.

CDC has three COVID-19 case surveillance datasets:

• COVID-19 Case Surveillance Public Use Data with Geography: Public use, patient-level dataset with clinical data (including symptoms), demographics, and county and state of residence. (19 data elements)
• COVID-19 Case Surveillance Public Use Data: Public use, patient-level dataset with clinical and symptom data and demographics, with no geographic data. (12 data elements)
• COVID-19 Case Surveillance Restricted Access Detailed Data: Restricted access, patient-level dataset with clinical and symptom data, demographics, and state and county of residence. Access requires a registration process and a data use agreement. (33 data elements)

• Data elements can be found on the COVID-19 case report form located at www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf.
• Data are considered provisional by CDC and are subject to change until the data are reconciled and verified with the state and territorial data providers.
• Some data cells are suppressed to protect individual privacy.
• The datasets will include all cases with the earliest date available in each record (date received by CDC or date related to illness/specimen collection) at least 14 days prior to the creation of the current datasets. This 14-day lag allows case reporting to be stabilized and ensures that time-dependent outcome data are accurately captured.
• Datasets are updated monthly.
• Datasets are created using CDC’s Policy on Public Health Research and Nonresearch Data Management and Access and include protections designed to protect individual privacy.
• For more information about data collection and reporting, please see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/about-us-cases-deaths.html.
• For more information about the COVID-19 case surveillance data, please see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/faq-surveillance.html
  

Overview

The COVID-19 case surveillance database includes individual-level data reported to U.S. states and aut

Note: Reporting of new COVID-19 Case Surveillance data will be discontinued July 1, 2024, to align with the process of removing SARS-CoV-2 infections (COVID-19 cases) from the list of nationally notifiable diseases. Although these data will continue to be publicly available, the dataset will no longer be updated.

Authorizations to collect certain public health data expired at the end of the U.S. public health emergency declaration on May 11, 2023. The following jurisdictions discontinued COVID-19 case notifications to CDC: Iowa (11/8/21), Kansas (5/12/23), Kentucky (1/1/24), Louisiana (10/31/23), New Hampshire (5/23/23), and Oklahoma (5/2/23). Please note that these jurisdictions will not routinely send new case data after the dates indicated. As of 7/13/23, case notifications from Oregon will only include pediatric cases resulting in death.

This case surveillance public use dataset has 19 elements for all COVID-19 cases shared with CDC and includes demographics, geography (county and state of residence), any exposure history, disease severity indicators and outcomes, and presence of any underlying medical conditions and risk behaviors.

Currently, CDC provides the public with three versions of COVID-19 case surveillance line-listed data: this 19 data element dataset with geography, a 12 data element public use dataset, and a 33 data element restricted access dataset.

The following apply to the public use datasets and the restricted access dataset:

• Data elements can be found on the COVID-19 case report form located at www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf.
• Data are considered provisional by CDC and are subject to change until the data are reconciled and verified with the state and territorial data providers.
• Some data are suppressed to protect individual privacy.
• Datasets will include all cases with the earliest date available in each record (date received by CDC or date related to illness/specimen collection) at least 14 days prior to the creation of the current datasets. This 14-day lag allows case reporting to be stabilized and ensure that time-dependent outcome data are accurately captured.
• Datasets are updated monthly.
• Datasets are created using CDC’s Policy on Public Health Research and Nonresearch Data Management and Access and include protections designed to protect individual privacy.
• For more information about data collection and reporting, please see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/about-us-cases-deaths.html.
• For more information about the COVID-19 case surveillance data, please see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/faq-surveillance.html
  

Overview

The COVID-19 case surveillance database includes individual-level data reported to U.S. states and autonomous reporting entities, including New York City and the District of Columbia (D.C.), as well as U.S. territories and affiliates. On April 5, 2020, COVID-19 was added to the Nationally Notifiable Condition List and classified as “immediately notifiable, urgent (within 24 hours)” by a Council of State and Territorial Epidemiologists (CSTE) Interim Position Statement (<a href="https://cdn.ymaws.com/www.cste.org/resource/resmgr/ps/positionstatement2020/Interim-20-ID-01_COVID

Abstract (en): In 2008, a group of uninsured low-income adults in Oregon was selected by lottery to be given the chance to apply for Medicaid. This lottery provides an opportunity to gauge the effects of expanding access to public health insurance on the health care use, financial strain, and health of low-income adults using a randomized controlled design. The Oregon Health Insurance Experiment follows and compares those selected in the lottery (treatment group) with those not selected (control group). The data collected and provided here include data from in-person interviews, three mail surveys, emergency department records, and administrative records on Medicaid enrollment, the initial lottery sign-up list, welfare benefits, and mortality. This data collection has seven data files: Dataset 1 contains administrative data on the lottery from the state of Oregon. These data include demographic characteristics that were recorded when individuals signed up for the lottery, date of lottery draw, and information on who was selected for the lottery, applied for the lotteried Medicaid plan if selected, and whose application for the lotteried plan was approved. Also included are Oregon mortality data for 2008 and 2009. Dataset 2 contains information from the state of Oregon on the individuals' participation in Medicaid, Supplemental Nutrition Assistance Program (SNAP), and Temporary Assistance to Needy Families (TANF). Datasets 3-5 contain the data from the initial, six month, and 12 month mail surveys, respectively. Topics covered by the surveys include demographic characteristics; health insurance, access to health care and health care utilization; health care needs, experiences, and costs; overall health status and changes in health; and depression and medical conditions and use of medications to treat them. Dataset 6 contains an analysis subset of the variables from the in-person interviews. Topics covered by the survey questionnaire include overall health, health insurance coverage, health care access, health care utilization, conditions and treatments, health behaviors, medical and dental costs, and demographic characteristics. The interviewers also obtained blood pressure and anthropometric measurements and collected dried blood spots to measure levels of cholesterol, glycated hemoglobin and C-reactive protein. Dataset 7 contains an analysis subset of the variables the study obtained for all emergency department (ED) visits to twelve hospitals in the Portland area during 2007-2009. These variables capture total hospital costs, ED costs, and the number of ED visits categorized by time of the visit (daytime weekday or nighttime and weekends), necessity of the visit (emergent, ED care needed, non-preventable; emergent, ED care needed, preventable; emergent, primary care treatable), ambulatory case sensitive status, whether or not the patient was hospitalized, and the reason for the visit (e.g., injury, abdominal pain, chest pain, headache, and mental disorders). The collection also includes a ZIP archive (Dataset 8) with Stata programs that replicate analyses reported in three articles by the principal investigators and others: Finkelstein, Amy et al "The Oregon Health Insurance Experiment: Evidence from the First Year". The Quarterly Journal of Economics. August 2012. Vol 127(3). Baicker, Katherine et al "The Oregon Experiment - Effects of Medicaid on Clinical Outcomes". New England Journal of Medicine. 2 May 2013. Vol 368(18). Taubman, Sarah et al "Medicaid Increases Emergency Department Use: Evidence from Oregon's Health Insurance Experiment". Science. 2 Jan 2014. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes.. Presence of Common Scales: Patient Health Questionnaire-9 (PHQ-9) Total Severity Score SF-8 Health Survey Physical Component Score SF-8 Health Survey Mental Component Score Framingham Risk Score Response Rates: For the mail surveys, the response rates were 45 percent for the initial survey, 49 percent for the six month survey, and 41 percent for the 12 month survey. For the in-person survey the response rate was 59 percent. The individu...

Channel migration is the natural process by which streams move laterally over time. It is typically a gradual phenomenon that works over many years to effect significant migration. In some cases, usually associated with flood events, significant migration can happen rapidly. Channel migration can and has created hazardous conditions within Oregon’s developed riparian areas. Areas of high susceptibility to rapid and potentially catastrophic migration are known anecdotally, but statewide susceptibility screening has not been performed. This dataset represents a screening of channel migration susceptibility for the primary and (if applicable) secondary drainage in each subbasin (HUC-8) that intersects with the State of Oregon.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national filewith no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independentdata set, or they can be combined to cover the entire nation. Linear Water Features includes single-line drainage water features and artificial path features that run through double-line drainage features such as rivers and streams, and serve as a linear representation of these features. The artificial path features may correspond to those in the USGS National Hydrographic Dataset (NHD). However, in many cases the features do not match NHD equivalent feature and will not carry the NHD metadata codes. These features have a MAF/TIGER Feature Classification Code (MTFCC) beginning with an "H" to indicate the super class of Hydrographic Features.

About this dataset

Context

The dataset tabulates the Oregon population by race and ethnicity. The dataset can be utilized to understand the racial distribution of Oregon.

Content

The dataset will have the following datasets when applicable

Please note that in case when either of Hispanic or Non-Hispanic population doesnt exist, the respective dataset will not be available (as there will not be a population subset applicable for the same)

• Oregon, OH Population Breakdown by Race
• Oregon, OH Non-Hispanic Population Breakdown by Race
• Oregon, OH Hispanic or Latino Population Distribution by Their Ancestries

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

State Government Buildings in Oregon. This dataset is comprised of buildings or properties that are owned or leased by state level governments. It includes buildings occupied by the headquarters of cabinet level state government executive departments, legislative office buildings outside of the capitol building, offices and court rooms associated with the highest level of the judicial branch of the state government, and large multi-agency state office buildings. Because the research to create this dataset was primarily keyed off of the headquarters of cabinet level state government agencies, some state office buildings that don't house a headquarters for such an agency may have been excluded. Intentionally excluded from this dataset are government run institutions (e.g., schools, colleges, prisons, and libraries). Also excluded are state capitol buildings, as these entities are represented in other HSIP layers. State owned or leased buildings whose primary purpose is not to house state offices have also been intentionally excluded from this dataset. Examples of these include "Salt Domes", "Park Shelters", and "Highway Garages". All entities that have been verified to have no building name have had their [NAME] value set to "NO NAME". If the record in the original source data had no building name and TGS was unable to verify the building name, the [NAME] value was set to "UNKNOWN". All phone numbers in this dataset have been verified by TGS to be the main phone for the building. If the building was verified not to have a main phone number, the [TELEPHONE] field has been left blank. At the request of NGA, text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. At the request of NGA, all diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record dates from 11/27/2007 and the newest record dates from 05/28/2008.

After over two years of public reporting, the State Profile Report will no longer be produced and distributed after February 2023. The final release was on February 23, 2023. We want to thank everyone who contributed to the design, production, and review of this report and we hope that it provided insight into the data trends throughout the COVID-19 pandemic. Data about COVID-19 will continue to be updated at CDC’s COVID Data Tracker.

The State Profile Report (SPR) is generated by the Data Strategy and Execution Workgroup in the Joint Coordination Cell, in collaboration with the White House. It is managed by an interagency team with representatives from multiple agencies and offices (including the United States Department of Health and Human Services (HHS), the Centers for Disease Control and Prevention, the HHS Assistant Secretary for Preparedness and Response, and the Indian Health Service). The SPR provides easily interpretable information on key indicators for each state, down to the county level.

It is a weekly snapshot in time that:

• Focuses on recent outcomes in the last seven days and changes relative to the month prior
• Provides additional contextual information at the county level for each state, and includes national level information
• Supports rapid visual interpretation of results with color thresholds

This dataset is the City of Bend Police Department Case Offenses GIS layer curated for public use. Data is exported nightly from County E911 and ingested into City databases for both internal and external use.Please note data is updated nightly and reflects cases received as of 6 PM the previous day.Attribute Information: See Table Field Name Description

OBJECTID For internal use.

CaseNumber A unique identifier that corresponds to a call for service number. Case numbers with a “91” after the dash indicate they originated as an online report submitted via bendpolicereports.com (i.e. 2021-91001234). The first four numbers of a case number are the year the case was created.

ReportedDate This is the date and time the incident was reported to Deschutes County 911 or initiated by a Bend Police officer.

Day of Week Day of the week the case was reported.

CrimeCode Description of an offense as assigned by Oregon National Incident-Based Reporting System (O-NIBRS). One or more offense codes may be applied to each case report to identify which offenses occurred during the incident. In some instances, no codes are applied to a case report if the intent is to only document information; such instances will appear as “Case Report Only / No Crime Codes” in any tables.

CrimeCodeDesc Crime code description, based on the grouping of statutes as defined by Oregon Criminal Justice Information Services (CJIS) Division and National Incident-Base Reporting System (NIBRS). Full definitions available on the State of Oregon CJIS Uniform Crime Reporting Reference Materials website.

Statute Oregon Revised Statutes (ORS) applied to the case report. ORS are the codified laws of the State of Oregon. Full statute definitions are available on the State of Oregon website.

StatuteDesc Description of the listed ORS. Full statute definitions are available on the State of Oregon website.

Counts The number of offenses reported in an incident.

AttemptCode Indicates whether the reported offense was attempted or committed.

CaseAddress The address where the incident occurred, rounded to the hundred block for privacy. Occasionally, reporting parties or involved subjects may not be able to provide the exact location where the reported incident occurred, a non-verifiable address is provided, or the crime may have occurred in a location outside Deschutes County. In these instances, the location field will say “address not verified or outside jurisdiction.”

Neighborhood City of Bend neighborhood in which an offense occurred. For questions regarding individual cases or incidents, you can request records from the Bend Police Department here: https://www.bendoregon.gov/government/departments/police/records-division or you can send an email to police@bendoregon.gov

Note: Authorizations to collect certain public health data expired at the end of the U.S. public health emergency declaration on May 11, 2023. The following jurisdictions discontinued COVID-19 case notifications to CDC: Iowa (11/8/21), Kansas (5/12/23), Louisiana (10/31/23), New Hampshire (5/23/23), and Oklahoma (5/2/23). Please note that these jurisdictions will not routinely send new case data after the dates indicated. As of 7/13/23, case notifications from Oregon will only include pediatric cases resulting in death.

This table summarizes COVID-19 case and death data submitted to CDC as case reports for the line-level dataset. Case and death counts are stratified according to sex, age, and race and ethnicity at regional and national levels. Data for US territories are included in case and death counts, but not population counts. Weekly cumulative counts with five or fewer cases or deaths are not reported to protect confidentiality of patients. Records with unknown or missing sex, age, or race and ethnicity and of multiple, non-Hispanic race and ethnicity are included in case and death totals. COVID-19 case and death data are provisional and are subject to change. Visualization of COVID-19 case and death rate trends by demographic variables may be viewed on COVID Data Tracker (https://covid.cdc.gov/covid-data-tracker/#demographicsovertime).

The Department’s role is to protect existing water rights by preventing excessive groundwater declines, restoring aquifer stability, and preserving aquifers with limited storage capacity for designated high public value uses. The Department has several administrative tools for the management of the state's groundwater resources. New uses of groundwater may be restrictively classified within the basin programs. Unappropriated groundwater may be withdrawn from further appropriation by an order of the Water Resources Commission. A critical groundwater area boundary may be established by rule and restrictions to existing groundwater uses within the critical area may be designated by a contested case hearing and order of the commission.There are 14 areas in Oregon in which groundwater has been restrictively classified. The limitations to new groundwater uses are listed in the pertinent basin programs. The Fort Rock area is within the Goose and Summer Lakes Basin (OAR 690-513). The Ella Butte area is within the Umatilla Basin (OAR 690-507). There are 12 such areas, known as groundwater limited areas, in the northern Willamette Valley, including both the Willamette and Sandy basins (OAR 690-502 & OAR 690-503). These areas are in the following approximate locations: Sandy-Boring, Damascus, Gladtidings, Kingston, Mt. Angel, Sherwood-Dammasch-Wilsonville, Stayton-Sublimity, Parrett Mountain, Chehalem Mountain, Eola Hills, South Salem Hills, and Amity Hills-Walnut Hill.There are seven critical groundwater areas in Oregon. Four of these, the Ordnance Gravel Critical Groundwater Area, Ordnance Basalt Critical Groundwater Area, Butter Creek Critical Groundwater Area and Stage Gulch Critical Groundwater Area, are all within the Umatilla Basin. The Cow Valley Critical Groundwater Area is in the Malheur Basin. The Dalles Critical Groundwater Area is in the Hood Basin. The Cooper-Bull Mountain Critical Groundwater Area is in the Willamette Basin.There are two areas in Oregon for which the commission has issued orders withdrawing specific aquifers from further appropriation. One is near Mosier in the Hood Basin. The other is near Silverton in the Willamette Basin.In most of the above restricted areas, the limitations apply only to the specific aquifer that has had water-level declines or other problems documented. In some cases, groundwater may still be available at a different depth from a different aquifer. As more wells are drilled, the Department may find other areas where use of groundwater must be limited.

About this dataset

Context

The dataset tabulates the Oregon population by race and ethnicity. The dataset can be utilized to understand the racial distribution of Oregon.

Content

The dataset will have the following datasets when applicable

Please note that in case when either of Hispanic or Non-Hispanic population doesnt exist, the respective dataset will not be available (as there will not be a population subset applicable for the same)

• Oregon, MO Population Breakdown by Race
• Oregon, MO Non-Hispanic Population Breakdown by Race
• Oregon, MO Hispanic or Latino Population Distribution by Their Ancestries

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

This Coastal Relief Gridded database provides the first comprehensive view of the US Coastal Zone; one that extends from the coastal state boundaries to as far offshore as the NOS hydrographic data will support a continuous view of the seafloor. In many cases, this seaward limit reaches out to, and in places even beyond the continental slope. The gridded database contains data for the entire coastal zone of the conterminous US, including Hawaii and Puerto Rico.

This study provides statistical information on how prosecutors and the courts disposed of criminal cases involving adults arrested for felony crimes in two individual urban jurisdictions, Portland, Oregon and Washington, D.C. Cases in the data files were initiated or filed in 1982. Both the Washington, D.C. file and the Portland file contain information on all felony arrests (which include arrests declined as well as those filed), cases filed, and cases indicted. Sentencing information is provided in the Portland file but is not available for Washington D.C.

About this dataset

Context

The dataset tabulates the Oregon population by race and ethnicity. The dataset can be utilized to understand the racial distribution of Oregon.

Content

The dataset will have the following datasets when applicable

Please note that in case when either of Hispanic or Non-Hispanic population doesnt exist, the respective dataset will not be available (as there will not be a population subset applicable for the same)

• Oregon, IL Population Breakdown by Race
• Oregon, IL Non-Hispanic Population Breakdown by Race
• Oregon, IL Hispanic or Latino Population Distribution by Their Ancestries

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

The Oregon Fish Passage Barrier Data Standard (OFPBDS) dataset contains barriers to fish passage in Oregon watercourses. Barriers include the following types of natural or artificial structures: bridges, cascades, culverts, dams, debris jams, fords, natural falls, tide gates, and weirs. The OFPBDS dataset does not include structures which are not associated with in-stream features (such as dikes, levees or berms). Barriers are structures which do, or potentially may, impede fish movement and migration. Barriers can be known to cause complete or partial blockage to fish passage, or they can be completely passable, or they may have an unknown passage status. This dataset complies with version 1.1 of the OFBPDS data standard. New optional attributes have been added to describe fish passage barrier feature modifications, to describe supplementary information (via a comments field) and also to linear reference the barrier features to the National Hydrography Dataset. The OFPBDS dataset now contains over 40,000 barrier features from 19 separate sources including: Oregon Department of Fish and Wildlife (ODFW), Oregon Department of Transportation (ODOT), Oregon Department of Water Resources (OWRD), Oregon Department of Forestry (ODF), Oregon Watershed Enhancement Board (OWEB), Oregon Department of Land Conservation and Development (DLCD) US Bureau of Land Management (BLM), US Forest Service, Nez Perce Tribe, Benton SWCD, Washington county, Lower Columbia River Estuary Partnership and watershed councils representing the Rogue, Umpqua, Siuslaw, Santiam, Calapooia, Clackamas and Scapoose basins. The Data Steward obtained fish passage barrier data from multiple data originators between 2008 and 2019, collaborated with them to develop inclusion / exclusion criteria and dataset specific crosswalks for converting data from its original data structure to the structure of the OFPBDS. The data were then converted into the OFPBDS format and analyzed for duplication with existing OFPBDS barrier features. Where duplicates were identified, depending upon the scenario, one feature was either chosen over the other or in some cases attributes from different sources are combined. Source information is retained for each feature. The data were then loaded into the OFPBDS database. Barrier features were linear referenced (Framework Hydro only which is outside of the standard) and the corresponding optional attribute elements were populated. The data conversion, duplication reconciliation and linear referencing protocols are documented in the Oregon Fish Passage Barrier Data Management Plan. A separate dataset containing fish passage barrier features that have been completely removed or replaced (e.g. dam removals and culvert replacements) is published simultaneously with the OFPBDS dataset. The OFPBDS database is the most comprehensive compilation of fish passage barrier information in Oregon however, it does NOT represent a complete and current record of every fish passage barrier within the state. Efforts to address deficiencies in data currency, completeness and accuracy are ongoing and are often limited by lack of sufficient resources. Attributes (including key attributes such as fish passage status) are often unknown or incomplete. Consistency in attribution also varies among data originators. Field verification of barrier features and their attributes will be an important component to making this dataset current, comprehensive and accurate. Fish passage status is a key attribute. Many barrier features have an unknown passage status. For other features, the passage status may have changed since it was originally documented. Note that this metadata file is best viewed in ArcCatalog. Documentation for the OFPBDS can be found online at http://www.oregon.gov/DAS/EISPD/GEO/docs/bioscience/OregonFishPassageBarrierDataStandardv1dot1.pdf.

Fire Stations in Oregon Any location where fire fighters are stationed or based out of, or where equipment that such personnel use in carrying out their jobs is stored for ready use. Fire Departments not having a permanent location are included, in which case their location has been depicted at the city/town hall or at the center of their service area if a city/town hall does not exist. This dataset includes those locations primarily engaged in forest or grasslands fire fighting, including fire lookout towers if the towers are in current use for fire protection purposes. This dataset includes both private and governmental entities. Fire fighting training academies are also included.

This dataset is comprised completely of license free data.

The Fire Station dataset and the EMS dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes.

Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries.

Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results.

All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics.

The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record dates from 07/11/2006 and the newest record dates from 06/02/2008.

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), weights needed to be developed for use in the weighted sum of the different favorability index models produced from geoscientific exploration datasets. This was done using two different approaches: one based on expert opinions, and one based on statistical learning. This GDR submission includes the datasets used to produce the statistical learning-based weights. While expert opinions allow us to include more nuanced information in the weights, expert opinions are subject to human bias. Data-centric or statistical approaches help to overcome these potential human biases by focusing on and drawing conclusions from the data alone. The drawback is that, to apply these types of approaches, a dataset is needed. Therefore, we attempted to build comprehensive standardized datasets mapping anomalies in each exploration dataset to each component of each play. This data was gathered through a literature review focused on magmatic hydrothermal plays along with well-characterized areas where superhot or supercritical conditions are thought to exist. Datasets were assembled for all three play types, but the hydrothermal dataset is the least complete due to its relatively low priority. For each known or assumed resource, the dataset states what anomaly in each exploration dataset is associated with each component of the system. The data is only a semi-quantitative, where values are either high, medium, or low, relative to background levels. In addition, the dataset has significant gaps, as not every possible exploration dataset has been collected and analyzed at every known or suspected geothermal resource area, in the context of all possible play types. The following training sites were used to assemble this dataset: - Conventional magmatic hydrothermal: Akutan (from AK PFA), Oregon Cascades PFA, Glass Buttes OR, Mauna Kea (from HI PFA), Lanai (from HI PFA), Mt St Helens Shear Zone (from WA PFA), Wind River Valley (From WA PFA), Mount Baker (from WA PFA). - Superhot EGS: Newberry (EGS demonstration project), Coso (EGS demonstration project), Geysers (EGS demonstration project), Eastern Snake River Plain (EGS demonstration project), Utah FORGE, Larderello, Kakkonda, Taupo Volcanic Zone, Acoculco, Krafla. - Supercritical: Coso, Geysers, Salton Sea, Larderello, Los Humeros, Taupo Volcanic Zone, Krafla, Reyjanes, Hengill. **Disclaimer: Treat the supercritical fluid anomalies with skepticism. They are based on assumptions due to the general lack of confirmed supercritical fluid encounters and samples at the sites included in this dataset, at the time of assembling the dataset. The main assumption was that the supercritical fluid in a given geothermal system has shared properties with the hydrothermal fluid, which may not be the case in reality. Once the datasets were assembled, principal component analysis (PCA) was applied to each. PCA is an unsupervised statistical learning technique, meaning that labels are not required on the data, that summarized the directions of variance in the data. This approach was chosen because our labels are not certain, i.e., we do not know with 100% confidence that superhot resources exist at all the assumed positive areas. We also do not have data for any known non-geothermal areas, meaning that it would be challenging to apply a supervised learning technique. In order to generate weights from the PCA, an analysis of the PCA loading values was conducted. PCA loading values represent how much a feature is contributing to each principal component, and therefore the overall variance in the data.

This dataset is the City of Bend Police Department Calls for Service tabular layer curated for public use. Data is exported nightly from County E911 and ingested into City databases for both internal and external use. Calls with the following type are excluded from both the public GIS and tabular data:Abuse / NeglectAMI Mental / Behavioral DisorderC99 Assist to MedicsDirector's HoldDomestic DisputeJuvenile ProblemKidnappingMIP Minor in PossessionMissing / Overdue PersonRestraining Order ViolationRunaway JuvenileSex CrimeStalkingSuicidal SubjectSuicide AttemptedSuicide AttemptPlease note data is updated nightly and reflects calls received as of 6 PM the previous day.Attribute Information: See Table Field Name Description

OBJECTID For internal use.

IncidentNumber A unique incident identifier that corresponds to a call for service number.

CreateDateTime Date and time that the call was received by Deschutes County 911 or initiated by a Bend Police officer.

Day_of_Week Day of the week the call was received.

Hour_of_Day Time the call was received.

CallType The specific nature of the call for service.

Source Where the call for service originated.

CallAddress The address of the call, generalized to the hundred block for privacy. Occasionally, reporting parties or involved subjects are unable to provide the exact location where the reported incident occurred, a non-verifiable address is provided, or the crime may have occurred in a location outside of Deschutes County. In these instances, the location field will say “address not verified or outside jurisdiction.”

Neighborhood The City of Bend neighborhood boundary in which a call for service originated. For questions regarding individual cases or incidents, you can request records from the Bend Police Department here: https://www.bendoregon.gov/government/departments/police/records-division or you can send an email to police@bendoregon.gov

The polygon (vector) shapefiles represent claim areas within Public Land Survey System (PLSS) sections aggregated by serial (claim) numbers with information about Bureau of Land Management (BLM) land and mineral use authorizations geothermal. The land areas specified by BLM authorizations vary in size and orientation, and may cross one or more PLSS section boundaries. For spatial consistency, the information was aggregated to the square mile PLSS section boundary and by serial numbers. The original source data from BLM Cases Recordation database (LR2000) were specific to the day they were generated (March 6, 2016) and subsequent data pulls will likely be different.