Find research datasets worth reusing

opencc-bySep 2019View details →

Martin Lane Oven Safe

A mysterious object on the south side of an exterior building wall on Martin Lane, near Monument, London. It is on the side wall of The Olde Wine Shades, one of few buildings to survive the Great Fire of London. It was once possibly a safe or bread oven but nobody is really sure. Date: unknown. There is a good blog on it here: https://lookup.london/martin-lane-oven-safe/ 238 photos taken in September 2019 with a Sony a6000 and processed in Agisoft Metashape. Source: Objaverse 1.0 / Sketchfab

opencc-bySep 2020View details →

Seven Stars Brick Lane

The Seven Stars is a derelict pub and now street art destination on Brick Lane, London. https://pubwiki.co.uk/LondonPubs/Spitalfield/SevenStars.shtml Date: 1937 (rebuilt). 605 photos taken in September 2020 with a Sony a6000 and processed in Reality Capture. Second floor and roof removed for simplicity. Source: Objaverse 1.0 / Sketchfab

opencc-byMar 2019View details →

Burrells-lane-window-detail-obj-simp

A window from an old building which is long gone, just the front wall left. It is located in Burrells Lane in Glasgow which is a steep lane joining High Street and Duke Street. Source: Objaverse 1.0 / Sketchfab

opencc-byJan 2019View details →

Drinking Fountain Carter Lane

The St. Lawrence & Mary Magdalene Drinking Fountain on Carter Lane opposite St Paul's Cathedral, London. Originally it stood in Guildhall Yard. The gold cross on the top is not shown in this scan. Date: 1866. http://www.mdfcta.co.uk/details-f/f148.html Photos taken January 2019 with a sony a6000 and processed in Agisoft Metashape. Source: Objaverse 1.0 / Sketchfab

opencc-byNov 2021View details →

Foster Lane Roman Mosaic

A small section of Roman mosaic mounted in a frame on a wall in a courtyard off Foster Lane next to St Vedast alias Foster Church, London. The mosaic was found below the floor of St Matthew Friday Street (demolished 1886). 108 photos taken in November 2021 with a Sony a7R III and processed in Reality Capture. Source: Objaverse 1.0 / Sketchfab

opencc-by-4.0Jul 2024View details →

Northern and central Walker Lane horizontal velocities in North America and Sierra Nevada reference frames.

The data in this file contains east and north velocities covering the northern and central sections of the Walker Lane, USA. The velocities were obtained from GPS time series, available at Nevada Geodetic Laboratory (NGL): http://geodesy.unr.edu/NGLStationPages/gpsnetmap/GPSNetMap.html (24 hour final solutions). The position time series were manually screened and corrected for offsets, and a local common-mode filter was applied following the methodology of Kreemer & Blewitt (2021, https://doi.org/10.1007/s00190-020-01466-5). Velocities in the North America frame were obtained using MIDAS, a robust median trend estimator (Blewitt et al., 2016,  https://doi.org/10.1002/2015JB012552). Two sets of stations were used to rotate the velocities into the Sierra Nevada frame: CAOV, CAPV, P140, P276, P310 for the northern section and CMBB, P245, P305, P308, P512 for the central section. The file contains the following columns: <ul> <li>sta: station ID</li> <li>lon: longitude of station (decimal degree)</li> <li>lat: latitude of station (decimal degree)</li> <li>ve_NA: east velocity in North America frame (mm/yr)</li> <li>vn_NA: north velocity in North America frame (mm/yr)  </li> <li>ve_SN: east velocity in Sierra Nevada frame (mm/yr)  </li> <li>vn_SN: north velocity in Sierra Nevada frame (mm/yr)  </li> <li>region: denotes whether the set of stations used to rotate the velocities into the Sierra Nevada frame are located in the northern (N) or central  (C) Walker Lane</li> <li>sve: east velocity uncertainty (mm/yr)</li> <li> svn: north velocity uncertainty (mm/yr)</li> <li>network: who operates the station</li> </ul>

opencc-by-4.0Aug 2019View details →

Automated Truck Lanes in Urban Area for Through and Cross Border Traffic

Autonomous trucks will soon be operational across our nation’s roadways. Yet, it is unclear how the design of our highway infrastructure should be modified to accommodate autonomous trucks, to enable them to operate in such a way to maximize the economic, capacity and safety benefits. The University of Texas at El Paso (UTEP) is proposing to develop and demonstrate, through microscopic traffic simulations, the concept of operations of autonomous truck lanes along the interstate freeways. Using the I-10 Freeway in the El Paso, TX region as the testbed, the research team will: (i) assess the existing structural, geometric and traffic designs in handling fully automated trucks, including the entrances, exits, and connectors; (ii) perform microscopic traffic simulations at critical locations to demonstrate design issues and the recommended design improvements; (iii) conduct a preliminary cost estimation on such infrastructure improvements.

opencc-by-4.0Nov 2022View details →

ES-PT, Advanced driving, Complex manoeuvres: lane merge

Use Case Category: Advanced Driving User Story: Complex manoeuvres in cross-border settings Location: Spain-Portugal (ES-PT) cross-border corridor According to 3GPP TS 22.186 R16, Advanced Driving “enables semi-automated or fully-automated driving. Longer inter-vehicle distance is assumed. Each vehicle and/or Road Side Unit (RSU) shares data obtained from its local sensors with vehicles in proximity, thus allowing vehicles to coordinate their trajectories or manoeuvres. In addition, each vehicle shares its driving intention with vehicles in proximity. The benefits of this use case group are safer traveling, collision avoidance, and improved traffic efficiency”. Scenario 1: Lane merge for automated vehicles: This scenario manages the situation where automated vehicles are in a lane merge scenario, analysing the traffic flow of the target lane. In this way, the system can detect existing vehicles including their lane position, acceleration, speed, size, etc. providing an extended perception layer, which is taken into account by the automated vehicle to determine the best merge manoeuvre according to the current situation. Vehicles in the lane to be merged are connected vehicles that share their vehicle data with the use of a Communication Unit with 5G capabilities and through a MEC Node. Road sensing technologies, such as traffic radars, are also used to detect the presence of vehicles in the target lane and to transmit their position and speed to the automated vehicle. Automated vehicle uses the Communication Unit as well in order to receive the information sent by surrounded vehicles and the road-side infrastructure, and therefore determine the status of the lane merge and the best way to operate to success in a safe and comfortable lane merge.

opencc-by-4.0Apr 2023View details →

Bioacoustic Sample Dataset from Lane County, Oregon, USA

Roughly 10.5 hours of bioacoustic recordings made in Lane County, Oregon, USA in May 2019. The audio was recorded in two blocks of four 1-hour recordings centered around sunrise and sunset and 10-minute recordings on the hour outside of these blocks. The audio contains vocalizations of various species of birds and mammals as well as sounds from insects and logging activity. These sounds have not been annotated. This is provided as a sample dataset to help users become familiar with the use of audio processing software and common bioacoustics workflows. The files are organized in a folder representing the study site (COA_22108 = Oregon Coast Range bioacoustic monitoring hexagon 22108) with a subfolder representing the recording station (Stn_1). Filenames encode the study area, field site, recording station, date (YYYYMMDD), and time at the start of each recording (HHMMSS, 24-hour time, PST). Recordings were made using a Wildlife Acoustics Song Meter SM4 automated recording unit with the following parameters: Format: WAV Channels: 1 Sample rate: 32 kHz Encoding: 16-bit signed integer PCM

opencc-by-4.0Dec 2022View details →

Testing autonomous vehicle lane keeping assist system in BeamNG simulator

In this video, you can see some of the failures revealed while testing the driving agent on various road topologies in BeamNG simulator. Road topologies were generated by our tool RIGAA (available at: <a href="https://zenodo.org/record/8242223">Reinforcement learning informed evolutionary search for autonomous systems testing | Zenodo</a>)

opencc-by-4.0Sep 2023View details →

MCMC chains representing stellar halo fits for Lane et al. (2023) paper published in MNRAS

Results for the paper entitled "The stellar mass of the Gaia-Sausage/Enceladus accretion remnant" published in MNRAS by Lane, Bovy, & Mackereth. The results are in the form of MCMC posterior chains, which are used to generate the results recorded in Table 1 of the manuscript. The process used to generate these data is outlined in section 2 (data & sample preparation), section 3 (Density modelling framework), and section 4 (Presentation of results) of the manuscript. The data are contained within a single gzipped .tar file, organized in two directories: gse/ containing the results for fits to the GS/E kinematic samples, and all/ containing the results for the fits to the whole halo sample. In the gse/ directory, there are three directories: eLz/, AD/, and JRLz/, containing the results for the fits to each of the respective kinematically defined subsamples. Within these directories, as well as within all/, are a final set of directories for each of the eight density profiles considered in the work. Within each of these directories are a single file named "samples.npy" which is a binary file (see <a href="https://numpy.org/doc/stable/reference/generated/numpy.lib.format.html#module-numpy.lib.format">this link</a> for format information) containing a numpy array of shape (# of parameters, # of posterior samples). The number of posterior samples is the number of walkers (100) times the number of samples per walker (10,000), minus the number of burn-in steps per walker (1,000) = 900,000. The number of parameters can be inferred from the density profiles definitions in section 3 of the manuscript, and the ordering of the parameters is the same as in Table 1. The units of the parameters are as in Table 1, except for the parameters theta and phi which are scaled such that they are defined on the interval (0,1), representing the intervals (0,2pi) and (0,pi) respectively.

opencc-by-4.0Oct 2023View details →

Simulation of an Agile Automotive Assembly Lane

General Description The provided collection of datasets comprises 14 simulated event logs of an flexible automotive assembly lane. Each event log is stored in a csv-file that can be easily converted to other standards such as the eXtensible Event Stream (XES) standard. For a more detailed explanation, we refer to the provided supplementary document.   Simulation Starting from a base model, 13 different scenarios were implemented that cover changes in processing times, station operator availability, operator efficiency, or bottlenecks in the supply chain. Each scenario was implemented in CPN Tools and, in addition to the event log, we also provide the respective simulation model and configurations.   Acknowledgements Funded under the Excellence Strategy of the Federal Government and the Länder. Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy - EXC-2023 Internet of Production - 390621612. We also thank the Alexander von Humboldt (AvH) Stiftung for supporting our research.

dryad36/100

Surviving in the fast lane: No increased mortality, but faster growth for pathogen-exposed larvae of a family living beetle

Open the record for dataset details and reuse information.

publicOct 2025View details →

H. J. Andrews Experimental Forest site, station Lane County, OR (FIPS 41039), study of county area in units of squareKilometers on a yearly timescale

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from H. J. Andrews Experimental Forest (AND) contains county area measurements in squareKilometers units and were aggregated to a yearly timescale.

H. J. Andrews Experimental Forest site, station Lane County, OR (FIPS 41039), study of number of farms in units of number on a yearly timescale

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from H. J. Andrews Experimental Forest (AND) contains number of farms measurements in number units and were aggregated to a yearly timescale.

H. J. Andrews Experimental Forest site, station Lane County, OR (FIPS 41039), study of farmland acres (total) in units of acre on a yearly timescale

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from H. J. Andrews Experimental Forest (AND) contains farmland acres (total) measurements in acre units and were aggregated to a yearly timescale.

H. J. Andrews Experimental Forest site, station Lane County, OR (FIPS 41039), study of population employed in commerce (percent of total) in units of percent on a yearly timescale

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from H. J. Andrews Experimental Forest (AND) contains population employed in commerce (percent of total) measurements in percent units and were aggregated to a yearly timescale.

H. J. Andrews Experimental Forest site, station Lane County, OR (FIPS 41039), study of population employed at farms (percent of total) in units of percent on a yearly timescale

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from H. J. Andrews Experimental Forest (AND) contains population employed at farms (percent of total) measurements in percent units and were aggregated to a yearly timescale.

H. J. Andrews Experimental Forest site, station Lane County, OR (FIPS 41039), study of population employed in manufacturing (percent of total) in units of percent on a yearly timescale

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from H. J. Andrews Experimental Forest (AND) contains population employed in manufacturing (percent of total) measurements in percent units and were aggregated to a yearly timescale.

H. J. Andrews Experimental Forest site, station Lane County, OR (FIPS 41039), study of population employed in service (percent of total) in units of percent on a yearly timescale

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from H. J. Andrews Experimental Forest (AND) contains population employed in service (percent of total) measurements in percent units and were aggregated to a yearly timescale.