VITAL SIGNS INDICATOR Fatalities From Crashes (EN4-6)

FULL MEASURE NAME Fatalities from crashes (traffic collisions)

LAST UPDATED May 2022

DESCRIPTION Fatalities from crashes refers to deaths as a result of injuries sustained in collisions. The California Highway Patrol includes deaths within 30 days of the collision that are a result of injuries sustained as part of this metric. This total fatalities dataset includes fatality counts for the region and counties, as well as individual collision data and metropolitan area data.

DATA SOURCE National Highway Safety Administration: Fatality Analysis Reporting System

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) The data is reported by the California Highway Patrol (CHP) to the Statewide Integrated Traffic Records System (SWITRS), which was accessed via SafeTREC’s Transportation Injury Mapping System (TIMS). The data was tabulated using provided categories specifying injury level, individuals involved, causes of collision, and location/jurisdiction of collision (for more: http://tims.berkeley.edu/help/files/switrs_codebook.doc).

For more regarding reporting procedures and injury classification, see the California Highway Patrol Manual (https://one.nhtsa.gov/nhtsa/stateCatalog/states/ca/docs/CA_CHP555_Manual_2_2003_ch1-13.pdf).

This U.S. Geological Survey (USGS) data release presents U-Th-Pb concentrations, isotopic ratios, and geochronologic data collected by thermal ionization mass spectrometry (TIMS) for Proterozoic igneous and metamorphic rocks of the Mojave Province, California and Nevada. Sample and data collection occurred by 1984 and 1990.

Thermal Infrared Multispectral Scanner (TIMS) data were collected over geologic features such as volcanic fields, playas, dunes, and alluvial fans. Each image file contains 6 bands in band-interleaved format, 8 bits per pixel. Each image is accompanied by an auxiliary file which contains the line by line temperature values of the references sources as recorded by the thermistors during each data take as well as the corresponding radiance values (in all six bands) for each thermistor as recorded by the scan head.

TIMS - inspection database. Numeric and descriptive record of security inspections of transport industry. No personal data other than name of inspector and possible references to names of security managers dealt with during inspections

This layer contains Iowa DOT Office of Transportation Operations Transportation Incident Management (TIM) Closures.

For BOREAS, the TIMS imagery, along with the other remotely sensed images, was collected to provide spatially extensive information over the primary study areas. The level-0 TIMS images cover the time periods of 16-Apr-1994 to 20-Apr-1994 and 06-Sep-1994 to 17-Sep-1994. The images are available in their original uncalibrated format. Companion files include (1) an image inventory listing to inform users of the images that are available and (2) example thumbnail images that may be viewed and the image data files downloaded using a convenient viewer utility.

Contact database. Names, addresses, telephone number and e-mail of up 10,000 transport industry security contacts. Information is stored on the TIMS system.

VITAL SIGNS INDICATOR Injuries From Crashes (EN7-9)

FULL MEASURE NAME Serious injuries from crashes (traffic collisions)

LAST UPDATED October 2017

DESCRIPTION Injuries from crashes refers to serious but not fatal injuries sustained in a collision. The California Highway Patrol classifies a serious injury as any combination of the following: broken bones; dislocated or distorted limbs; severe lacerations; skull, spinal, chest or abdominal injuries that go beyond visible injuries; unconsciousness at or when taken from the scene; or severe burns. This injuries dataset includes serious injury counts for the region and counties, as well as individual collision data.

DATA SOURCE California Highway Patrol: Statewide Integrated Traffic Records System

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) The data is reported by the California Highway Patrol (CHP) to the Statewide Integrated Traffic Records System (SWITRS), which was accessed via SafeTREC’s Transportation Injury Mapping System (TIMS). The data was tabulated using provided categories specifying injury level, individuals involved, causes of collision, and location/jurisdiction of collision (for more: http://tims.berkeley.edu/help/files/switrs_codebook.doc). Fatalities were normalized over historic population data from the US Census and American Community Surveys and vehicle miles traveled (VMT) data from the Federal Highway Administration.

For more regarding reporting procedures and injury classification, see the California Highway Patrol Manual (http://www.nhtsa.gov/nhtsa/stateCatalog/states/ca/docs/CACHP555Manual_22003ch1-13.pdf).

SACOG Regional Transportation Collision Dataset Transportation Injury Mapping System data, includes years 2012-2022.Provisional years 2023 and2024From TIMS"We geocoded the 2023-2024 provisional SWITRS data and uploaded it into TIMS. We have started including partial year SWITRS data for the current year with a 3-month delay. Currently, TIMS includes SWITRS data up to crashes that occurred on December 31, 2024. Please email tims_info@berkeley.edu if you have any follow up questions regarding this update.Please note that the provisional data are subject to change and only contain records added to the I-SWITRS website by CHP up until March 11 2025. Therefore, they should not be directly compared to the number of crashes in previous years."

The geographic data are built from the Technical Information Management System (TIMS). TIMS consists of two separate databases: an attribute database and a spatial database. The attribute information for offshore activities is stored in the TIMS database. The spatial database is a combination of the ARC/INFO and FINDER databases and contains all the coordinates and topology information for geographic features. The attribute and spatial databases are interconnected through the use of common data elements in both databases, thereby creating the spatial datasets. The data in the mapping files are made up of straight-line segments. If an arc existed in the original data, it has been replaced with a series of straight lines that approximate the arc. The Gulf of America OCS Region stores all its mapping data in longitude and latitude format. All coordinates are in NAD 27. Data can be obtained in three types of digital formats: INTERACTIVE MAP: The ArcGIS web maps are an interactive display of geographic information, containing a basemap, a set of data layers (many of which include interactive pop-up windows with information about the data), an extent, navigation tools to pan and zoom, and additional tools for geospatial analysis. SHP: A Shapefile is a digital vector (non-topological) storage format for storing geometric location and associated attribute information. Shapefiles can support point, line, and area features with attributes held in a dBASE format file. GEODATABASE: An ArcGIS geodatabase is a collection of geographic datasets of various types held in a common file system folder, a Microsoft Access database, or a multiuser relational DBMS (such as Oracle, Microsoft SQL Server, PostgreSQL, Informix, or IBM DB2). The geodatabase is the native data structure for ArcGIS and is the primary data format used for editing and data management.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Redirect Notice: The website https://transbase.sfgov.org/ is no longer in operation. Visitors to Transbase will be redirected to this page where they can view, visualize, and download Traffic Crash data.

A. SUMMARY This table contains all crashes resulting in an injury in the City of San Francisco. Fatality year-to-date crash data is obtained from the Office of the Chief Medical Examiner (OME) death records, and only includes those cases that meet the San Francisco Vision Zero Fatality Protocol maintained by the San Francisco Department of Public Health (SFDPH), San Francisco Police Department (SFPD), and San Francisco Municipal Transportation Agency (SFMTA). Injury crash data is obtained from SFPD’s Interim Collision System for 2018 through the current year-to-date, Crossroads Software Traffic Collision Database (CR) for years 2013-2017 and the Statewide Integrated Transportation Record System (SWITRS) maintained by the California Highway Patrol for all years prior to 2013. Only crashes with valid geographic information are mapped. All geocodable crash data is represented on the simplified San Francisco street centerline model maintained by the Department of Public Works (SFDPW). Collision injury data is queried and aggregated on a quarterly basis. Crashes occurring at complex intersections with multiple roadways are mapped onto a single point and injury and fatality crashes occurring on highways are excluded.

The crash, party, and victim tables have a relational structure. The traffic crashes table contains information on each crash, one record per crash. The party table contains information from all parties involved in the crashes, one record per party. Parties are individuals involved in a traffic crash including drivers, pedestrians, bicyclists, and parked vehicles. The victim table contains information about each party injured in the collision, including any passengers. Injury severity is included in the victim table.

For example, a crash occurs (1 record in the crash table) that involves a driver party and a pedestrian party (2 records in the party table). Only the pedestrian is injured and thus is the only victim (1 record in the victim table).

To learn more about the traffic injury datasets, see the TIMS documentation

B. HOW THE DATASET IS CREATED Traffic crash injury data is collected from the California Highway Patrol 555 Crash Report as submitted by the police officer within 30 days after the crash occurred. All fields that match the SWITRS data schema are programmatically extracted, de-identified, geocoded, and loaded into TransBASE. See Section D below for details regarding TransBASE.

C. UPDATE PROCESS After review by SFPD and SFDPH staff, the data is made publicly available approximately a month after the end of the previous quarter (May for Q1, August for Q2, November for Q3, and February for Q4).

D. HOW TO USE THIS DATASET This data is being provided as public information as defined under San Francisco and California public records laws. SFDPH, SFMTA, and SFPD cannot limit or restrict the use of this data or its interpretation by other parties in any way. Where the data is communicated, distributed, reproduced, mapped, or used in any other way, the user should acknowledge TransBASE.sfgov.org as the source of the data, provide a reference to the original data source where also applicable, include the date the data was pulled, and note any caveats specified in the associated metadata documentation provided. However, users should not attribute their analysis or interpretation of this data to the City of San Francisco. While the data has been collected and/or produced for the use of the City of San Francisco, it cannot guarantee its accuracy or completeness. Accordingly, the City of San Francisco, including SFDPH, SFMTA, and SFPD make no representation as to the accuracy of the information or its suitability for any purpose and disclaim any liability for omissions or errors that may be contained therein. As all data is associated with methodological assumptions and limitations, the City recommends that users review methodological documentation associated with the data prior to its analysis, interpretation, or communication.

This dataset can also be queried on the TransBASE Dashboard. TransBASE is a geospatially enabled database maintained by SFDPH that currently includes over 200 spatially referenced variables from multiple agencies and across a range of geographic scales, including infrastructure, transportation, zoning, sociodemographic, and collision data, all linked to an intersection or street segment. TransBASE facilitates a data-driven approach to understanding and addressing transportation-related health issues, informed by a large and growing evidence base regarding the importance of transportation system design and land use decisions for health. TransBASE’s purpose is to inform public and private efforts to improve transportation system safety, sustainability, community health and equity in San Francisco.

E. RELATED DATASETS Traffic Crashes Resulting in Injury: Parties Involved Traffic Crashes Resulting in Injury: Victims Involved TransBASE Dashboard iSWITRS TIMS

The BOREAS Staff Science Aircraft Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. For BOREAS, the TIMS imagery, along with other aircraft images, was collected to provide spatially extensive information over the primary study areas. The level-1B TIMS images cover the time periods of 16-Apr-1994 to 20-Apr-1994 and 06-Sep-1994 to 17-Sep-1994. The system calibrated images are stored in binary image format files. Companion files include (1) an image inventory listing to inform users of the images that are available and (2) example thumbnail images.

DHS case management system, known as the Joint Threat Information Management System (J-TIMS) to track the full lifecycle of an allegation from intake, through DHS OIG referral, investigation, and eventual case disposition

This feature layer spatially represents DriveNC//NCDOT’s TIMS incident data feed by Road Condition. The TIMS Incidents data contains the general location of and details about incidents that affect or will affect travel on roads maintained by the North Carolina Department of Transportation.This hosted feature layer view is intended for public viewing.NCDOT TIMS Incidents Points - Contains a point reference for all incidents, point and line.NCDOT TIMS Incidents Lines - Lines representing linear incidents. Generally, only select incidents types and road closed conditions will be represented as lines. A point feature will represent the same incident.This data includes all incidents including those recorded on concurrent routes. To remove these from the data, filter where "CreatedFromConcurrent = False".The data is provided through an automated routine that pulls data from the TIMS geojson feed every 5 minutes. Note that the data may disappear for a few moments while being refreshed.The feature layer contains all incidents; current and future. To only view current incidents in your web map, create a filter using the "StartDate" field. For example, filter by Start Date "in the last" 6 years. Note: DateTime fields are in UTC (as indicated in the field name). Text fields contain data/time values in Eastern Time.

Attributes/Fields:

Attribute/Field 


Description/Comments

Id

Unique Id of the Incident

Location

General description of the incident location.

Road

The road on which the incident occurred.

CommonName

Common name of the road on which the incident occurred or will occur

Direction

Direction of traffic impacted. Values include: North South East West All Inner Out

RouteType

Type of Route. Values include: Interstate US Route NC Route Secondary Road

RouteSuffix

Route Suffix. Values include: Alternate Business Bypass Connector Express Truck Toll

RouteId

NCDOT route id

City

Name of the nearest city to the incident.

CountyId

County number in which the incident occurred. Values from 1 to 100, where Alamance is 1 and Yancey is 100.

CountyName

Name of the county in which the incident occurred.

Division

Division number

EventId

Id of the Event designation. If the field is blank, the incident is not associated with an event.

EventName

Name of the Event designation. If the field is blank, the incident is not associated with an event.

Reason

Additional information about the incident.

IncidentType

Type of incident. Values include: Emergency Road Work Construction Night Time Construction Weekend Construction Maintenance Night Time Maintenance Road Obstruction Vehicle Crash Disabled Vehicle Congestion Signal Problem Weather Event Fog Fire Special Event Other Reported Incident

Severity

Severity of the incident. Values include: 1 = Low Impact 2 = Medium Impact 3 – High Impact

Condition

Road condition caused by the incident. Congestion Lane Closed Lane Shift Lanes Closed Lanes Narrowed Moving Closure Permanent Road Closure Ramp Closed Rest Area Closed Road Closed Road Impassable Shoulder Closed Lane Narrowed Ramp Lane Closed Ramp Lane Narrowed Road Closed with Detour

Detour

The detour or alternate route instructions

LanesClosed

The total number of lanes closed due to the incident

LanesTotal

The total number of lanes affected by the incident

DriveNCLink

Link to the DriveNC web page for the incident

StartDateUTC

Incident start date/time in UTC. AGOL automatically adjust date/time to the local time zone. Calculate the time when used outside of AGOL. To calculate EST subtract 5 hours. To calculate EDT subtract 4 hours.

EndDateUTC

Incident end date/time in UTC. AGOL automatically adjust date/time to the local time zone. Calculate the time when used outside of AGOL. To calculate subtract 5 hours. To calculate EDT subtract 4 hours.

LastUpdateDateUTC

Last update date/time in UTC. AGOL automatically adjust date/time to the local time zone. Calculate the time when used outside of AGOL. To calculate subtract 5 hours. To calculate EDT subtract 4 hours

TIMCCreationDateUTC

TIMS Creation date/time in UTC. Calculate the time when used outside of AGOL. To calculate EST subtract 5 hours.To calculate EDT subtract 4 hours

StartDateET

Incident Start Date in ET (EDT or EST).This is a text field suitable for display. Use the UTC fields for filtering on time.

StartTimeET

Incident Start Time in ET (EDT or EST). This is a text field suitable for display. Use the UTC fields for filtering on time.

EndDateET

Incident End Date in ET (EDT or EST). This is a text field suitable for display. Use the UTC fields for filtering on time.

EndTimeET

Incident End Time in ET (EDT or EST). This is a text field suitable for display. Use the UTC fields for filtering on time.

LastUpdateDateET

Last Update Date in ET (EDT or EST). This is a text field suitable for display. Use the UTC fields for filtering on time.

LastUpdateTimeET

Last Update Time in ET (EDT or EST). This is a text field suitable for display. Use the UTC fields for filtering on time.

TIMSCreationDateET

TIMS Creation Date in ET (EDT or EST). This is a text field suitable for display. Use the UTC fields for filtering on time.

TIMSCreationTimeET

TIMS Creation Time in ET (EDT or EST). This is a text field suitable for display. Use the UTC fields for filtering on time.

Latitude

Latitude

Longitude

Longitude

Note: Details about the incident are available through the NCDOT TIMS site. You can link directly to the incident details by combining https://tims.ncdot.gov/TIMS/IncidentDetail.aspx?id= and the TimsId/Incident ID. Note: The Last Modified and Created dates apply to this item entry in GO!NC/ArcGIS Online and may not reflect the actual dates of the data or map service itself.

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Data-independent acquisition (DIA) methods have become increasingly attractive in mass spectrometry (MS)-based proteomics, because they enable high data completeness and a wide dynamic range. Recently, we combined DIA with parallel accumulation – serial fragmentation (dia-PASEF) on a Bruker trapped ion mobility separated (TIMS) quadrupole time-of-flight (TOF) mass spectrometer. This requires alignment of the ion mobility separation with the downstream mass selective quadrupole, leading to a more complex scheme for dia-PASEF window placement compared to DIA. To achieve high data completeness and deep proteome coverage, here we employ variable isolation windows that are placed optimally depending on precursor density in the m/z and ion mobility plane. This Automatic Isolation Design procedure is implemented in the freely available py_diAID package. In combination with in-depth project-specific proteomics libraries and the Evosep LC system, we reproducibly identified over 7,700 proteins in a human cancer cell line in 44 minutes with quadruplicate single-shot injections at high sensitivity. Even at a throughput of 100 samples per day (11 minutes LC gradients), we consistently quantified more than 6,000 proteins in mammalian cell lysates by injecting four replicates. We found that optimal dia-PASEF window placement facilitates in-depth phosphoproteomics with very high sensitivity, quantifying more than 35,000 phosphosites in a human cancer cell line stimulated with an epidermal growth factor (EGF) in triplicate 21 minutes runs. This covers a substantial part of the regulated phosphoproteome with high sensitivity, opening up for extensive systems-biological studies.

The project needs data for macroscopic statistical modeling, which are OTS rankings and historical crash data. OTS crash ranking data California Office of Traffic Safety (OTS) provides a crash ranking dataset that was developed so that individual cities could compare their city’s traffic safety statistics to those of other cities with similar-sized populations. The OTS crash rankings are based on the Empirical Bayesian Ranking Method. It adds weights to different crash statistical categories including observed crash counts, population and daily vehicle miles traveled (DVMT). In addition, the OTS crash rankings include different types of crashes with larger percentages of total victims and areas of focus for the OTS grant program. In conjunction with the research context, two types of crash rankings are focused on, namely pedestrians and bicyclists. SWITRS crash data The Transportation Injury Mapping System (TIMS) to provide the project quick, easy, and free access to California crash d..., The Safe Transportation Research and Education Center (SafeTREC) at the University of California, Berkeley, develops the Transportation Injury Mapping System (TIMS) to provide a quick, easy and free access to California crash data provided by the Statewide Integrated Traffic Records System (SWITRS). We collect five-year-long crash data, which are from 01/01/2014 to 12/31/2018. The crash data includes bicyclist and pedestrian collisions with vehicles resulting in injuries across four types of crash severity: fatal, severe injury, visible injury, and complaint of injury. The data consists of three tables including the collision dataset, the involved parties dataset, and the victims dataset. In particular, we use the collision and parties datasets that contain enough information for modeling. The rows in the crash data are built based on each case of a crash and includes information such as weather, road surface, road condition, control device, and lighting. The parties dataset includes in..., The data files can be viewed by Excel.Â

Comprehensive dataset containing 775 verified Tim Hortons locations in United States with complete contact information, ratings, reviews, and location data.