cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15787/vtt1/lyubjp
title: Canadian Naturalistic Driving Study InSight Dataset

description: The InSight website contains important subsets of the overall dataset. The website is meant to serve as a resource for researchers that are interested in learning more about the dataset and exploring its potential. Not all of the data collected in the study is available directly from the website, in some cases because of privacy reasons, in others because of feasibility. Users are encouraged to visit the "Background" section, where they will find frequently asked questions, data dictionaries, and additional documentation. Access to the data on the website is governed by its Terms of Service, and requires a validation process to confirm the user's e-mail address and the provision of a certificate that proves the completion of Institutional Review Board training on human subjects research. Detailed access requirement instructions are available on the website home page. The records in this version of the dataset (version 1.0) represent 213,550 trips, 149 drivers, 150 vehicles, and 1,979 events.
DOI: 10.5066/f7j101nv
title: Historical data sets including inorganic and organic chemistry of water, oil, and sediments, aquifer hydraulic conductivity, and sediment grain size distribution at the National Crude Oil Spill Fate and Natural Attenuation Research Site near Bemidji, Minnesota, USA, 1984-2010

description: This U.S. Geological Survey (USGS) Data Release provides analytical data from samples and measurements completed at the National Crude Oil Spill Fate and Natural Attenuation Research Site near Bemidji, Minnesota (Site) between 1984 and 2010. Included are inorganic and organic chemistry data from water, oil, and sediment samples, hydraulic conductivity data from well slug tests, and sediment grain-size distribution data from core samples. Most of these data sets have been described in previously published peer-reviewed reports, however the tabular data sets were not available with these publications. This data release provides the data in a tabular, database-ready format. Each result value in the data sets is coded to describe the kind of sample collected, the material that was analyzed, the method of analysis, and the publication where the value was originally published. Some sample codes are taken from the U.S. Geological Survey's National Water Information System (NWIS, https://waterdata.usgs.gov/nwis) and the remaining codes were developed specifically for Site data. Data dictionaries containing code definitions are available at a companion data release titled &amp;amp;quot;Sampling site information, well construction details, and data dictionaries for data sets associated with the National Crude Oil Spill Fate and Natural Attenuation Site near Bemidji, Minnesota&amp;amp;quot;, available at https://doi.org/10.5066/F7736PDR. In 1979, a high-pressure pipeline carrying crude oil burst near the city of Bemidji, Minnesota and spilled approximately 1.7 million liters (10,700 barrels) of crude oil into glacial outwash deposits. Since 1983, scientists with the U.S. Geological Survey, in collaboration with scientists from academic institutions, industry, and the regulatory community have conducted extensive investigations of multiphase flow and transport, volatilization, dissolution, geochemical interactions, microbial populations, and biodegradation with the goal of providing an improved understanding of the natural processes limiting the extent of hydrocarbon contamination. Long-term field studies at Bemidji have illustrated that the fate of hydrocarbons evolves with time, and a snap-shot study of a hydrocarbon plume may not provide information that is of relevance to the long-term behavior of the plume during natural attenuation. The research at the site has been supported primarily by the U.S. Geological Survey's Toxic Substances Hydrology Program.
DOI: 10.15787/vtt1/mxfpmx
title: The Effects of Medical Conditions on Driving Performance

description: Project Description Our project is investigating differences in driving exposure, driving performance, and safety between age-matched drivers with and without various medical conditions (and associated functional impairments). Our goal in the planned analysis will be to identify drivers for whom medical conditions of interest—including, but not necessarily limited to, COPD, Parkinson’s Disease and diabetes-related peripheral neuropathy—are represented in the SHRP 2 database, to fully document the characteristics of these drivers in terms of the variables available in the Driver dataset, and to examine variables in the Trip and Event datasets to determine whether significant differences exist in relation to age-matched drivers without (self-reported) medical conditions or measured deficits of vision or function. Data Request Scope The dataset includes data only for SHRP 2 drivers who meet the inclusion criteria listed in Appendix A (attached), which puts the drivers into four specified Groups. Data extraction techniques were used to prepare three datasets: - Exposure Analysis: This dataset was derived from Trip Summary Measures. See Appendix B (attached) for details on the derived data elements. - Driver Dataset: This dataset consists of data from the Driver Assessment data. See Appendix C (attached) for a list of the included variables. - Event Dataset: This dataset consists of data from the Event reduction data. See Appendix D (attached) for a list of the included variables. -- Data Specification See Appendix A, B, C, and D in attached document. --
DOI: 10.15787/vtt1/ngaoap
title: Differences between younger and elderly driver behavior and how they interact with roadway infrastructure in a naturalistic setting

description: Project Description The main focus of this project was to use data collected by the SHRP 2 Naturalistic Driving Study (NDS) to compare the driving behaviors of younger and elderly drivers and how they interact with roadway infrastructure elements in hopes to identify potential differences in factors that could lead to crash scenarios. Variables in the Trip and Event datasets as well as information in the SHRP2 database describing driver demographics, functional status, risk perception, and knowledge were included which may account for significant variance in the likelihood of occurrence of these crash types. Data Request Scope The dataset encompasses all crash events ranging from minor crashes to severe crashes. Data Specification The data included in the dataset include determinant factors such as roadway infrastructure, trip details, antecedent driver behaviors, and driver cognitive trait factors. The dataset exists as a Comma Separated Values (CSV) file of 21,531 rows of 160 columns.
DOI: 10.15787/vtt1/nqafth
title: Driver Behavior at Highway-Rail Grade Crossings Using Naturalistic Driving Study Data

description: Project Description Traffic incidents at highway-rail grade crossings continue to be a danger to both highway users and railroads causing over 250 fatalities each year. Michigan Tech will use the NDS data from grade crossing segments to analyze driver behavior at crossings, and to evaluate the effectiveness of a variety of traffic control devices currently in use at crossings. They used standard data analysis techniques, utilizing a variety of software tools, including Excel, MATLAB, and available database software. Project results will be used to investigate driver reaction to the existing traffic control devices, and impacts of the crossing environment, including weather, time of day, driver familiarity with the crossing, surface roughness. We will also investigate impacts from driver demographics. Future work will include using the NDS research results to inform and validate ongoing driver simulator research efforts. Data Request Scope The motivation for creating the dataset was to enable Michigan Tech to conduct a pilot investigation of driver behavior around highway-rail grade crossings. The data contained transits at three specific highway-rail grade crossings the first of which included two crossings, one active and one passive (NAVTEQ nodes 845714796, 96351877, and 96284604). Michigan Tech received video of front and rear views, time series data (excluding radar), and demographic information: participant ID, gender, and age group, for a total of 300 events. The event duration was ten seconds prior and ten seconds after each traversal. Data was sampled at 10 Hz. Additional reduction was provided for twenty transit events, ten active and ten passive crossings. These detailed narrative described driver behavior during each transit event. Data Specification Video files were provided as .mp4 format. Time-series files were delivered in .csv format, and demographic information was in .xlsx format. Please see attached data dictionary for a description of variables.
DOI: 10.15787/vtt1/qkythv
title: Focus Crash Types and Risk Factors

description: Project Description Systemic safety improvements, when selected and targeted appropriately, provide a tremendous opportunity to proactively reduce crashes. This is particularly useful for crash types and situations that are somewhat disperse in their occurrence (e.g., lane departure crashes on low volume roads, pedestrian crashes at intersections in an urban environment, crossing path crashes at unsignalized intersections in rural areas). State and local agencies are starting to embrace the benefit of systemic safety improvements, particularly now that systemic improvements are specifically identified in MAP-21. However, additional guidance is needed to help these agencies select and target their improvements to make the most of limited funds. As such, detailed information is needed on the crashes and contributing factors that are best targeted by systemic improvements and the types of locations and situations where these crashes occur. The purpose of this effort is to develop this detailed information. This analysis will focus on the event data in the NDS including information on crash severity and type (e.g. rollover, as well as road characteristics (e.g., number of travel lanes, weather conditions, alignment, etc.). Using the specified data, we plan on utilizing statistical methods to relate the various road characteristics to crash severity and type. In doing so, we will be able to identify road characteristics that are associated with higher crash severity (so called "risk factors"). Having identified risk factors for crash types and severity, we will subsequently be able to identify road segments where the risk factors are present thereby identifying appropriate areas for systemic safety improvements. Data Request Scope This dataset contains data for 1,531 crash or near crash events. Data Specification The data set consists of the following data elements. eventID eventSeverity1 eventSeverity2 preIncidentManeuver eventNature1 incidentType1 crashSeverity1 incidentType2 crashSeverity2 airbagDeployment vehicleRollover driverSeatbeltUse infrastructure visualObstructions lighting weather surfaceCondition trafficFlow contigTravelLanes throughTravelLanes relationToJunction intersectionInfluence alignment grade locality constructionZone numberOfOtherMotorists numberOfObjectsAnimals motorist2Type motorist3Type precipitatingEvent trafficControl eventID driverSeatBeltUse driverAge travelSpeed travelLane signPresence trafficControlDevice regulatorySignsNearSite schoolZoneSignsNearSite warningSignsNearSite weatherCondition weatherInfluence rollOver driverUsingCellPhonePriorToCrash lineOfSightClarity lineOfSightObstruction crashType preImpactIntent trafficSignalOperation activityPriorToCrash injurySeverity --
DOI: 10.15787/vtt1/rjtrtn
title: Toward a Better Understanding of Vulnerable Road User Safety Issues

description: Project Description Phase 1 of this research investigated the precursors of motor vehicle crashes and near crashes experienced by SHRP2 drivers involving bicyclists and pedestrians. We examined variables in the Trip and Event datasets as well as information in the SHRP2 database describing driver demographics, functional status, risk perception, and knowledge to determine which variables may account for significant variance in the likelihood of occurrence of these crash types. We also reviewed front camera video – in which only the roadway is visible, not the driver’s face – of each crash event. Phase 2 expanded and refined the methodology used in the Phase 1 exploratory analyses to examine the relationship between older drivers’ performance in freeway merging situations where ramps and acceleration lanes are characterized by more favorable (less demanding) versus less favorable (more demanding) highway design elements. We examined performance measures (kinematic data) for age-matched drivers with varying functional profiles who have each traversed a common set of ramps/acceleration lanes, and/or intersections, under known operating conditions, using a larger sample drawn from multiple SHRP2 sites. Planned analysis methods included between-groups comparisons (ANOVA) and regression modeling (using functional status to predict differences in kinematic measures). Data Request Scope For Phase 1.1, approximately 100 Events were identified according to criteria in Appendix A. Time series, speed limit, event, trip, and driver data and front video were extracted for each of these events. For Phase 1.2, additional driver information was requested for all drivers age 60 or over. For Phase 2, maneuvers of interest were identified at 27 intersections. Trip, driver, and time series data and front video were extracted separately for 1) the time period 15 seconds before entry to the Reference Link ID and 2) the time period 15 seconds after exit of the Reference Link ID. See Appendix A for more details. Data Specification See Appendix A. --
DOI: 10.15787/vtt1/u2bhwd
title: An Examination of Driver and Situational Factors that Affect Driver Red Light Running and Go/No-Go Dilemma-Zone Decisions at High-Speed Signalized Intersections

description: Project Description The ultimate goal of this project was to support the development of countermeasures to mitigate red-light running events. The findings from this project could potentially be used to provide guidance for design and/or implementation of countermeasures which would be of high value for safety practitioners and traffic operations staff at the State and local level. Data Request Scope The dataset contains data from traversals of roadway segments within the dilemma zones of intersections with different characteristics. Data Specification The dataset includes variables reflecting specific driver, situational, location-specific, and environmental factors that influence driver decisions in the dilemma zone. Summary data from 41628 traversals through 29 selected intersections (25 columns), and timeseries data from 328 selected traversal epochs (27 columns).
DOI: 10.15787/vtt1/u7cshn
title: Inferring cognitive workload and crash risk from naturalistic driving data

description: Project Description This dataset supported the study toidentify the factors that are potentially relevant to cognitive workload and crash risk. Data Request Scope This dataset contains The event data for all the crash, near-crash and baseline. Driver Questionnaires Medical Conditions Medications Data Specification VTTI delivered to University of Toronto the following Variables: Event Table o Precipitating Event o Event Nature 1 o Incident Type 1 o Event Severity 1 o Crash Severity 1 o Event Nature 2 o Incident Type 2 o Event Severity 2 o Crash Severity 2 o Driver Behavior 1 o Driver Behavior 2 o Driver Behavior 3 o Driver Impairments o Front Seat Passengers o Rear Seat Passengers o Secondary Task 1 o Secondary Task 1 Start Time o Secondary Task 1 End Time o Secondary Task 1 Outcome o Secondary Task 2 o Secondary Task 2 Start Time o Secondary Task 2 End Time o Secondary Task 2 Outcome o Secondary Task 3 o Secondary Task 3 Start Time o Secondary Task 3 End Time o Secondary Task 3 Outcome o Vehicle Contributing Factors o Infrastructure o Visual Obstructions o Lighting o Weather o Surface Condition o Traffic Flow o Contiguous Travel Lanes o Through Travel Lanes o V1 Lane Occupied o Traffic Density o Traffic Control o Relation to Junction o Intersection Influence o Alignment o Grade o Locality o Construction Zone o Number of Other Motorists/Non-Motorists o Number of Objects/Animals Driver Questionnaires o Gender o Age Group o Average Annual Miles o Years Driving o Training o Number of Violations o Number of Crashes o Crash 1 Severity o Crash 1 Fault o Crash 2 Severity o Crash 2 Fault o Acuity Medical Conditions Medications (all variables from InSight)
DOI: 10.15787/vtt1/ul4fic
title: Geometric Design Speed Characteristics on Freeway Ramps

description: Project Description This study examines driving data on freeway ramps from the SHRP2 NDS - speed profiles along with selected driver and vehicle variables - and compared that data to the design characteristics of the ramps traveled during the study. In addition to the SHRP2 data, the research uses detailed information from the road agencies in the SHRP2 participating states (New York, Indiana, Florida, North Carolina, and Washington) to document the ramps' design characteristics. The objective of the comparison was to identify relationships between the factors used to select freeway ramp design speed (e.g., radius, superelevation, etc.) and the actual speeds of drivers traveling on those ramps and their associated behaviors (e.g., brake/accelerator use, steering wheel angle, etc.). The findings from the comparison will then be further compared to the findings from recent research to identify similarities, differences, and potential topics for future research or considerations for changes to existing design guidance. Data Request Scope The delivered data includes 10,834 CSV files of timeseries data. Data Specification Timeseries variables: System.Time_Stamp vtti.timestamp vtti.file_id vtti.abs vtti.accel_x vtti.accel_y vtti.accel_z vtti.esc vtti.gyro_x vtti.gyro_y vtti.gyro_z vtti.lane_width vtti.left_marker_probability vtti.odometer vtti.pedal_brake_state vtti.pedal_gas_position vtti.right_marker_probability vtti.speed_gps vtti.speed_network vtti.steering_wheel_position vtti.traction_control_state --
DOI: 10.15787/vtt1/xrzdvp
title: Evaluating Relationships Between Perception-Reaction Times, Emergency Deceleration Rates, and Crash Outcomes using Naturalistic Driving Data

description: Project Description This dataset was created to enable an analysis by South Dakota State University of the relationships among operating speed, perception-reaction time, and deceleration rate. Data Request Scope The data set consists 4,237 crash and near-crash events available on InSight v2.1.1. Data Specification Requested elements include questionnaire data, vehicle data, event details, and kinematic data. Latitude and longitude was only provided for near-crash events that did not occur near the trip origin. For a complete list of InSight variables delivered, please see DriverAndVehicle_DataDictionary.pdf. For a complete list of Time Series variables delivered, please see TimeSeries_DataDictionary.pdf.
DOI: 10.15787/vtt1/zsqbgc
title: Using the New SHRP2 Naturalistic Driving Study Safety Databases to Examine Safety Concerns for Older Drivers

description: Project Description This project focuses on older drivers' navigation of signalized intersections, including when turning. Drivers 65 years of age and older account for a disproportionate number of traffic crashes and fatalities. This project uses SHRP2 data to better understand older drivers' behavior at signalized intersections, both when they are turning, especially their left turns, and when they go straight through intersections. Data Request Scope The data provided includes 18 CSV files of questionaire and summary data, 604 CSV files of timeseries data, and 595 MP4 files of video epochs. Data Specification Time series variables: System.Time_Stamp vtti.timestamp vtti.file_id vtti.abs vtti.accel_x vtti.accel_y vtti.accel_z vtti.gyro_z vtti.pedal_brake_state vtti.speed_gps vtti.speed_network vtti.steering_wheel_position vtti.turn_signal vtti.video_frame
DOI: 10.15787/vtt1/3aiac7
title: Analysis of SHRP2 Data to Understand Normal and Abnormal Driving Behavior in Work Zones; FHWA

description: Project Description The goal of this research is to develop a new analytical approach to understanding driving behavior and its relationship to safety. We are applying these methods to understanding driver behavior in work zones. Data Request Scope The project consists of 3 phases (see attached appendix). Phase 1: consists of all time series variables and front video for 71 work-zone crashes and near-crashes from the SHRP 2 NDS. Phase 2.1: consists of front video from 52 crashes and near-crashes of interest, which were used to identify start and end times for locations of interest. Phase 2.2: consists of all time series variables and front video for trips matched to the the locations identified in Phase 2.1. Matching was done based on criteria specified by data recipient. Phase 2.3: consists of 600 additional events (approximately 2 minutes each). Phase 3: consists of time series and speed limit data for 50 crash events and 400 normative baseline events. Data Specification See attached appendix for details.
DOI: 10.15787/vtt1/3fq4gc
title: Naturalistic Investigation of Contributing Factors by Crash Type

description: Project Description In this project we intend to analyze the role that a variety of contributing factors play in crash risk across crash types to determine whether significant interactions exist. We will compare the interplay between factors (such as specific driver behaviors) and crash type (such as rear-end or backing crashes) using logistic regression, factor/component analysis, and/or nonparametric methods. Data Request Scope In order to effectively analyze the relative risk of a variety of contributing cash factors, we request previously-reduced and kinematic data for all crashes of level 1 - 3 in the SHRP2 dataset, along with baselines. Data Specification Participant ID Event ID Age group Site (six states) Gender Incident type 1 2 Traffic density Surface condition Infrastructure Visual obstruction Traffic flow Traffic control Relation to junctoin Intersection influence Alignment Grade Locality Construction zone Weather Lighting Event severity 1 Event severity 2 Crash severity 1 Crash severity 2 At fault status Secondary task 1 Secondary task 2 Secondary task 3 Driver behavior 1 Driver behavior 2 Driver behavior 3 Driver impairment
DOI: 10.25345/c54j21
title: MassIVE MSV000085760 - Metabolome dynamics associated with CLAD disease progression
title: This project is about an untargeted metabolomic analysis in samples that come from chronic lung allograft dysfunction disease patients.
DOI: 10.18141/1465116
title: SACROC CMG model

description: This model was built for simulating CO2-EOR at the SACROC northern platform.
DOI: 10.18141/1465140
title: History, Sampling, Porosity and Permeability Testing of the Salem Limestone, Oriskany Sandstone and Marcellus Shale

description: Carbon Storage TRS
DOI: 10.18141/1468399
title: Computed Tomography Scanning and Geophysical Measurements of the Rogersville Shale from the Smith #1 Well

description: UCR TRS
DOI: 10.18141/1471662
title: Computed Tomography Scanning and Geophysical Measurements of the Marcellus Formation from the Armstrong #1 Well

description: UCR TRS
DOI: 10.18141/1474110
title: NATCARB

description: The National Carbon Sequestration Database (NATCARB) is a geographic information system (GIS)-based tool for viewing carbon capture, use and storage (CCUS) potential across the United States. Through a graphical user interface, NATCARB displays locations and associated metadata about stationary CO2 sources and potential geologic sinks. Users can access, query and model, analyze, display, and download CO2 storage resource data.
DOI: 10.18141/1475587
title: An Investigation into Solution Verification for CFD-DEM

description: ARS TRS