cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/icpsr38623.v1
title: Federal Justice Statistics Program: Suspects in Federal Criminal Matters, 2020
title: Version 1

description: The data contain records of suspects in federal criminal matters received by United States attorneys or filed before the United States magistrates during fiscal year 2020. The data were constructed from the Executive Office for United States Attorneys (EOUSA) Central System file. Records include suspects in criminal matters, and are limited to suspects whose matters were not declined immediately by the United States attorneys. According to the EOUSA, the United States attorneys conduct approximately 95 percent of the prosecutions handled by the Department of Justice. The Central Charge and Central System data contain variables from the original EOUSA files as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security Number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by Abt Associates and the Bureau of Justice Statistics. Data and documentation were prepared by Abt Associates.
description: Datasets: DS1: Federal Justice Statistics Program: Suspects in Federal Criminal Matters, 2020
description: Suspects in federal criminal matters received by United States attorneys or filed before United States magistrates during fiscal year 2020.
DOI: 10.3886/icpsr38623
title: Federal Justice Statistics Program: Suspects in Federal Criminal Matters, 2020
title: Archival Version

description: The data contain records of suspects in federal criminal matters received by United States attorneys or filed before the United States magistrates during fiscal year 2020. The data were constructed from the Executive Office for United States Attorneys (EOUSA) Central System file. Records include suspects in criminal matters, and are limited to suspects whose matters were not declined immediately by the United States attorneys. According to the EOUSA, the United States attorneys conduct approximately 95 percent of the prosecutions handled by the Department of Justice. The Central Charge and Central System data contain variables from the original EOUSA files as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security Number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by Abt Associates and the Bureau of Justice Statistics. Data and documentation were prepared by Abt Associates.
description: Datasets: DS1: Federal Justice Statistics Program: Suspects in Federal Criminal Matters, 2020
description: Suspects in federal criminal matters received by United States attorneys or filed before United States magistrates during fiscal year 2020.
DOI: 10.5519/qd.nhcknkmz
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (5514092 records)
DOI: 10.5281/zenodo.7786284
title: One meter integrated depth velocity (total, ageostrophy, Ekman and Stokes components) fields for the Mediterranean Sea each 6 hours (from 2005 to 2006)

description: One meter integrated depth surface velocity fields for the Mediterranean Sea from January 2005 to January 2006 calculated following the methodology in Morales-Marquez et al.(2020). This dataset provides the total velocity field, the ageostrophic, Ekman and Stokes components.
description: {"references": ["Morales\u2010M\u00e1rquez, V., Hern\u00e1ndez\u2010Carrasco, I., Simarro, G., Rossi, V., & Orfila, A. (2021). Regionalizing the Impacts of Wind\u2010and Wave\u2010Induced Currents on Surface Ocean Dynamics: A Long\u2010Term Variability Analysis in the Mediterranean Sea. Journal of Geophysical Research: Oceans, 126(9), e2020JC017104."]}
DOI: 10.5281/zenodo.7786283
title: One meter integrated depth velocity (total, ageostrophy, Ekman and Stokes components) fields for the Mediterranean Sea each 6 hours (from 2005 to 2006)

description: One meter integrated depth surface velocity fields for the Mediterranean Sea from January 2005 to January 2006 calculated following the methodology in Morales-Marquez et al.(2020). This dataset provides the total velocity field, the ageostrophic, Ekman and Stokes components.
description: {"references": ["Morales\u2010M\u00e1rquez, V., Hern\u00e1ndez\u2010Carrasco, I., Simarro, G., Rossi, V., & Orfila, A. (2021). Regionalizing the Impacts of Wind\u2010and Wave\u2010Induced Currents on Surface Ocean Dynamics: A Long\u2010Term Variability Analysis in the Mediterranean Sea. Journal of Geophysical Research: Oceans, 126(9), e2020JC017104."]}
DOI: 10.34992/h75j-xp10
title: Lake Manitoba CTD Idronaut Data
DOI: 10.48490/38tt-n386
title: Data for Figure TS.30 -  Technical Summary of Working Group III Contribution to the IPCC Sixth Assessment Report
DOI: 10.5258/soton/d2345
title: Dataset for journal article: Microplastics in European sea salts - an example of exposure through consumer choice and of interstudy methodological discrepancies

description: This dataset contains: Data supporting the above mentioned publication can be found in the zip folder 'Raw data_Raman spectra files.zip' and the excel file 'Raw data_Accompanying file for spectra.xlsx'. The latter file is divided into tabs. Tab 'INFO' Provides an overview of information found in the file. Tab 'Salt' Contains results from library matching of Raman spectra data of analysed particles from commercial sea salt samples. Tab 'Blanks' Contains results from library matching of Raman spectra data of analysed particles from blank samples run alongside commercial sea salt samples. Tab 'Packaging' Contains results from library matching of Raman spectra data of analysed particles from the packaging of commercial sea salt samples. Further, the folder 'Raw data_images.zip' contains images of potential microplastics that were isolated from commercial sea salt samples. Note: not all of these were identified to be plastic.
DOI: 10.3886/icpsr38616.v1
title: Federal Justice Statistics Program: Offenders Released From Prison, 2020
title: Version 1

description: The data contain records of sentenced offenders released from the custody of the Bureau of Prisons (BOP) during fiscal year 2020. The data include commitments of United States District Court, violators of conditions of release (e.g., parole, probation, or supervised release violators), offenders convicted in other courts (e.g., military or District of Columbia courts), and persons admitted to prison as material witnesses or for purposes of treatment, examination, or transfer to another authority. Records of offenders who exit federal prison temporarily, such as for transit to another location, to serve a weekend sentence, or for health care, are not included in the exiting cohort. These data include variables that describe the offender, such as age, race, citizenship, as well as variables that describe the sentences and expected prison terms. The data file contains original variables from the Bureau of Prisons' SENTRY database as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security Number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, D.C.) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute through 2012. Data from 2013 and on were prepared by Abt Associates.
description: Datasets: DS1: Federal Justice Statistics Program: Offenders Released From Prison, 2020
description: Offenders released from the custody of the United States Bureau of Prisons during fiscal year 2020.
DOI: 10.3886/icpsr38616
title: Federal Justice Statistics Program: Offenders Released From Prison, 2020
title: Archival Version

description: The data contain records of sentenced offenders released from the custody of the Bureau of Prisons (BOP) during fiscal year 2020. The data include commitments of United States District Court, violators of conditions of release (e.g., parole, probation, or supervised release violators), offenders convicted in other courts (e.g., military or District of Columbia courts), and persons admitted to prison as material witnesses or for purposes of treatment, examination, or transfer to another authority. Records of offenders who exit federal prison temporarily, such as for transit to another location, to serve a weekend sentence, or for health care, are not included in the exiting cohort. These data include variables that describe the offender, such as age, race, citizenship, as well as variables that describe the sentences and expected prison terms. The data file contains original variables from the Bureau of Prisons' SENTRY database as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security Number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, D.C.) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute through 2012. Data from 2013 and on were prepared by Abt Associates.
description: Datasets: DS1: Federal Justice Statistics Program: Offenders Released From Prison, 2020
description: Offenders released from the custody of the United States Bureau of Prisons during fiscal year 2020.
DOI: 10.5281/zenodo.7779522
title: A Benchmark Dataset with Knowledge Graph Generation for Industry 4.0 Production Lines

description: A benchmark dataset for knowledge graph generation in Industry 4.0 production lines and to show the benefits of using ontologies and semantic annotations of data to showcase how I4.0 industry can benefit from KGs and semantic datasets. This work is a result of collaborations with the production line managers, supervisors, and engineers of a football industry to acquire realistic production line data. Knowledge Graphs (KGs) or a Knowledge Graph (KG) emerged as a significant technology to store the semantics of the domain entities. The data is mapped and populated with RGOM classes and relations using an automated solution based on JenaAPI, producing an I4.0 KG. <br> <br> Usage:<br> <br> Recently, we use this dataset to analyze the performance of the five state-of-the-art KG embedding models, namely ComplEx, DistMult,TransE, ConvKB, and ConvE. We evaluated the models using two key metrics: Mean Reciprocal Rank (MRR), and Hits@N (Hits@10, Hits@3, and Hits@1). We observed that the TransE model outperforms other models, followed by ComplEx and DistMult, with ConvE demonstrating the lowest performance. Similarly, the dataset can be used alternatively in other potential scenarios.
DOI: 10.5281/zenodo.7779521
title: A Benchmark Dataset with Knowledge Graph Generation for Industry 4.0 Production Lines

description: A benchmark dataset for knowledge graph generation in Industry 4.0 production lines and to show the benefits of using ontologies and semantic annotations of data to showcase how I4.0 industry can benefit from KGs and semantic datasets. This work is a result of collaborations with the production line managers, supervisors, and engineers of a football industry to acquire realistic production line data. Knowledge Graphs (KGs) or a Knowledge Graph (KG) emerged as a significant technology to store the semantics of the domain entities. The data is mapped and populated with RGOM classes and relations using an automated solution based on JenaAPI, producing an I4.0 KG. <br> <br> Usage:<br> <br> Recently, we use this dataset to analyze the performance of the five state-of-the-art KG embedding models, namely ComplEx, DistMult,TransE, ConvKB, and ConvE. We evaluated the models using two key metrics: Mean Reciprocal Rank (MRR), and Hits@N (Hits@10, Hits@3, and Hits@1). We observed that the TransE model outperforms other models, followed by ComplEx and DistMult, with ConvE demonstrating the lowest performance. Similarly, the dataset can be used alternatively in other potential scenarios.
DOI: 10.5281/zenodo.7785861
title: Run of an example Galaxy collection workflow

description: This dataset is an RO-Crate representation of an execution of an example Galaxy workflow, making use of some of Galaxy's platform specific features. It follows the Workflow Run Crate profile. The workflow has been run with Galaxy version 23.0 and exported using the implemented export invocation to RO-crate feature.
DOI: 10.5281/zenodo.7785860
title: Run of an example Galaxy collection workflow

description: This dataset is an RO-Crate representation of an execution of an example Galaxy workflow, making use of some of Galaxy's platform specific features. It follows the Workflow Run Crate profile. The workflow has been run with Galaxy version 23.0 and exported using the implemented export invocation to RO-crate feature.
DOI: 10.3886/icpsr38617.v1
title: Federal Justice Statistics Program: Offenders in Prison at Year-End, 2020
title: Version 1

description: The data contain records of sentenced offenders in the custody of the Bureau of Prisons (BOP) at year-end of fiscal year 2020. The data include commitments of United States District Court, violators of conditions of release (e.g., parole, probation, or supervised release violators), offenders convicted in other courts (e.g., military or District of Columbia courts), and persons admitted to prison as material witnesses or for purposes of treatment, examination, or transfer to another authority. These data include variables that describe the offender, such as age, race, citizenship, as well as variables that describe the sentences and expected prison terms. The data file contains original variables from the Bureau of Prisons' SENTRY database as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security Number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by Abt Associates and the Bureau of Justice Statistics. Data and documentation were prepared by Abt Associates.
description: Datasets: DS1: Federal Justice Statistics Program: Offenders in Prison at Year-End, 2020
description: Offenders in the custody of the United States Bureau of Prisons at year-end of fiscal year 2020.
DOI: 10.3886/icpsr38617
title: Federal Justice Statistics Program: Offenders in Prison at Year-End, 2020
title: Archival Version

description: The data contain records of sentenced offenders in the custody of the Bureau of Prisons (BOP) at year-end of fiscal year 2020. The data include commitments of United States District Court, violators of conditions of release (e.g., parole, probation, or supervised release violators), offenders convicted in other courts (e.g., military or District of Columbia courts), and persons admitted to prison as material witnesses or for purposes of treatment, examination, or transfer to another authority. These data include variables that describe the offender, such as age, race, citizenship, as well as variables that describe the sentences and expected prison terms. The data file contains original variables from the Bureau of Prisons' SENTRY database as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security Number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by Abt Associates and the Bureau of Justice Statistics. Data and documentation were prepared by Abt Associates.
description: Datasets: DS1: Federal Justice Statistics Program: Offenders in Prison at Year-End, 2020
description: Offenders in the custody of the United States Bureau of Prisons at year-end of fiscal year 2020.
DOI: 10.6084/m9.figshare.22362160.v1
title: Supplementary Information.pdf

description: Supplementary data of the following research article: Prolonged mechanical muscle loading stimulates mechanosensors and causes a moderate glycolytic-to-oxidative fiber-type switch in mice
DOI: 10.5281/zenodo.7786270
title: The SafeSpace magnetospheric models sample forecast for the 2015 St Patrick's geomagnetic storm

description: This dataset presents the sample forecast of the magnetosphere models in the SafeSpace project, for the March 2015 St Patrick's storm. It is build from a synthetic solar wind forecast at L1 and corresponding Kp forecast. This forecast if fed in the SPM plasma density model, as well as in a VLF wave intensities model, yielding the dataset presented here. All files are in the CDF file format. The GEOIDX_20150301.cdf file contains the synthetic solar wind and Kp ensemble forecast. The Bw2_20150301.cdf file contains the corresponding VLF wave intensities. The SPM_dens_20150301.cdf file contains the corresponding plasma densities. The SafeSpace_RBSP_A_Nowcast.cdf and SafeSpace_RBSP_B_Nowcast.cdf files contains the reconstructed electron fluxes along the RBSP spacecrafts for the whole March 2015 month, using data assimilation in the SafeSpace pipeline. The SafeSpace_RBSP_A_Forecast.cdf and SafeSpace_RBSP_B_Nowcast.cdf files contains a 4 days forecast of the electron fluxes along the RBSP spacecrafts for March 17th to March 20th, 2015. This dataset and the SafeSpace pipeline is described in details in the article by Brunet et al. "Improving the electron radiation belt nowcast and forecast using the SafeSpace data assimilation modelling pipeline", currently in review in AGU Space Weather.
DOI: 10.5281/zenodo.7786269
title: The SafeSpace magnetospheric models sample forecast for the 2015 St Patrick's geomagnetic storm

description: This dataset presents the sample forecast of the magnetosphere models in the SafeSpace project, for the March 2015 St Patrick's storm. It is build from a synthetic solar wind forecast at L1 and corresponding Kp forecast. This forecast if fed in the SPM plasma density model, as well as in a VLF wave intensities model, yielding the dataset presented here. All files are in the CDF file format. The GEOIDX_20150301.cdf file contains the synthetic solar wind and Kp ensemble forecast. The Bw2_20150301.cdf file contains the corresponding VLF wave intensities. The SPM_dens_20150301.cdf file contains the corresponding plasma densities. The SafeSpace_RBSP_A_Nowcast.cdf and SafeSpace_RBSP_B_Nowcast.cdf files contains the reconstructed electron fluxes along the RBSP spacecrafts for the whole March 2015 month, using data assimilation in the SafeSpace pipeline. The SafeSpace_RBSP_A_Forecast.cdf and SafeSpace_RBSP_B_Nowcast.cdf files contains a 4 days forecast of the electron fluxes along the RBSP spacecrafts for March 17th to March 20th, 2015. This dataset and the SafeSpace pipeline is described in details in the article by Brunet et al. "Improving the electron radiation belt nowcast and forecast using the SafeSpace data assimilation modelling pipeline", currently in review in AGU Space Weather.
DOI: 10.5258/soton/d2540
title: Dataset for the journal article 'Photonic Metamaterial Analogue of a Continuous Time Crystal'

description: Experimental data presented in the paper published in Nature Physics: Photonic metamaterial analogue of a continuous time crystal, Tongjun Liu, Jun-Yu. Ou, Kevin F. MacDonald, Nikolay I. Zheludev, Nat. Phys.
DOI: 10.3886/icpsr38624.v1
title: Federal Justice Statistics Program: Arrests and Bookings for Federal Offenses, 2020
title: Version 1

description: The data contain records of arrests and bookings for federal offenses in the United States during fiscal year 2020. The data were constructed from the United States Marshals Service (USMS) Capture database. Records include arrests and bookings made by federal law enforcement agencies (including the USMS) and state and local agencies. Justice involved individuals arrested or booked for federal offenses are transferred to the custody of the USMS for processing, transportation, and detention. The Capture system contains data on all justice involved individuals within the custody of the USMS. Variables containing identifying information were either removed, coarsened, or blanked in order to protect the identities of individuals. A primary difference between the 2020 data and previous years is that the 2020 data were subset based upon an admission to custody in the fiscal year. In previous years, arrest date was used to subset the records. Some individuals in the 2020 data will have a missing arrest date. These data are part of a series designed by Abt Associates and the Bureau of Justice Statistics. Data and documentation were prepared by Abt Associates.
description: Datasets: DS1: Federal Justice Statistics Program: Arrests and Bookings for Federal Offenses, 2020
description: Federal offenders in the custody of the United States Marshals Service during fiscal year 2020.
description: Beginning in 2020, records reflect date at the start of custody rather than arrest date.
DOI: 10.3886/icpsr38624
title: Federal Justice Statistics Program: Arrests and Bookings for Federal Offenses, 2020
title: Archival Version

description: The data contain records of arrests and bookings for federal offenses in the United States during fiscal year 2020. The data were constructed from the United States Marshals Service (USMS) Capture database. Records include arrests and bookings made by federal law enforcement agencies (including the USMS) and state and local agencies. Justice involved individuals arrested or booked for federal offenses are transferred to the custody of the USMS for processing, transportation, and detention. The Capture system contains data on all justice involved individuals within the custody of the USMS. Variables containing identifying information were either removed, coarsened, or blanked in order to protect the identities of individuals. A primary difference between the 2020 data and previous years is that the 2020 data were subset based upon an admission to custody in the fiscal year. In previous years, arrest date was used to subset the records. Some individuals in the 2020 data will have a missing arrest date. These data are part of a series designed by Abt Associates and the Bureau of Justice Statistics. Data and documentation were prepared by Abt Associates.
description: Datasets: DS1: Federal Justice Statistics Program: Arrests and Bookings for Federal Offenses, 2020
description: Federal offenders in the custody of the United States Marshals Service during fiscal year 2020.
description: Beginning in 2020, records reflect date at the start of custody rather than arrest date.
DOI: 10.25573/serc.22361548
title: GBIF derived dataset

description: Derived occurrence dataset from GBIF used in Mixed messages and the drivers of public and media interest in US invasive plants manuscript by Woodworth et al.
DOI: 10.25573/serc.22361548.v1
title: GBIF derived dataset

description: Derived occurrence dataset from GBIF used in Mixed messages and the drivers of public and media interest in US invasive plants manuscript by Woodworth et al.
DOI: 10.5519/qd.ntg75o3h
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (3 records)
DOI: 10.6084/m9.figshare.22363549
title: Demographics and behavioral data

description: Demographics and behavioral data