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About 10,000 papers for “Event data”

Event Data

Marc Garnica Caparrós · 2024

Cited by 2

Aggregated event data

Madita Stirner, Christian Paret · OSF Preprints (OSF Preprints) · 2021

Performance and descriptive data from the experiment

Cited by 0Open access

Calving event data

Symons, John, Sprogis, Kate, Bejder, Lars · Figshare · 2018

This data contains the 100 known females and any sightings of their respective calves (if any). The dataset consisted of 12 primary periods (australasian seasons), with 4 primary periods collected for each of 3 years. Calf code is a unique identifier for each individual calf.

Cited by 0Open access

Raster Event Data

Anderson Loake, Max, Steinsaltz, David, Patten, Hamish · University of Oxford · 2025

The raster objects contain vulnerability, hazard, and exposure data for a set of past earthquake events, as described in the manuscript 'A Bayesian Approach for Earthquake Impact Modelling' (available at: https://arxiv.org/abs/2412.15791). They are split into the events used to train and test the model. The code used to generate the R objects is contained in https://github.com/hamishwp/ODDRIN. The objects are created using data from a range of sources, including:Global Data Lab: J. Smits and I. Permanyer. The Subnational Human Development Database. Scientific data, 6(1):1–15, 2019.Vs30: D. C. Heath, D. J. Wald, C. B. Worden, E. M. Thompson, and G. M. Smoczyk. A global hybrid VS 30 map with a topographic slope–based default and regional map insets. Earthquake Spectra, 36(3):1570–1584, 2020.Earthquake frequency: K. Johnson, M. Villani, K. Bayliss, C. Brooks, S. Chandrasekhar, T. Chartier, Y. Chen, J. Garcia-Pelaez, R. Gee, R. Styron, A. Rood, M. Simionato, and M. Pagani. Global Earthquake Model (GEM) seismic hazard map (version 2023.1 - June 2023). GEM https://doi.org/10.5281/zenodo.8409647, 2023.Income Inequality: F. Alvaredo, A. B. Atkinson, T. Piketty, and E. Saez. World Inequality Database, 2022. URL http://wid.world/data.Copernicus Building Damage Footprints: Copernicus Emergency Management Service. Copernicus emergency management service - mapping, 2012. URL https://emergency.copernicus.eu/mapping. The European Commission.UNITAR/UNOSAT Building Damage Footprints: UNITAR/UNOSAT. UNITAR’s Operational Satellite Applications Programme – UNOSAT, 2023. URL https://unosat.org/<br>products/.WorldPop Population: A. J. Tatem. WorldPop, open data for spatial demography. Scientific Data, 4(1):1–4, 2017. doi: 10.1038/sdata.2017.4.Bing Building Footprints: Microsoft. Global ML Building Footprints, 2022. URL https://github.com/microsoft/GlobalMLBuildingFootprints. Accessed:<br>2024-06-17.<br>Shakemap: D. J. Wald, B. C. Worden, V. Quitoriano, and K. L. Pankow. ShakeMap manual: Technical manual, user’s guide, and software guide. Technical Report 12-A1, United States Geological Survey, 2005.

Cited by 0Open access

Conflict Event Data

Clionadh Raleigh, Roudabeh Kishi · 2022

Conflict event data and analysis provide one of the main evidence bases for political violence studies, shifting conflict studies away from a focus on national-level studies or individual state or conflict studies that can have limited generalizability. While several publicly available conflict event data projects now exist, they differ significantly in their scope, catchment, and depth – largely a result of how each prioritizes conflicts and event types. How information is collected (by researchers or by machines) also significantly impacts what data ultimately look like, as a function of inclusion criteria, sourcing, and review processes that are in place. These differences impact the geographies and scales of conflict that may be seen, as well as what threats to civilians look like. Foreign policy analysts must therefore have a keen awareness of what a dataset is designed to capture, and what narratives on violence it supports and refutes.

Cited by 3

Event probabilities data

Saurels, Blake, Arnold, Derek · The University of Queensland · 2023

EEG and behavioural data for the paper titled: Event probabilities have a different impact on early and late electroencephalographic measures regarded as metrics of prediction The set includes raw EEG data, cleaned EEG data, and analysis scripts. EEG and behavioural data for the paper titled: Event probabilities have a different impact on early and late electroencephalographic measures regarded as metrics of prediction The set includes raw EEG data, cleaned EEG data, and analysis scripts.

Cited by 0Open access

Auroral event data

Qian Wang · Zenodo (CERN European Organization for Nuclear Research) · 2023

Description: The Aurora event data database contains two datasets: "Auroral event data" and "Dayside auroral observation". The dataset of "Auroral event data" has 14 auroral image sequences with a total of 21,372 images (total size: 1.61GB). The 14 aurora image sequences are from 2003 to 2021 as the study data of the "Unsupervised auroral event Segmentation Based on All-sky Imager Observation". The aurora event data are ground-based observation data acquired by three-wavelength (427.8, 557.7, and 630.0 nm) all-sky imaging (ASI) at YRS (the geographic coordinates are 78.92°N, 11.93°E, the corrected magnetic latitude is 76.24°N, MLT=UT+3.1h.) in Ny-Ålesund, Svalbard. The device captures an aurora image every 10 seconds with an exposure time of 7 seconds. The captured raw image is a 14-bit 512×512 pixel image. The angle between the horizontal direction of the ASI image and the magnetic meridian is 61.1°. Data acquisition instruments: In 2003, three all-sky CCD auroral imagers were installed to observe aurora phenomenon. This system can record 24-hour auroral activities from October to March of each year. File nameing convention: Each auroral image has a unique file name that contains the N/S, date, band, and time information. Filename example: N20031221G081212. N: North pole 20031221:December 21, 2003 G:G-band 081212:8:12:12 UT All aurora images are provided in .bmp image format. In "Auroral event data", each auroral image sequence is provided as a separate zip file, with a total of 14 segments of the aurora image sequences lasting a total of 57 hr, 12 min, 47 sec, of which: N20031221G081212_N20031221G112151: 2003.12.21 08:12:12-11:21:51 aurora data, duration 3 hr, 9 min, 39 sec; N20031221G112011_N20031221G142951: 2003.12.21 11:20:11-14:29:51 aurora data,duration 2 hr, 9 min, 40 sec; N20031222G074012_N20031222G104951: 2003.12.22 07:40:12-10:49:51 aurora data, duration 3 hr, 9 min, 39 sec; N20031222G115011_N20031222G145952: 2003.12.22 11:50:11-14:59:52 aurora data, duration 2 hr, 9 min, 41 sec; N20031223G091111_N20031223G145951: 2003.12.23 09:11:11-14:59:51 aurora data, duration 5 hr, 48 min, 40 sec; N20031224G115011_N20031224G145951: 2003.12.24 11:50:11-14:59:51 aurora data, duration 3 hr, 9 min, 40 sec; N20031225G115011_N20031225G145951: 2003.12.25 11:50:11-14:59:51 aurora data, duration 3 hr, 9 min, 40 sec; N20031226G090001_N20031226G145951: 2003.12.26 09:00:01-14:59:51 aurora data, duration 5 hr, 59 min, 50 sec; N20031228G115250_N20031228G145952: 2003.12.28 11:52:50-14:59:52 aurora data, duration 3 hr, 7 min, 2 sec; N20031229G092100_N20031229G145954: 2003.12.29 09:21:00-14:59:54 aurora data, duration 5 hr, 38 min, 54 sec; N20031230G030002_N20031230G091103: 2003.12.30 03:00:02-09:11:03 aurora data, duration 6 hr, 11 min, 1 sec; N20031230G115014_N20031230G145954: 2003.12.30 11:50:14-14:59:54 aurora data, duration 3 hr, 9 min, 40 sec; N20031231G030003_N20031231G101004: 2003.12.31 03:00:03-10:10:04 aurora data, duration 7 hr, 10 min, 1 sec; N20211129G130010_N20211129G160950: 2021.11.29 13:00:10-16:09:50 aurora data, duration 3 hr, 9 min, 40 sec; In "Dayside auroral observation", two entire image sequences of dayside (03:00-15:00 UT) auroral ASI observations are provided, which is: N20031225G: 2003.12.25 03:00:01-14:59:51 aurora data, duration 12 hr, 4320 images; N20031228G: 2003.12.28 03:00:07-14:59:52 aurora data, duration 12 hr, 4386 images; Cite as: Auroral event data. 10.5281/Zenodo.10013563 The analysis and validation of the "Aurora event data" are described in our preparing paper "Unsupervised Auroral Event Segmentation Based on All-sky Imager Observation".

Cited by 0Open access

Event: Data Carpentry

Jamene Brooks‐Kieffer, Brianna Marshall, Michelle Hudson et al. · OSF Preprints (OSF Preprints) · 2016

This component contains introductory material, case studies, and (where available) discussion group notes about Data Carpentry workshops. The discussion groups were held during the RDAP 2016 panel "Crowdsourcing Guidelines for a Successful Data Event: An Un(conference) Panel." Files are documented in a ReadMe on the component's wiki.

Cited by 0

Recurrent Event Data

Russell Stocker · Encyclopedia of Quantitative Risk Analysis and Assessment · 2008

Abstract Many lifetime data studies involve units that experience multiple‐ordered events of the same nature. The resulting data is commonly termed recurrent event data . This article presents some of the important aspects that need to be considered when modeling this type of data. It surveys several of the models that are found in the literature. The models are applied to a real data set for comparative purposes.

Cited by 0

Adverse event data.

Edmundo Vázquez-Cornejo (12289582), Olga Morales-Ríos (4740189), Gabriela Hernández-Pliego (12289585) et al. · Figshare · 2022

Cited by 0Open access

Event Data Recorder

Event Data Recorder Committee · 2023

&lt;div class="section abstract"&gt; &lt;div class="htmlview paragraph"&gt;This SAE Recommended Practice describes common definitions and operational elements of Event Data Recorders. The SAE J1698 series of documents consists of the following:&lt;/div&gt; &lt;ul class="list disc"&gt; &lt;li class="list-item"&gt; &lt;div class="htmlview paragraph"&gt;SAE J1698-1 - Event Data Recorder - Output Data Definition: Provides common data output formats and definitions for a variety of data elements that may be useful for analyzing vehicle crash and crash-like events that meet specified trigger criteria.&lt;/div&gt;&lt;/li&gt; &lt;li class="list-item"&gt; &lt;div class="htmlview paragraph"&gt;SAE J1698-2 - Event Data Recorder - Retrieval Tool Protocol: Utilizes existing industry standards to identify a common physical interface and define the protocols necessary to retrieve records stored by light duty vehicle Event Data Recorders (EDRs).&lt;/div&gt;&lt;/li&gt; &lt;li class="list-item"&gt; &lt;div class="htmlview paragraph"&gt;SAE J1698-3 - Event Data Recorder - Compliance Assessment: Defines procedures that may be used to validate that relevant EDR output records conform with the reporting requirements specified in Part 563, &lt;span class="xref"&gt;Table 1&lt;/span&gt; during the course of FMVSS-208, FMVSS-214, and other applicable vehicle level crash testing.&lt;/div&gt;&lt;/li&gt;&lt;/ul&gt;&lt;/div&gt;

Cited by 0

Health event data

Anthony Staines, Lars Järup · 2001

Abstract This chapter serves as guide to those setting out to analyze large health-related datasets. It focuses on European systems, especially in the UK and the Scandinavian countries, although many of the issues are applicable to other industrialized countries. A wide range of spatial data sources are available for epidemiological analysis. New and powerful methods of handling spatial data, including GIS and Bayesian multi-level modelling, have made sophisticated and complex analyses possible. To make effective use of these approaches, epidemiologists must be aware of the details of the data with which they propose to work, and of the specific problems and limitations of routinely collected health data, which often form the core of spatial analysis.

Cited by 10

Event: Data Carpentry

Brianna Marshall, Michelle Hudson, Andrew Johnson et al. · OSF Preprints (OSF Preprints) · 2016

This component contains introductory material, case studies, and (where available) discussion group notes about Data Carpentry workshops. The discussion groups were held during the RDAP 2016 panel "Crowdsourcing Guidelines for a Successful Data Event: An Un(conference) Panel." Files are documented in a ReadMe on the component's wiki.

Cited by 0

Raster Event Data

Anderson Loake, Max · University of Oxford · 2025

The raster objects contain vulnerability, hazard, and exposure data for a set of past earthquake events, as described in the manuscript 'A Bayesian Approach for Earthquake Impact Modelling' (available at: https://arxiv.org/abs/2412.15791). They are split into the events used to train and test the model. The code used to generate the R objects is contained in https://github.com/hamishwp/ODDRIN. The objects are created using data from a range of sources, including:Global Data Lab: J. Smits and I. Permanyer. The Subnational Human Development Database. Scientific data, 6(1):1–15, 2019.Vs30: D. C. Heath, D. J. Wald, C. B. Worden, E. M. Thompson, and G. M. Smoczyk. A global hybrid VS 30 map with a topographic slope–based default and regional map insets. Earthquake Spectra, 36(3):1570–1584, 2020.Earthquake frequency: K. Johnson, M. Villani, K. Bayliss, C. Brooks, S. Chandrasekhar, T. Chartier, Y. Chen, J. Garcia-Pelaez, R. Gee, R. Styron, A. Rood, M. Simionato, and M. Pagani. Global Earthquake Model (GEM) seismic hazard map (version 2023.1 - June 2023). GEM https://doi.org/10.5281/zenodo.8409647, 2023.Income Inequality: F. Alvaredo, A. B. Atkinson, T. Piketty, and E. Saez. World Inequality Database, 2022. URL http://wid.world/data.Copernicus Building Damage Footprints: Copernicus Emergency Management Service. Copernicus emergency management service - mapping, 2012. URL https://emergency.copernicus.eu/mapping. The European Commission.UNITAR/UNOSAT Building Damage Footprints: UNITAR/UNOSAT. UNITAR’s Operational Satellite Applications Programme – UNOSAT, 2023. URL https://unosat.org/<br>products/.WorldPop Population: A. J. Tatem. WorldPop, open data for spatial demography. Scientific Data, 4(1):1–4, 2017. doi: 10.1038/sdata.2017.4.Bing Building Footprints: Microsoft. Global ML Building Footprints, 2022. URL https://github.com/microsoft/GlobalMLBuildingFootprints. Accessed:<br>2024-06-17.<br>Shakemap: D. J. Wald, B. C. Worden, V. Quitoriano, and K. L. Pankow. ShakeMap manual: Technical manual, user’s guide, and software guide. Technical Report 12-A1, United States Geological Survey, 2005.

Cited by 0Open access