Seattle Police Department Micro Community Policing Plan InformationThis layer was published in the WGS 1984 Web Mercator Auxiliary Sphere coordinate system.

FBI National Incident-Based Reporting System (FBI NIBRS) crime data for Seattle Police Department (City) in Washington, including incidents, statistics, demographics, and detailed incident information.

This data represents police response activity. Each row is a record of a Call for Service (CfS) logged with the Seattle Police Department (SPD) Communications Center. Calls originated from the community and range from in progress or active emergencies to requests for problem solving. Additionally, officers will log calls from their observations of the field.

Previous versions of this data set have withheld approximately 40% of calls. This updated process will release more than 95% of all calls but we will no longer provide latitude and longitude specific location data. In an effort to safeguard the privacy of our community, calls will only be located to the “beat” level. Beats are the most granular unit of management used for patrol deployment. To learn more about patrol deployment, please visit: https://www.seattle.gov/police/about-us/about-policing/precinct-and-patrol-boundaries.

As with any data, certain conditions and qualifications apply:

1) These data are queried from the Data Analytics Platform (DAP), and updated incrementally on a daily basis. A full refresh will occur twice a year and is intended to reconcile minor changes.

2) This data set only contains records of police response. If a call is queued in the system but cleared before an officer can respond, it will not be included.

3) These data contain administrative call types. Use the “Initial” and “Final” call type to identify the calls you wish to include in your analysis.

We invite you to engage these data, ask questions and explore.

Records representing Use of Force (UOF) by sworn law enforcement officers of the Seattle Police Department.

Seattle Police Department In-Car Video Dropped Frame Report

Content

This data represents records of police reported stops under Terry v. Ohio, 392 U.S. 1 (1968). Each row represents a unique stop.

• Each record contains perceived demographics of the subject, as reported by the officer making the stop and officer demographics as reported to the Seattle Police Department, for employment purposes.

• Where available, data elements from the associated Computer Aided Dispatch (CAD) event (e.g. Call Type, Initial Call Type, Final Call Type) are included.

Context

This is a dataset hosted by the City of Seattle. The city has an open data platform found here and they update their information according the amount of data that is brought in. Explore New York City using Kaggle and all of the data sources available through the City of Seattle organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

Cover photo by Marina Vitale on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

Note! Subject Data is temporarily unavailable, while we chase down a bug. Please excuse the inconvenience (DGAL-8).

This data represents records of police reported stops under Terry v. Ohio, 392 U.S. 1 (1968). Each row represents a unique stop.

• Each record contains perceived demographics of the subject, as reported by the officer making the stop and officer demographics as reported to the Seattle Police Department, for employment purposes.

• Where available, data elements from the associated Computer Aided Dispatch (CAD) event (e.g. Call Type, Initial Call Type, Final Call Type) are included.

A list of all public data requests made to the Seattle Police Department 2016 to December 2020. Requester names have been anonymized. Request summaries have been redacted to remove personally identifiable information (e.g. names, addresses, phone numbers, etc.) entered by the requester.

The goal of the project was to improve police officers' sleep, health, safety, and wellness, thus improving the quality of police services. Using a multi-phase, mixed method approach, the core objectives included: Measure the effects of work schedules and sleep loss on Seattle Police Department (SPD) officer health, wellness, safety, and quality of life. Develop a fatigue risk management strategy, informed by the data collected during objective one. Using a randomized control trial design, implement the resulting fatigue risk management strategy across the SPD, which is a large municipal police department (approximately 1,500 sworn officers) Measure the effectiveness of the fatigue risk management strategy. The main research questions the study sought to address were as follows: What are the effects of shift work, work hours, sleep loss, and fatigue on police officers' safety, health, and quality of life? Can a fatigue risk management strategy influence these effects? Variables include measures of officers' sleep patterns and sleep quality, physical and mental health metrics, descriptions of the officers' role at the SPD, and demographic variables including age, gender, and race/ethnicity.

The Seattle Police Department has different iterations of police beats as the city's needs evolved. This layer represents what the beats looked like from 2017 to present. This layer was published in the WGS 1984 Web Mercator Auxiliary Sphere coordinate system.

The specific aim of this project was to evaluate the usefulness of the Seattle Police Department's (SPD) Lethality Scale in identifying misdemeanor cases that might be high risk for escalating violence and subsequent felony incidents. Data provide information on 11,972 unique couples with incidents occurring between January 1, 1995, and December 31, 1997, involving intimate couples in which the suspect was at least 18 years old and the victim was at least 16, with no age restriction for cases referred to the juvenile division. The researchers reformatted the Domestic Violence Unit's (DVU) database to reflect a three-year history of violence between unique couple members. Only intimate couples were considered, meaning suspects and victims who were married, divorced, had a child in common, or were dating. The Lethality Scale was derived from the data in the DVU database. It was composed of six incident characteristic components (offense score, weapon score, location score, injury score, personal score, and incident/other score) with varying values that contributed to an overall score. The Total Lethality Score was the sum of the values from these six components. The lethality score referred to an individual only and did not reflect information about other people involved in the incident. To interpret the score, the DVU specified a period of time--for example, six months--and computed lethality score values for every person involved in an incident during this period. Information on individuals with a Total Lethality Score over a certain cut-off was printed and reviewed by a detective. Data are provided for up to 25 incidents per unique couple. Incident variables in the dataset provide information on number of persons involved in the incident, time and weekday of the incident, beat, precinct, census tract, and place where the incident occurred, type of primary and secondary offenses, if a warrant was served, charges brought, final disposition, weapon type used, arrests made, court order information, if evidence was collected, if statements or photos were taken by the DVU, and sergeant action. Dates were converted to time intervals and provide the number of days between the incident date and the date the file was sent to the prosecutor, the date charges were brought, and the date the case was officially closed. Time intervals were also calculated for days between each incident for that couple. Personal information on the two persons in a couple includes age, gender, injuries and treatment, relationship and cohabitation status of the individuals, pregnancy status of each individual, alcohol and drug use at the time of the incident, and role of the individual in the incident (victim, suspect, victim/suspect). Lethality scale scores are included as well as the number of incidents in which the unique couple was involved in 1995 and 1996, and 1989 median household income for the census tract.

This data represents records of police reported stops under Terry v. Ohio, 392 U.S. 1 (1968). Each row represents a unique stop.

• Each record contains perceived demographics of the subject, as reported by the officer making the stop and officer demographics as reported to the Seattle Police Department, for employment purposes.

• Where available, data elements from the associated Computer Aided Dispatch (CAD) event (e.g. Call Type, Initial Call Type, Final Call Type) are included.

Spatial data files of City of Seatle Police precincts and beats. Coordinate system is WGS84

● This dataset was provided by: Seattle Police Department ● Dataset category: Public Safety ● Dataset created date: February 14, 2020

Acknowledgement

This data has been taken from Seattle city's official website

Financial overview and grant giving statistics of Seattle Police Officers Guild Benefit Trust

Background: “In 2006, the Seattle Police Department began surveying members of the public (customers) who had personal contact with an officer after calling 9-1-1. The surveys have been conducted two to four times a year, and a total of 44 surveys have been conducted to date. These surveys have been designed to assess customers’ experiences and satisfaction with the service provided by the Seattle Police Department, and the results of the surveys have been used to assess service delivery; examine differences between precincts; identify strategies and tactics to achieve specific service objectives; and provide feedback to officers, precinct captains, and watch lieutenants. This report presents the results of the September 2019 customer survey and compares the September 2019 survey results to results from the 13 other surveys conducted since March 2016.”

Research Methods. “Similar to the previous surveys, 200 customers who called 9-1-1 and had an officer dispatched to provide assistance were interviewed by telephone for this survey. All of the customers interviewed had called 9-1-1 between August 21 and August 29, 2019, and were randomly selected from lists of 9-1-1 callers who had an officer dispatched to provide assistance, excluding sensitive cases such as domestic violence calls. The interviews were completed between September 3 and September 10, 2019. The interviews were approximately 10 to 12 minutes long. The questionnaire used in the interviews was developed with Department input and approval. During the course of this research, some questions have been added to or deleted from the survey questionnaire to reflect the changing information needs of the Department. However, questions about customers’ overall satisfaction with their experience with the Department after calling 9-1-1, experiences with and opinions of the officer who first visited after the call to 9-1-1, opinions of the Seattle Police Department overall, and satisfaction with the service provided by the 9-1-1 operator have been included in every survey. Since late 2006 and early 2007, the surveys also included questions about customers’ feelings of safety in Seattle.”

Financial overview and grant giving statistics of Seattle Police Management Assoc

This data represents crime reported to the Seattle Police Department (SPD). Each row contains the record of a unique event where at least one criminal offense was reported by a member of the community or detected by an officer in the field. This data is the same data used in meetings such as SeaStat (https://www.seattle.gov/police/information-and-data/seastat) for strategic planning, accountability and performance management.

These data contain offenses and offense categorization coded to simulate the standard reported to the FBI under the National Incident Based Reporting System (NIBRS) and used to generate Uniform Crime Report (UCR) summary statistics. As these records evolve, daily and are continually refreshed, they will not match official UCR statistics. They represent a more accurate state of the record.

Previous versions of this data set have withheld approximately 40% of crimes. This updated process includes all records of crime reports logged in the Departments Records Management System (RMS) since 2008, which are tracked as part of the SeaStat process. In an effort to safeguard the privacy of our community, offense reports will only be located to the “beat” level. Location specific coordinates will no longer be provided.

Beats are the most granular unit of management used for patrol deployment. To learn more about patrol deployment, please visit: https://www.seattle.gov/police/about-us/about-policing/precinct-and-patrol-boundaries. In addition to the Departments patrol deployment areas, these data contain the “Neighborhood” where the crime occurred, if available. This coding is used to align crime data with the Micro Community Policing Plan (MCPP). For more information see: https://www.seattle.gov/police/community-policing/about-mcpp.

As with any data, certain condition and qualifications apply: 1) These data are refreshed, daily and represent the most accurate, evolved state of the record.

2) Due to quality control processes, these data will lag between 2 and 6 weeks. Most changes will occur within that record and reports logged in the last 2 weeks should be treated as volatile. Analysts may wish to remove these records from their analysis.

3) Not all offenses are reported here, only the primary offense as determined by the “Hierarchy Rule.” For more information on NIBRS and UCR, see the FBI (https://ucr.fbi.gov/nibrs-overview).

4) This dataset contains records of offenses that occurred prior to “go-live” of the existing RMS. Records are queried based on the full population of data and are not constrained by “Occurred Date.”

We invite you to engage these data, ask questions and explore.

Financial overview and grant giving statistics of Seattle Police Foundation