cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/icpsr35019.v1
title: Uniform Crime Reporting Program Data: County-Level Detailed Arrest and Offense Data, 2012
title: Version 1

description: This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).
description: Datasets: 
 
 DS0: Study-Level Files 
 DS1: Arrests, All Ages 
 DS2: Arrests, Adult 
 DS3: Arrests, Juveniles 
 DS4: Crimes Reported 
 DS5: Allocated Statewide Data for Arrests, All Ages 
 DS6: Allocated Statewide Data for Arrests, Adults 
 DS7: Allocated Statewide Data for Arrests, Juveniles 
 DS8: Allocated Statewide Data for Crimes Reported
description: Uniform Crime Reporting Program Data Series
description: self-enumerated questionnaire 
Two major changes to the Uniform Crime Reports (UCR) county-level files were implemented beginning with the 1994 data. A new imputation algorithm to adjust for incomplete reporting by individual law enforcement jurisdictions was adopted. Within each county, data from agencies reporting 3 to 11 months of information were weighted to yield 12-month equivalents. Data for agencies reporting less than three months of data were replaced with data estimated by rates calculated from agencies reporting 12 months of data located in the agency's geographic stratum within its state. Secondly, a new Coverage Indicator was created to provide users with a diagnostic measure of aggregated data quality in a particular county. Data from agencies reporting only statewide figures were allocated to the counties in the state in proportion to each county's share of the state population.
In the arrest files (Parts 1-3 and 5-7), data were estimated for agencies reporting zero months based on the procedures mentioned above. However, due to the structure of the data received from the Federal Bureau of Investigation (FBI), estimations could not be produced for agencies reporting zero months in the crimes reported files (Parts 4 and 8). Offense data for agencies reporting one or two months are estimated using the above procedures. Users are encouraged to refer to the codebook for more information.
No arrest data were provided for Alabama and Florida. Limited arrest data were provided for Illinois and South Dakota. Limited crimes reported data were available for Alaska, Illinois, Mississippi, and South Dakota.
UCR program staff at the Federal Bureau of Investigation (FBI) were consulted in developing the new adjustment procedures. However, these UCR county-level files are not official FBI UCR releases and are being provided for research purposes only. Users with questions regarding these UCR county-level data files can contact the National Archive of Criminal Justice Data at ICPSR.
description: County law enforcement agencies in the United States. Smallest Geographic Unit: county
DOI: 10.3886/icpsr36117.v2
title: Uniform Crime Reporting Program Data: County-Level Detailed Arrest and Offense Data, United States, 2013
title: Version 2

description: This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).
description: Datasets: DS0: Study-Level Files DS1: Arrests, All Ages DS2: Arrests, Adult DS3: Arrests, Juveniles DS4: Crimes Reported DS5: Allocated Statewide Data for Arrests, All Ages DS6: Allocated Statewide Data for Arrests, Adults DS7: Allocated Statewide Data for Arrests, Juveniles DS8: Allocated Statewide Data for Crimes Reported
description: County law enforcement agencies in the United States. Smallest Geographic Unit: county
description: self-enumerated questionnaireTwo major changes to the Uniform Crime Reports (UCR) county-level files were implemented beginning with the 1994 data. A new imputation algorithm to adjust for incomplete reporting by individual law enforcement jurisdictions was adopted. Within each county, data from agencies reporting 3 to 11 months of information were weighted to yield 12-month equivalents. Data for agencies reporting less than three months of data were replaced with data estimated by rates calculated from agencies reporting 12 months of data located in the agency's geographic stratum within its state. Secondly, a new Coverage Indicator was created to provide users with a diagnostic measure of aggregated data quality in a particular county. Data from agencies reporting only statewide figures were allocated to the counties in the state in proportion to each county's share of the state population.In the arrest files (Parts 1-3 and 5-7), data were estimated for agencies reporting zero months based on the procedures mentioned above. However, due to the structure of the data received from the Federal Bureau of Investigation (FBI), estimations could not be produced for agencies reporting zero months in the crimes reported files (Parts 4 and 8). Offense data for agencies reporting one or two months are estimated using the above procedures. Users are encouraged to refer to the codebook for more information.No arrest data were provided for Alabama, Florida, and Illinois. Limited arrest data were provided for South Dakota. Limited crimes reported data were available for Alaska, Illinois, Mississippi, and South Dakota.UCR program staff at the Federal Bureau of Investigation (FBI) were consulted in developing the new adjustment procedures. However, these UCR county-level files are not official FBI UCR releases and are being provided for research purposes only. Users with questions regarding these UCR county-level data files can contact the National Archive of Criminal Justice Data at ICPSR.
DOI: 10.3886/icpsr36399.v2
title: Uniform Crime Reporting Program Data: County-Level Detailed Arrest and Offense Data, United States, 2014
title: Version 2

description: This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).
description: Datasets: DS0: Study-Level Files DS1: Arrests, All Ages DS2: Arrests, Adult DS3: Arrests, Juveniles DS4: Crimes Reported DS5: Allocated Statewide Data for Arrests, All Ages DS6: Allocated Statewide Data for Arrests, Adults DS7: Allocated Statewide Data for Arrests, Juveniles DS8: Allocated Statewide Data for Crimes Reported
description: County law enforcement agencies in the United States. Smallest Geographic Unit: county
description: self-enumerated questionnaireTwo major changes to the Uniform Crime Reports (UCR) county-level files were implemented beginning with the 1994 data. A new imputation algorithm to adjust for incomplete reporting by individual law enforcement jurisdictions was adopted. Within each county, data from agencies reporting 3 to 11 months of information were weighted to yield 12-month equivalents. Data for agencies reporting less than three months of data were replaced with data estimated by rates calculated from agencies reporting 12 months of data located in the agency's geographic stratum within its state. Secondly, a new Coverage Indicator was created to provide users with a diagnostic measure of aggregated data quality in a particular county. Data from agencies reporting only statewide figures were allocated to the counties in the state in proportion to each county's share of the state population.In the arrest files (Parts 1-3 and 5-7), data were estimated for agencies reporting zero months based on the procedures mentioned above. However, due to the structure of the data received from the Federal Bureau of Investigation (FBI), estimations could not be produced for agencies reporting zero months in the crimes reported files (Parts 4 and 8). Offense data for agencies reporting one or two months are estimated using the above procedures. Users are encouraged to refer to the codebook for more information.No arrest data were provided for Florida and Illinois. Limited crimes reported data were available for Alaska, Mississippi, and South Dakota.UCR program staff at the Federal Bureau of Investigation (FBI) were consulted in developing the new adjustment procedures. However, these UCR county-level files are not official FBI UCR releases and are being provided for research purposes only. Users with questions regarding these UCR county-level data files can contact the National Archive of Criminal Justice Data at ICPSR.
DOI: 10.3886/e115006v1-168121
title: National Neighborhood Data Archive (NaNDA): Crimes by County, United States, 2002-2014

description: This dataset contains
county-level totals for the years 2002-2014 for eight types of crime: murder,
rape, robbery, aggravated assault, burglary, larceny, motor vehicle theft, and
arson. These crimes are classed as Part I criminal offenses by the United
States Federal Bureau of Investigations (FBI) in their Uniform Crime Reporting
(UCR) program. Each record in the dataset represents the total of each type of
criminal offense reported in (or, in the case of missing data, attributed to)
the county in a given year.<br><br>A curated version of this data is available through ICPSR at https://www.icpsr.umich.edu/web/ICPSR/studies/38649/versions/V1
description: All counties in the United States, excluding US island territories. Smallest Geographic Unit: county
DOI: 10.15468/dl.fkhday
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Trichosporon asahii var. asahii"
 ]
}

 The dataset includes 12 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002329-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nuje4p
title: Occurrence Download

description: A dataset containing 1193 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Sri Lanka",
 "TaxonKey is Nettapus coromandelianus (J.F.Gmelin, 1789)",
 "Year 2000-2025"
 ]
}

 The dataset includes 1193 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002331-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8zdkwt
title: Occurrence Download

description: A dataset containing 39 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Dictyostelium discoideum Raper, 1935"
 ]
}

 The dataset includes 39 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002332-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.68nf34
title: Occurrence Download

description: A dataset containing 387 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Sri Lanka",
 "TaxonKey is Anas poecilorhyncha J.R.Forster, 1781",
 "Year 2000-2025"
 ]
}

 The dataset includes 387 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002335-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.27003451.v1
title: Chapter 2

description: Supplementary Information for Chapter 2 of the Doctoral Thesis
DOI: 10.15468/dl.dh4rva
title: Occurrence Download

description: A dataset containing 494 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Sri Lanka",
 "TaxonKey is Rallina eurizonoides (Lafresnaye, 1845)",
 "Year 2000-2025"
 ]
}

 The dataset includes 494 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002336-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pjycrt
title: Occurrence Download

description: A dataset containing 145 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Sri Lanka",
 "TaxonKey is Lewinia striata (Linnaeus, 1766)",
 "Year 2000-2025"
 ]
}

 The dataset includes 145 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002339-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rbz2w9
title: Occurrence Download

description: A dataset containing 3279275 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is New Zealand",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 3279275 records from 281 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002337-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.64g65d
title: Occurrence Download

description: A dataset containing 545 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Sri Lanka",
 "TaxonKey is Zapornia fusca (Linnaeus, 1766)",
 "Year 2000-2025"
 ]
}

 The dataset includes 545 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002341-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28426499
title: EVM Validation files

description: Validating experimental vignette methodology - authentic leadership
DOI: 10.6084/m9.figshare.28426499.v1
title: EVM Validation files

description: Validating experimental vignette methodology - authentic leadership
DOI: 10.15468/dl.w77vkw
title: Occurrence Download

description: A dataset containing 3458 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is Asia",
 "Country is Sri Lanka",
 "TaxonKey is Ciconia episcopus (Boddaert, 1783)",
 "Year 2000-2025"
 ]
}

 The dataset includes 3458 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002343-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wee26b
title: Occurrence Download

description: A dataset containing 149 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Inimicus japonicus (Cuvier, 1829)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 149 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002344-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ez2aa5
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plantae",
 "HasCoordinate is true",
 "Geometry MULTIPOLYGON (((-114.2827 38.57419, -114.2763 38.56383, -114.2755 38.5604, -114.2758 38.55172, -114.2779 38.54761, -114.2775 38.5442, -114.2697 38.5338, -114.268 38.52923, -114.2666 38.52768, -114.2667 38.5254, -114.2668 38.52503, -114.2689 38.51752, -114.2743 38.51463, -114.2744 38.51236, -114.2696 38.5096, -114.2706 38.50565, -114.2714 38.50208, -114.2726 38.49569, -114.2667 38.48609, -114.2645 38.47886, -114.2629 38.4705, -114.2641 38.46372, -114.264 38.46305, -114.2639 38.46271, -114.2639 38.4626, -114.2633 38.45992, -114.2619 38.45875, -114.2606 38.45494, -114.2555 38.45065, -114.2561 38.44765, -114.2505 38.44147, -114.2489 38.44049, -114.2454 38.43832, -114.2425 38.43863, -114.2392 38.43515, -114.2288 38.43112, -114.2263 38.43409, -114.2266 38.43712, -114.2323 38.43952, -114.2361 38.44264, -114.2369 38.44454, -114.2355 38.44565, -114.2249 38.44464, -114.2193 38.44034, -114.2109 38.43523, -114.204 38.43771, -114.1935 38.43556, -114.1916 38.43627, -114.1914 38.44005, -114.1933 38.44199, -114.1961 38.44244, -114.1975 38.44361, -114.2006 38.45236, -114.1999 38.45802, -114.1989 38.45951, -114.2011 38.46373, -114.201 38.46675, -114.1984 38.47274, -114.1993 38.47352, -114.2099 38.47377, -114.2108 38.47455, -114.2096 38.4802, -114.2148 38.48334, -114.2272 38.49801, -114.2271 38.50141, -114.2246 38.50513, -114.2269 38.50746, -114.2268 38.50897, -114.2253 38.51006, -114.2195 38.51069, -114.2175 38.5129, -114.218 38.51405, -114.2217 38.51603, -114.2299 38.51585, -114.2314 38.51663, -114.2341 38.52049, -114.2334 38.52576, -114.2366 38.53038, -114.2365 38.53264, -114.2393 38.53498, -114.2397 38.53801, -114.2444 38.5419, -114.2471 38.54612, -114.246 38.55102, -114.2488 38.55222, -114.2517 38.5519, -114.2543 38.55512, -114.2585 38.55797, -114.2591 38.55835, -114.2619 38.56307, -114.2627 38.57285, -114.2628 38.57565, -114.2629 38.58215, -114.2633 38.58913, -114.2629 38.59888, -114.2627 38.60353, -114.2643 38.6057, -114.2655 38.60731, -114.2721 38.60561, -114.2753 38.60162, -114.2765 38.60013, -114.279 38.59601, -114.2804 38.59521, -114.2791 38.59339, -114.2792 38.59075, -114.2822 38.58816, -114.2826 38.58477, -114.2827 38.58447, -114.2827 38.58443, -114.2827 38.58422, -114.2835 38.57913, -114.2827 38.57419)), ((-114.1932 38.42525, -114.1954 38.42766, -114.2005 38.42817, -114.204 38.42636, -114.204 38.42448, -114.198 38.41941, -114.1964 38.41885, -114.1934 38.42107, -114.1932 38.42525)), ((-114.1938 38.41085, -114.1932 38.41369, -114.1972 38.41409, -114.1992 38.41339, -114.2017 38.4108, -114.2013 38.40928, -114.2015 38.40851, -114.198 38.40863, -114.1938 38.41085)))"
 ]
}

 The dataset includes 11 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002345-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.375gwe
title: Occurrence Download

description: A dataset containing 3523 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is Asia",
 "Country is Sri Lanka",
 "TaxonKey is Ixobrychus sinensis (Gmelin, 1789)",
 "Year 2000-2025"
 ]
}

 The dataset includes 3523 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002346-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kdaas7
title: Occurrence Download

description: A dataset containing 149 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Inimicus japonicus (Cuvier, 1829)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 149 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002349-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26188/28426541
title: CT machine comparison

description: In human CT imaging, opportunistic calculation of bone mineral density (BMD) is used to screen for osteoporosis, where BMD is estimated by Hounsfield Units (HU). There is potential to use HU for estimation of BMD in veterinary imaging. However, HU values can vary between different machines and over time. We undertook a serial measurements study to determine (1) the extent of the difference of the mean HU and noise (HU standard deviation) of eight regions of interest (ROI) of an electron density phantom scanned on two CT machines, a Siemens CT (conventional) machine and the Equina by Asto CT (standing) machine; and (2) to determine if the HU values obtained on each machine differed over time. The mean HU from 30 scans of an electron density phantom were generated from each of the two CT machines (N=60; conventional and standing). Differences between machines were assessed using a linear mixed effects model. The mean HU of each positive value ROI from the conventional machine was lower than for the standing machine (P &lt; 0.001) and the difference was greatest for the denser phantom inserts. A calibration curve equation utilising the four bone-equivalent insert plugs of the phantom, with known calcium hydroxyapatite (CaHA) concentration, was generated using linear regression to represent CaHA, and therefore BMD, for the conventional machine (CaHA=-29.58+0.98xROImean) and the standing machine (CaHA=-54.53+0.95xROImean). For opportunistic calculation of BMD from HU in horses, the differences in HU observed between different CT machines warrants calibration of HU using a bone equivalent phantom.
DOI: 10.26188/28426541.v1
title: CT machine comparison

description: In human CT imaging, opportunistic calculation of bone mineral density (BMD) is used to screen for osteoporosis, where BMD is estimated by Hounsfield Units (HU). There is potential to use HU for estimation of BMD in veterinary imaging. However, HU values can vary between different machines and over time. We undertook a serial measurements study to determine (1) the extent of the difference of the mean HU and noise (HU standard deviation) of eight regions of interest (ROI) of an electron density phantom scanned on two CT machines, a Siemens CT (conventional) machine and the Equina by Asto CT (standing) machine; and (2) to determine if the HU values obtained on each machine differed over time. The mean HU from 30 scans of an electron density phantom were generated from each of the two CT machines (N=60; conventional and standing). Differences between machines were assessed using a linear mixed effects model. The mean HU of each positive value ROI from the conventional machine was lower than for the standing machine (P &lt; 0.001) and the difference was greatest for the denser phantom inserts. A calibration curve equation utilising the four bone-equivalent insert plugs of the phantom, with known calcium hydroxyapatite (CaHA) concentration, was generated using linear regression to represent CaHA, and therefore BMD, for the conventional machine (CaHA=-29.58+0.98xROImean) and the standing machine (CaHA=-54.53+0.95xROImean). For opportunistic calculation of BMD from HU in horses, the differences in HU observed between different CT machines warrants calibration of HU using a bone equivalent phantom.