Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
338
datasets available to search
ShareScore release 0.9.0
Dataset results
338 results for “gps”
GPS Location Spoofing Attack Detection for Enhancing the Security of Autonomous Vehicles (presentation video)
<p>Video of the presentation for the publication M. Kamal, A. Barua, C. Vitale, C. Laoudias and G. Ellinas, "GPS Location Spoofing Attack Detection for Enhancing the Security of Autonomous Vehicles," 2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall), 2021, pp. 1-7, doi: 10.1109/VTC2021-Fall52928.2021.9625567.</p>
GPS data for COPEX campaign carried out in 2002 in Brazil by INPE (Boa Vista Station)
<p>This repository provides the GPS data acquired in Boa Vista station during the Conjugate Point Equatorial Experiment (COPEX) campaign in 2002. In the folders it can find the raw intensity data (FSL file) and also the summary files (SUM files), containing only with S4 index with time and satellite ID. More information about the campaign can be found in Muella et al. (2008), Abdu et al. (2009) and de Paula et al. (2010). Information about the data recording format and reading extraction procedure of this dataset can be found in Appendix B of Beach (1998). More details regarding the receiver used and extraction tools can be found at: <a href="https://gps.ece.cornell.edu/tools.php">https://gps.ece.cornell.edu/tools.php</a></p> <p>Abdu, M. A., Batista, I. S., Reinisch, B. W., De Souza, J. R., Sobral, J. H. A., Pedersen, T. R., ... & Groves, K. M. (2009). Conjugate Point Equatorial Experiment (COPEX) campaign in Brazil: Electrodynamics highlights on spread F development conditions and day‐to‐day variability. Journal of Geophysical Research: Space Physics, 114(A4).</p> <p>Beach, T. L. (1998). Global Positioning System studies of equatorial scintillations. Cornell University.</p> <p>De Paula, E. R., Muella, M. T. A. H., Sobral, J. H. A., Abdu, M. A., Batista, I. S., Beach, T. L., & Groves, K. M. (2010). Magnetic conjugate point observations of kilometer and hundred‐meter scale irregularities and zonal drifts. Journal of Geophysical Research: Space Physics, 115(A8).</p> <p>Muella, M. T. A. H., De Paula, E. R., Kantor, I. J., Batista, I. S., Sobral, J. H. A., Abdu, M. A., ... & Smorigo, P. F. (2008). GPS L-band scintillations and ionospheric irregularity zonal drifts inferred at equatorial and low-latitude regions. Journal of Atmospheric and Solar-Terrestrial Physics, 70(10), 1261-1272.</p>
GPS data for COPEX campaign carried out in 2002 in Brazil by INPE (Campo Grande Station)
<p>This repository provides the GPS data acquired in Campo Grande station during the Conjugate Point Equatorial Experiment (COPEX) campaign in 2002. In the folders it can be found the raw intensity data (FSL file) and also the summary files (SUM files), containing only with S4 index with time and satellite ID. More information about the campaign can be found in Muella et al (2008), Abdu et al (2009) and de Paula et al (2010). Information about the data recording format and reading extraction procedure of this dataset can be found in Appendix B of Beach (1998). More details regarding the receiver used and extraction tools can be found at: <a href="https://gps.ece.cornell.edu/tools.php">https://gps.ece.cornell.edu/tools.php</a></p> <p>Abdu, M. A., Batista, I. S., Reinisch, B. W., De Souza, J. R., Sobral, J. H. A., Pedersen, T. R., ... & Groves, K. M. (2009). Conjugate Point Equatorial Experiment (COPEX) campaign in Brazil: Electrodynamics highlights on spread F development conditions and day‐to‐day variability. Journal of Geophysical Research: Space Physics, 114(A4).</p> <p>Beach, T. L. (1998). Global Positioning System studies of equatorial scintillations. Cornell University.</p> <p>De Paula, E. R., Muella, M. T. A. H., Sobral, J. H. A., Abdu, M. A., Batista, I. S., Beach, T. L., & Groves, K. M. (2010). Magnetic conjugate point observations of kilometer and hundred‐meter scale irregularities and zonal drifts. Journal of Geophysical Research: Space Physics, 115(A8).</p> <p>Muella, M. T. A. H., De Paula, E. R., Kantor, I. J., Batista, I. S., Sobral, J. H. A., Abdu, M. A., ... & Smorigo, P. F. (2008). GPS L-band scintillations and ionospheric irregularity zonal drifts inferred at equatorial and low-latitude regions. Journal of Atmospheric and Solar-Terrestrial Physics, 70(10), 1261-1272.</p>
GPS data for COPEX campaign carried out in 2002 in Brazil by INPE (Cachimbo Station)
<p>This repository provides the GPS data acquired in Cachimbo station during the Conjugate Point Equatorial Experiment (COPEX) campaign in 2002. In the folders it can find the raw intensity data (FSL file) and also the summary files (SUM files), containing only with S4 index with time and satellite ID. More information about the campaign can be found in Muella et al. (2008), Abdu et al. (2009) and de Paula et al. (2010). Information about the data recording format and reading extraction procedure of this dataset can be found in Appendix B of Beach (1998). More details regarding the receiver used and extraction tools can be found at: <a href="https://gps.ece.cornell.edu/tools.php">https://gps.ece.cornell.edu/tools.php</a></p> <p>Abdu, M. A., Batista, I. S., Reinisch, B. W., De Souza, J. R., Sobral, J. H. A., Pedersen, T. R., ... & Groves, K. M. (2009). Conjugate Point Equatorial Experiment (COPEX) campaign in Brazil: Electrodynamics highlights on spread F development conditions and day‐to‐day variability. Journal of Geophysical Research: Space Physics, 114(A4).</p> <p>Beach, T. L. (1998). Global Positioning System studies of equatorial scintillations. Cornell University.</p> <p>De Paula, E. R., Muella, M. T. A. H., Sobral, J. H. A., Abdu, M. A., Batista, I. S., Beach, T. L., & Groves, K. M. (2010). Magnetic conjugate point observations of kilometer and hundred‐meter scale irregularities and zonal drifts. Journal of Geophysical Research: Space Physics, 115(A8).</p> <p>Muella, M. T. A. H., De Paula, E. R., Kantor, I. J., Batista, I. S., Sobral, J. H. A., Abdu, M. A., ... & Smorigo, P. F. (2008). GPS L-band scintillations and ionospheric irregularity zonal drifts inferred at equatorial and low-latitude regions. Journal of Atmospheric and Solar-Terrestrial Physics, 70(10), 1261-1272.</p>
Interseismic and Coseismic Slip Behaviors Along the Tuolaishan-Lenglongling Faults From InSAR, GPS and Optical Observations
<p>This repository contains:</p> <p>(1) The coseismic horizontal displacements measured from Planet-Lab and Landsat-9 optical data in grd format. The matlab script (i.e., grdread2.m) can be used to read the data in grd format.</p> <p>(2) Interseismic fault-parallel and fault-norm veloctiy profiles projected by the east-west and north-south velocity maps, the vertical and InSAR-derived descening (Track 33) LOS velocity profiles perpendicular to the seismogenic fault of the 2022 Menyuan Mw 6.7 earthquake. The data in profile files is formated as longitude, latitude, velocity and fault-perpendicular distance.</p>
Spatial behavior and diet data for discrete-choice analyses: data observed and classified from GPS video camera collars worn by female members of the Fortymile Caribou Herd across Alaska, USA, and Yukon, Canada
<p>Competition for resources and space can drive forage selection of large herbivores from the bite through the landscape scale. Animal behavior and foraging patterns are also influenced by abiotic and biotic factors. Fine-scale mechanisms of density-dependent foraging at the bite scale are likely consistent with density-dependent behavioral patterns observed at broader scales, but few studies have directly tested this assertion. Here, we tested if space use intensity, a proxy of spatiotemporal density, affects foraging mechanisms at fine spatial scales similarly to density-dependent effects observed at broader scales in caribou. We specifically assessed how behavioral choices are affected by space use intensity and environmental processes using behavioral state and forage selection data from caribou (<i>Rangifer tarandus granti</i>) observed from GPS video-camera collars using a multivariate discrete-choice modeling framework. We found that the probability of eating shrubs increased with increasing caribou space use intensity and cover of <i>Salix</i> spp. shrubs, whereas the probability of eating lichen decreased. Insects also affected fine-scale foraging behavior by reducing the overall probability of eating. Strong eastward winds mitigated the negative effects of insects and resulted in higher probabilities of eating lichen. Lastly, caribou exhibited foraging functional responses wherein their probability of selecting each food type increased as the availability (% cover) of that food increased. Space use intensity signals of fine-scale foraging were consistent with density-dependent responses observed at larger scales and with recent evidence suggesting declining reproductive rates in the same caribou population. Our results highlight the potential risks of overgrazing on sensitive forage species such as lichen. Remote investigation of the functional responses of foraging behaviors provides exciting future applications where spatial models can identify high-quality habitats for conservation.</p>
RF recordings of GPS SVN49 broadcasting non-standard codes
<p>This dataset consists of several recordings of the L1 signal broadcasted by GPS<br> SVN49 between 2019-06-26 and 2019-06-28. This satellite broadcasts a<br> non-standard code as its L1 C/A signal, where the usual spread-spectrum PRN is<br> replaced by a PRN which consists of alternating zeros and ones (akin to a square<br> wave subcarrier). This produces strong spectral lines at +/-511.5kHz from the L1<br> centre frequency.</p> <p>The signal is modulated with a navigation message in the usual way using 50baud<br> BPSK.</p> <p>The recordings have been made with a LimeSDR using an external 10MHz GPSDO and a<br> small and inexpensive GPS patch antenna.</p> <p><strong>Included files</strong></p> <p>The .bin files contain waterfall data generated with STRF. This<br> data can be used to identify the satellite producing the signal using Doppler<br> measurements.</p> <p>The mjd58660.dat file contains Doppler measurements extracted with STRF.</p> <p>The .c64 files are IQ recordings of the upper sideband of<br> the modulation (centred at L1 + 511.5kHz). One of them is done at 5ksps and<br> another at 10ksps. The timestamp of the start of each recording is indicated in<br> the filename. The format is complex IQ data as 32-bit floats.</p>
ScintPi: A low-cost, easy-to-build GPS ionospheric scintillation monitor for DASI studies of space weather, education, and citizen science initiatives
<p>These data sets contain ionospheric scintillation (GPS L1) observations (S4 indices) collected by a ScintPi prototype during 2018 at a low magnetic latitude station (Presidente Prudente). ScintPi is a low-cost, easy-to-build GPS ionospheric scintillation monitor for DASI studies of space weather, education, and citizen science initiatives.</p> <p>The file named "ScintPi_PPR_S4_2018.mat" contains S4 values (s4mat) for 2018 as a function of universal time (utmat), day-of-year (doymat), GPS satellite identifier number (prnmat), GPS satellite elevation (elmat) and azimuth (azmat) angles.</p> <p>The file named "ScintPi_PPR_20180211.mat" contains example raw (10 Hz) measurements made by ScintPi on February 11, 2018. The file contains values of receiver's altitude, latitude and longitude (variables alt,lat, and lon), GPS satellite azimuth and elevation (variables el and az), GPS identifier number (prn), signal-to-noise ratio (snr), and day-of-year (doy).</p>
The North American Monsoon GPS Hydrometeorological Network 2017: Flux and Precipitation Data
<p>Water, energy and carbon fluxes and ancillary meteorological measurements and precipitation data taken during The North American Monsoon GPS-Hydrometeorological Network 2017. The experiment was carried out during the summer of 2017 in the state of Sonora in northwestern Mexico.</p>
LoRa signal quality and GPS positioning time series dataset
<p>This time series dataset contains measurements taken by moving devices equipped with LoRa communication and GPS positioning capabilities. The measurements have been captured at the Sálvora Archipelago in Galicia (Spain), which belong to the Atlantic Islands of Galicia National Park, in which we have deployed three LoRa gateways at the following locations (latitude, longitude, altitute):</p> <ul> <li>Gateway 1 (42.46972, -9.01345, 73)</li> <li>Gateway 2 (42.49955, -9.00654, 5)</li> <li>Gateway 3 (42.50893, -9.04902, 31)</li> </ul> <p>The dataset is provided as a single comma-separated values (CSV) file, with the following data in each line:</p> <ul> <li>Device identification</li> <li>Received signal strength indicator (RSSI) from LoRa Gateway 1</li> <li>Signal-to-noise ratio (SNR) from Gateway 1</li> <li>RSSI from LoRa Gateway 2</li> <li>SNR from Gateway 2</li> <li>RSSI from LoRa Gateway 3</li> <li>SNR from Gateway 3</li> <li>LoRa spreading factor</li> <li>Timestamp</li> <li>Device latitude received from GPS</li> <li>Device longitude received from GPS</li> <li>Device altitude received from GPS</li> </ul>
GPS-synchronized recordings of 5 MHz during October 2, 2024 eclipse from Tortel, Aysén, Chile
Open the record for dataset details and reuse information.
A relative-motion method for parsing spatio-temporal behaviour of dyads using GPS relocation data
<p>In this paper, we introduce a novel method for classifying and computing the frequencies of movement modes of intra- and interspecific dyads, focusing in particular on distance-mediated approach, retreat, following and side by side movement modes. Besides distance, other factors such as time of day, season, sex, or age can be included in the analysis to assess if they cause frequencies of movement modes to deviate from random. By subdividing the data according to selected factors, our method allows us to identify those responsible for (or correlated with) significant differences in the behaviour of dyadic pairs. We demonstrate and validate our method using both simulated and empirical data. Our simulated data were obtained from a relative-motion, biased random-walk (RM-BRW) model with attraction and repulsion components. Our empirical data were GPS relocation data collected from African elephants in Etosha National Park, Namibia. The simulated data were primarily used to validate our method while the empirical data were used to illustrate the types of behavioural assessment that our methodology reveals. Our method facilitates automated, observer-bias-free analysis of the locomotive interactions of dyads using GPS relocation data, which are becoming increasingly ubiquitous as telemetry and related technologies improve. It should open up a whole new vista of behavioural-interaction type analyses to movement and behavioural ecologists.</p>
GPS and hydraulic head measurement utilized in North China Plain research
<p>This dataset contains the raw data of the GPS and hydraulic head measurement <br> utilized in North China Plain research.</p> <p>## Included files</p> <p>The `gps_cmonoc.dat` file contains the horizontal and vertical velocities of <br> the 35 continuous GPS stations from the Crustal Movement Observation Network of <br> China (CMONOC) project.</p> <p>The `gps_bjcors.dat` file contains the horizontal and vertical velocities of <br> the 14 continuous GPS stations from the Beijing Continuously Operating Reference <br> Station (BJCORS) network.</p> <p>The `gps_campaign.dat` file contains the horizontal and vertical velocities of <br> the 432 campaign GPS stations from the Crustal Movement Observation Network of <br> China (CMONOC) project.</p> <p>The `hydraulic_datacenter.xlsx` file contains the 559 measurements from confined <br> well accessed from the National Earth System Science Data Center, National Science <br> & Technology Infrastructure of China (http://www.geodata.cn), recording during 2005-2018.</p> <p>The `hydraulic_yearbook.xlsx` file contains the 130 measurements from both confined<br> and unconfined well compiled from the yearbook 'the China Groundwater Level Yearbook <br> for Geo-environmental Monitoring', recoding during 2005-2016.</p>
MARitime SIMulated (MARSIM) Dataset for GPS Spoofing Detection
<p>MARitime SIMulated (MARSIM) is a comprehensive and labeled dataset created to test and evaluate NMEA-based anomaly detection approaches related to GNSS/GPS spoofing attacks in the maritime context, e.g. <a href="https://github.com/fkie-cad/mana">MANA</a>. It consists of multiple scenarios (benign and attacked) with a duration of 120 s, provided as network traffic recordings, i.e., in packet capture (pcap) format. Each recording contains the NMEA 0183 sentences transmitted within the network of a single vessel heading north from a fixed point with constant velocity. The recordings are reduced to two PNT transmitting devices, namely the pair of GPS receivers, which are placed at a fixed distance of 4 m from each other.</p> <p>Working with the provided packet captures can be facilitated by using our <a href="https://github.com/fkie-cad/maritime-dissector">Wireshark dissector</a>.</p> <p>For more information, please see Spravil J, Hemminghaus C, von Rechenberg M, Padilla E, Bauer J. Detecting Maritime GPS Spoofing Attacks Based on NMEA Sentence Integrity Monitoring. Journal of Marine Science and Engineering. 2023; 11(5):928. DOI: <a href="https://doi.org/10.3390/jmse11050928">10.3390/jmse11050928</a></p>
XEN-45 Gel Stent Versus Trabeculectomy in Glaucoma: Gold-Standard Pathway Study (GPS)
ClinicalTrials.gov study NCT03654885. IPD Sharing: YES. Countries: 1. Publications: 1.
GPS collar data and social-ecological feature data for examining the movement of coyotes in Los Angeles, California (2019-2021)
Open the record for dataset details and reuse information.
Remote sensing and GPS tracking reveal temporal shifts in habitat use in nonbreeding Black-tailed Godwits
Open the record for dataset details and reuse information.
Spatial behavior and diet data for discrete-choice analyses: data observed and classified from GPS video camera collars worn by female members of the Fortymile Caribou Herd across Alaska, USA, and Yukon, Canada
Open the record for dataset details and reuse information.
GPS coordinates and vegetation descriptions for the ITEX circumarctic flux survey plots 2003-2009
GPS locations and vegetation descriptions for the ITEX flux survey plots. Survey plots were located in the Toolik Lake LTER fertilization experiment in Alaska; at Imnavait Creek, Alaska; at Paddus, Latnjajaure and the Stepps site near Abisko in northern Sweden; at various sites in Adventdalen, Svalbard; in the Zackenberg valley, Northeast Greenland; at BEO near Barrow, Alaska and at the Anaktuvuk River Burn in Alaska. Measurements were made during the growing seasons 2003 to 2009.
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating Research (CiPEHR): GPS Plot Locations
The Carbon in Permafrost Experimental Heating Research (CiPEHR) project addresses the following questions: 1) Does ecosystem warming cause a net release of C from the ecosystem to the atmosphere?, 2) Does the decomposition of old C, that comprises the bulk of the soil C pool, influence ecosystem C loss?, and 3) How do winter and summer warming alone, and in combination, affect ecosystem C exchange? We are answering these questions using a combination of field and laboratory experiments to measure ecosystem carbon balance and radiocarbon isotope ratios at a warming experiment located in an upland tundra field site near Healy, Alaska in the foothills of the Alaska Range. This dataset contains plot locations made using a differential GPS with real time kinematic correction in early August of 2017.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.