cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5066/f7nc5zb8
title: Liquefaction observations from ten earthquakes in the US, Japan, China, and Taiwan

description: These data include observations of liquefaction from ten earthquakes. The data are provided as a feature collection in a GeoJSON file format. Individual features are either points or polygons. Each feature has a single attribute called "earthquake" which gives the name and year of the earthquake associated with the liquefaction feature.
DOI: 10.20350/digitalcsic/7387
title: Accuracy, efficiency, productivity and researchers’ satisfaction in digital humanities data analysis: Experiment design

description: This documental appendix presents form-based materials employed in order to carry out emppricial studies aboput data analysis performance in digital humanities research contexts. The document includes questionnaires examples for obtaining personal and professional profile of the subjects, as well as data analysis tasks defined in two different case studies in digital humanities that allowed us to measure accuracy, efficiency, productivity and researchers' satisfaction during data analysis performance experiments.
description: Data analysis represents the most important group of tasks carried out in research contexts. Due to the current lack of empirical studies about data analysis performance in digital humanities research contexts, we conducted an empirical experiment comparing data analysis performance employed traditional software versus data analysis performance employed software-assistance tools which incorporate cognitive processes in their design. The experiment is designed in terms of accuracy, efficiency, productivity and user satisfaction during the data analysis made by researchers in digital humanities. This documental appendix presents all the materials created and employed for the empirical experiment presented, including the original forms to obtain information regarding the personal and professional profile of the subjects, as well as data analysis tasks defined in two different case studies in digital humanities that allowed us to measure 4 metrics: accuracy (in terms of correctness of the subjects' responses), efficiency (in terms of the time employed by subjects in performed each task), productivity (as a accuracy/efficiency ratio) and researchers’ satisfaction ( The instrument employed is a questionnaire based on Moody’s framework, which evaluates satisfaction based on three concepts: Perceived Usefulness (PU), Perceived Ease of Use (PEOU) and Intention to Use (ITU) in a 5-point Likert scale). The materials can be easily reusable or take as a basis for similar experiments about data analysis performance in digital humanities research contexts.
DOI: 10.20350/digitalcsic/7388
title: An experiment on accuracy, efficiency, productivity and researchers’ satisfaction in digital humanities data analysis: dataset appendix

description: Data analysis represents the most important group of tasks carried out in research contexts. Due to the current lack of empirical studies about data analysis performance in digital humanities research contexts, we conducted an empirical experiment comparing data analysis performance employed traditional software versus data analysis performance employed software-assistance tools which incorporate cognitive processes in their design. The experiment is designed in terms of accuracy, efficiency, productivity and user satisfaction during the data analysis made by researchers in digital humanities. It allowed us to find some clear benefits of the cognitive inclusion in the software designed for research contexts, with statistically significant differences in terms of accuracy, productivity and researcher’s satisfaction in support of this explicit inclusion, although some efficiency weaknesses are detected. This dataset presents the raw data obtained during the first round of our experiment, with a total of 16 subjects and 32 responses randomly collected as sample. The dataset also contains the results of the statistical analysis performed using a repeated measures experimental design in a mixed lineal model.
description: This dataset contains information regarding a performance experiment carried out in order to assess the data analysis process perform by digital humanitites scholars in research contexts. The datasets contains raw data obtained during the experiment, as well as the statistical analysis of the results using a repeated measures experimental design in a mixed lineal model.
DOI: 10.14469/hpc/1845
title: ionic, NN contraction + NMe3 to sequester proton, TS,Me-OPh, tert-butyl

description: Gaussian Calculation
DOI: 10.14469/hpc/1846
title: Conf7, TPSSh/6-311g(2df,p) nstates=120

description: Gaussian Calculation
DOI: 10.14469/hpc/1847
title: Conf6, TPSSh/6-311g(2df,p) nstates=150

description: Gaussian Calculation
DOI: 10.14469/hpc/1848
title: Conf5, TPSSh/6-311g(2df,p) nstates=150

description: Gaussian Calculation
DOI: 10.5066/f7s180nn
title: Miscellaneous flow discharge measurements collected downstream of Brandon Road Lock and Dam

description: Flow discharges were measured in the Des Plaines River from approximately river mile 286 to river mile 284 on October 1921, 2015 using Teledyne Rio Grande 1200 kHz acoustic Doppler current profilers (ADCP). The data were georeferenced with differential GPS receivers with submeter accuracy. These flow discharge measurements were collected in support of the US Army Corps of Engineers Great Lakes and Mississippi River Interbasin Study (GLMRIS), and were concurrent with a dye-tracing study. The discharge measurements included here were collected in the following locations: 1. immediately upstream, across, and immediately downstream of the NRG Energy Joliet Power Station right descending bank intake (North Intake) 2. immediately upstream, across, and immediately downstream of the NRG Energy Joliet Power Station left descending bank intake (South Intake) 3. immediately upstream, across, and immediately downstream of the NRG Energy Joliet Power Station right descending bank outfall (North Outfall) 4. across the NRG Energy Joliet Power Station left descending bank outfall (South Outfall) ADCP data were collected and initially reviewed in the WinRiver II software. Final review of discharge measurements was completed using the QRev discharge computation and review software (Mueller, 2016). The output from QRev includes an XML document with the processed results, and is included here. A stylesheet (XLS) file is also included to enable easy viewing of the QRev processed results. Note that additional discharge measurements associated with the dye-tracing study were taken at the existing US Geological Gaging Station, Des Plaines River in Lock Channel at Rockdale, IL (05538020), and can be accessed with the links below. A KMZ archive containing the locations of the ADCP shiptracks for each discharge measurement are included, along with an associated metadata file. Mueller, D.S., 2016, QRevSoftware for computation and quality assurance of acoustic Doppler current profiler moving-boat streamflow measurementsUsers manual for version 2.8: U.S. Geological Survey Open-File Report 20161052, 50 p., http://dx.doi.org/10.3133/ofr20161052.
DOI: 10.14469/hpc/1849
title: Conf8, TPSSh/6-311g(2df,p) nstates=120

description: Gaussian Calculation
DOI: 10.15787/vtt1/eeegnd
title: Driver Behavior in Horizontal Curves

description: Project Description The high rate of collisions on horizontal curves compared to other roadway elements makes them one of the most critical elements in transportation networks. This study aims at overcoming some of the problems associated with the current horizontal curve design approach. This dataset includes variables that define the movement of the vehicle and driver behavior when approaching and traversing horizontal curves. This dataset contains time series data for 4,598 traversals over 42 specified curves on rural arterial highways during specified time periods of interest. It also contains driver demographic and vehicle data for drivers and vehicles identified in the time series data. Data Request Scope/Specification This dataset contains the following time series information on trips passing through the selected curves during time periods of interest: File id (unique identifier for each data file) Time (time stamp; in ms from the start of the file) Date (day of week, month, year) Location (latitude, longitude) Longitudinal acceleration Lateral acceleration Speed of vehicle (network, if available, and GPS) Headway (time) and range for lead vehicles Brake state Steering wheel angle Number of satellites Light level This dataset also contains the following Driver, Vehicle, and Curve Traversal information for any vehicle/driver/traversal identified in the time series data: DRIVER: Anonymous Driver ID Age Group Gender Profession Years Driving VEHICLE: Anonymous Vehicle ID Vehicle type (e.g., passenger car, SUV) TRAVERSAL: Event id (unique identifier used for this project only) File id Start and end link id Start and end timestamp Anonymous Driver ID Anonymous Vehicle ID Trip Start Hour Link Start Hour Day of Month Month
DOI: 10.15787/vtt1/lkno2x
title: MRI Global S08 Phase 2 Left Turn Data

description: Data Request Scope A dataset containing forward and rearward video, time series variables, and participant demographic data for left turn events from major to minor roads. There are 1,434 left turn events across 59 different signalized intersections included in the data set, along with 321 left turn events across 15 unsignalized intersections. Intersection characteristics, such as speed limit and turn lane offset, are also included. Data Specification Dataset/Forward and rearward video (H264 encoded with mp4 wrapper), csv files for time series variables, xls files for participant demographic information, xlsx file for data dictionary.
DOI: 10.15787/vtt1/bpy3dq
title: VTTI: SHRP 2 Phase I Efforts - Standardization and Export of Training Dataset – Development of Data Repository

description: Project Description The purpose of this dataset is not to conduct research but to help researchers understand the driving related variables that are available in the second Strategic Highway Research Program (SHRP2) Naturalistic Driving Study (NDS). The data can also be useful for algorithm development and testing prior to running algorithms over all or part of the SHRP2 NDS dataset. The dataset was designed with the purpose of not requiring institutional review board (IRB) approval, and includes personally identifying information, including face video, and start and stop locations that can be openly shared. For this reason it cannot be used for research and should be thought of only as a training dataset. It resides on the InSight website and is available for download at no cost to qualified users. The focus of this effort was the time series data and video collected from the data acquisition system (DAS) that resides on the vehicle, including radar. Three vehicles from the Virginia Tech Transportation Institute (VTTI) fleet were driven from Blacksburg, VA to Durham, North Carolina to collect data on the same roads included in the roadway information database (RID). Data Request Scope Data were collected for one week and include approximately 100 trips and more than 2,500 vehicle miles. Since this was a limited data collection effort in which finding a naturally occurring scenario of interest was unlikely, several common events of interest were staged. The time of each staged scenario was documented. The following scenarios were included: Hard braking, Short headway, Low time to collision, High lateral acceleration, Vehicle cut in, and Flying pass. Data Specification Data were processed in the same way as for the original SHRP2 NDS including: the video processing, map matching to the RID, and the post processing done on the radar. It is downloadable in a 10 Hertz synchronized format. Access to the video is provided with each individual camera view separated and processed in the same manner as the main SHRP2 NDS dataset. The map matching yielded a heat map showing the trips driven on each road including origin and destination (i.e., does not require the current PII protection placed on the SHRP2 NDS). Therefore each trip is shown on the heat map from beginning to end.
DOI: 10.15787/vtt1/s1mwnf
title: Research Utilizing the SHRP2 Safety Data to Support Highway Safety

description: Project Description The purpose of this project was to provide new information on driver behavior that could be used to improve HVE programs to reduce speeding and aggressive driving behavior and thereby improve highway safety. Data Request Scope This dataset contains data for trips passing through specific High Visibility Highway Safety Enforcement Program (HVE) areas over specific time periods. CUBRC, Inc. provided the roadway link IDs and periods of time; VTTI returned the trip-level data about all trips over those links during those time periods, including participant and vehicle data. CUBRC used this trip-level data to select 589 trips for further analysis. VTTI then provided time-series data and forward video for these trips as well as participant survey responses for all drivers associated with the trips identified. Data Specification See dictionaries attached below.
DOI: 10.15787/vtt1/ss1ubm
title: Analysis of SHP2 Naturalistic Driving Study Data: Safer Glances, Driver Inattention, and Crash Risk

description: Project Description This work was sponsored by the Transportation Research Board. The purpose of this research is to develop a statistically validated set of inattention-risk functions describing how an increase in inattention performance leads to increased risk in lead-vehicle-pre-crash scenarios. And also with this relationship to identify which set of glance behaviors are safer than others. Data Request Scope The dataset delivered contains events of lead-vehicle crashes, near crashes and associated comparison conditions (baselines).The study has 2 phases. As the part of phase 1 the dataset delivered has 13 events obtained from the SHRP2 Naturalistic Driving Study (NDS) database: 4 rear-end crashes, 5 near crashes, and 4 baseline events. For phase 2 the dataset delivered had a total of 768 events of 268 crashes/near crashes and 520 baselines. Data Specification The dataset delivered had event data(crashes/near crashes), baseline data, majority of the time series data, rear and forward video data for (50-60) sec, demographics and driving history of the participants and crash interviews. The event data includes driver behavior data for eye glance variables, variables that describe the visual information that drivers rely on to initiate and control braking (called optical parameters) and measures of event severity.
DOI: 10.5281/zenodo.3922131
title: Datensatz: Recruiting aus Sicht der Bewerber_innen - Ein Vergleich klassischer und neuartiger digitaler Methoden im Personalmarketing

description: Datensatz inkl. Codebuch der Studie "Recruiting aus Sicht der Bewerber_innen - Ein Vergleich klassischer und neuartiger digitaler Methoden im Personalmarketing".
DOI: 10.5281/zenodo.3922130
title: Datensatz: Recruiting aus Sicht der Bewerber_innen - Ein Vergleich klassischer und neuartiger digitaler Methoden im Personalmarketing

description: Datensatz inkl. Codebuch der Studie "Recruiting aus Sicht der Bewerber_innen - Ein Vergleich klassischer und neuartiger digitaler Methoden im Personalmarketing".
DOI: 10.15787/vtt1/bg8ksz
title: Examining Drivers' Risk Perception and its Deviation from Reality

description: Project Description This research study examined how driver characteristics play a prominent role in compliance/non-compliance of traffic rules. Data Request Scope The following topics were investigated: (i) how the risk perceptions of violating traffic rules vary by driver characteristics such as gender, age group, ethnicity, education, marital status, work status, income, knowledge of rules, and miles driven, and, (ii) how different are the drivers' risk perceptions from the reality. The dataset received used the survey responses under the SHRP2 NDS study. Data Specification The variables from the Driver Demographic Questionnaire consisting of 3593 records and Risk Perception Questionnaire consisting of 3259 records were delivered to conduct the analysis. The two datasets were combined based on the participant id to examine the effect of driver characteristics on risk perception of traffic violations. The Site Name variable specifying the study site with which participant was associated was also provided.
DOI: 10.15787/vtt1/dafuh5
title: Mask Head Pose Validation Study Dataset

description: Project Description Driver head pose is an important factor in transportation safety research. As the scale of naturalistic driving studies has grown, it has become increasingly important to develop automated methods for estimating driver head pose. The objective of this study was to evaluate the capability of the currently deployed Virginia Tech Transportation Institute (VTTI) head pose estimation system (mask). To this end the following tasks were completed: Identified conditions in which the mask system estimated head pose accurately and precisely. Determined if the mask system quality confidence measure accurately identified cases in which head pose estimates should not be used. Evaluated the ability of the mask system to predict eye glance location and provide a course estimate of head pose. Identified system limitations that should be considered by researchers using mask head pose data. Data Request Scope Information and some public data about the study can also be accessed on the InSight website Overview documentation can be accessed here . Data Specification The following data elements are available: Eye glance data Front, Rear, Hands and Face video streams Facial landmark annotations Geometric method head rotation estimates Mask head rotation estimates Vehicle kinematics
DOI: 10.15787/vtt1/ecxiu1
title: Evaluating the Relationship between the Driver and Roadway to Address Rural Intersection Safety using the SHRP 2 Naturalistic Driving Study Data

description: Project Description This project observed driver behavior at rural intersection in order to better understand where drivers focus their attention, the role of distraction, the effectiveness of current countermeasures, roadway factors that lead to driver errors, and the impact of environmental factors on driver error. Data Request Scope All available driver and time series data for each intersection was requested. Data Specification Driver Survey Variables Driver age Gender Education level Annual miles driven Years of driving Number of moving violations Number of crashes DAS Variables ABS activation Acceleration, x-axis Acceleration, x-axis fast Acceleration, y-axis Acceleration, y-axis fast Acceleration, z-axis Acceleration, z-axis fast Airbag, driver Alcohol Cruise control Date (as described by VTTI this will include a measure of time of day, month, and year which is provided in a format so that it does reveal personally identifying information) Dilution of precision, position Time into trip (an approximate measure is acceptable if this is considered identifying, i.e. we would like something like 15 to 20 minutes from start of trip) Driver button flag Electronic stability control Elevation, GPS Head confidence Head position x Head position x baseline Head position y Head position y baseline Head position z Head position z baseline Headlight setting Illuminance, ambient Lane marking, distance, left Lane marking, distance, right Lane marking, probability, right Lane marking, type, left Lane marking, type, right Lane markings, probability, left Lane position offset Lane width Latitude Longitude Number of satellites Pedal, accelerator position Pedal, brake Pitch rate, y-axis Pitch rate, y-axis fast PRNDL Radar range rate forward x track n Radar range rate forward y track n Radar, target identification Roll rate, x-axis Roll rate, x-axis fast Seatbelt, driver Speed, GPS Speed, vehicle network Steering wheel position Timestamp Traction control Turn signal Video frame
DOI: 10.15787/vtt1/minaxo
title: IAP Project: Concept to Countermeasure- Research to Deployment Using the 2nd Strategic Highway Research Program (SHRP2) Naturalistic Driving Study (NDS) Data: The Interrelationships between Speed Limits’ Geometry and Driver Behavior

description: Project Description This research study was sponsored by Federal Highway Administration Implementation Assistance Program with funds flowing through the Michigan Department of Transportation. This study proposed to examine the rates of crash and near-crash events along freeway segments with various statutory speed limits. In addition to examining the naturalistic driving study (NDS) event data, additional support data will be obtained from the roadway information database (RID). Additionally, speed data will also be compared for select drivers over common freeway segments. The metrics to examine as a part of this effort will include the mean speed and speed variance for the same driver over various trips on the same segment, as well as for different drivers on these same segments. Data Request Scope The dataset delivered consisted of a sample of detailed event tables (including trip summaries, vehicle, and driver survey results) and time series variables collected for multiple drivers as part of the SHRP2 Naturalistic Driving Study. Time-series data (de-identified) was requested approximately for 300 near-crashes and 3700 baseline events. In particular, identified features of road geometry and driver behavior-related factors contributing to speed-related crashes/near crashes using data available from the InSight website were used to select relevant events (crashes, near-crashes, or baselines) on roads segments with “locality” type of “interstate/bypass/divided highway with no traffic signals” features. Data Specification The time series data included: vehicle trajectory data (e.g. latitude, longitude, speed, acceleration, and velocity) and vehicle control data (e.g., pedal gas position, pedal brake state steering wheel position). Additionally, a shape file of the travel density maps similar to those shown on the InSight website for all six states (FL, IN, NY, NC, PA, WA) including a layer with the number of trips and the number of drivers traversing each Link ID were added as well.
DOI: 10.15787/vtt1/nitezz
title: SwRI: Investigation of Techniques for Detecting Distracted Drivers Using SHRP2 Vehicle Data.

description: Project Description The motivation for creating the dataset was to enable SwRI to investigate the application of algorithms based on time series data to the prediction of a specific class of vehicle behavior. The work evaluated a set of measures for classifying streaming vehicle position data as to their ability to detect distracted driving. Data Request Scope SwRI received the majority of time series data (excluding GPS position and radar) for a total of 8880 crash, near crash, and baseline events where “Locality” was equal to either “Interstate/Bypass/Divided Highway with no traffic signals” or “Open Country.” The event duration was one minute prior and three seconds after an event of interest. Data was sampled at 10 Hz. SwRI also received the SHRP2 Insite website Event table variables corresponding to the events identified for the time series data. Data Specification See the dictionaries attached below.