cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5850263
title: HomogWS-se: A century-long homogenized dataset of near-surface wind speed observations since 1925 rescued in Sweden

description: Creating a century-long homogenized near-surface wind speed (WS) observation dataset is essential to improve our knowledge about the uncertainty and causes of WS stilling and recovery. We rescued paper-based WS records dating back to the 1920s at 13 stations in Sweden and established a four-step homogenization procedure to generate the first 10-member centennial homogenized WS dataset (HomogWS-se) for community uses among climatology, ecology, hydrology and energy industry. HomogWS-se can be used to study the WS variability and change, assess climate reanalysis, and constrain climate simulations for better future projection of changes in the WS and wind energy potential. HomogWS-se contains 13 individual text files with 10-member century-long homogenized monthly WS series, as well as the member-mean series.
description: {"references": ["Zhou, C., C. Azorin-Molina, E. Engstr\u00f6m, L. Wern, S. Hellstr\u00f6m, and D. Chen, 2022: A century-long homogenized dataset of near-surface wind speed observations since 1925 rescued in Sweden. Earth Syst. Sci. Data, 1-24, 10.5194/essd-2022-29."]}
DOI: 10.3886/icpsr03668.v1
title: Survey of Income and Program Participation (SIPP) 1996 Panel, Longitudinal Files
title: Version 1

description: This data collection contains basic demographic, social, and economic data for each member of interviewed households during the 12 waves of the 1996 panel of SIPP. Variables include age, sex, race, ethnic origin, marital status, household relationship, education, and veteran status. Limited data are provided on housing unit characteristics such as number of units in structure, tenure, access, and complete kitchen facilities. Core questions, repeated at each interview, cover monthly labor force activity, types and amounts of monthly income, and participation in various cash and noncash benefit programs for each month of the survey period. Data for employed persons include number of hours and weeks worked, earnings, and weeks without a job. Nonworkers are classified as unemployed or not in the labor force. In addition to income data associated with labor force activity, nearly 50 other types of income data are provided. Core data also include post-secondary school attendance, public or private subsidized rental housing, low-income energy assistance, and school breakfast and lunch participation. Several variables are included for use in identifying longitudinal households and persons in them and to aid in analysis.
description: A multistage stratified sampling design was used. One-fourth of the sample households were interviewed each month, and households were reinterviewed at four-month intervals. All persons at least 15 years old who were present as household members at the time of the first interview were included for the entire study, except those who joined the military, were institutionalized for the entire study period, or moved from the United States. Original household members who moved during the study period were followed to their new residences and interviewed there. New persons moving into households of members of the original sample also were included in the survey but were not followed if they left the household of an original sample person.
description: Datasets: DS0: Study-Level Files DS1: Wave 1 Core Longitudinal File DS2: Wave 2 Core Longitudinal File DS3: Wave 3 Core Longitudinal File DS4: Wave 4 Core Longitudinal File DS5: Wave 5 Core Longitudinal File DS6: Wave 6 Core Longitudinal File DS7: Wave 7 Core Longitudinal File DS8: Wave 8 Core Longitudinal File DS9: Wave 9 Core Longitudinal File DS10: Wave 10 Core Longitudinal File DS11: Wave 11 Core Longitudinal File DS12: Wave 12 Core Longitudinal File DS13: Longitudinal Weight File
description: The resident population of the United States, excluding persons living in institutions and military barracks.
DOI: 10.3886/icpsr03749.v1
title: Uniform Crime Reporting Program Data [United States]: Police Employee (LEOKA) Data, 2001
title: Version 1

description: Since 1930, the Federal Bureau of Investigation has compiled the Uniform Crime Reports (UCR) to serve as a periodic nationwide assessment of reported crimes not available elsewhere in the criminal justice system. Each year, this information is reported in four types of files: (1) Offenses Known and Clearances by Arrest, (2) Property Stolen and Recovered, (3) Supplementary Homicide Reports (SHR), and (4) Police Employee (LEOKA) Data. The Police Employee (LEOKA) Data provide information about law enforcement officers killed or assaulted (hence the acronym, LEOKA) in the line of duty. The variables created from the LEOKA forms provide in-depth information on the circumstances surrounding killings or assaults, including type of call answered, type of weapon used, and type of patrol the officers were on.
description: inap.
description: Datasets: DS1: Uniform Crime Reporting Program Data [United States]: Police Employee (LEOKA) Data, 2001
description: Law enforcement officers killed or assaulted as reported by law enforcement agencies.
description: The codebook for this collection is provided as a Portable Document Format (PDF) file. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using PDF reader software, such as the Adobe Acrobat Reader. Information on how to obtain a copy of the Acrobat Reader is provided on the ICPSR Web site.
DOI: 10.3886/icpsr03679.v1
title: Australian [Adelaide] Longitudinal Study of Aging, Wave 6: [1999-2000]
title: Version 1

description: The general purpose of the Australian [Adelaide] Longitudinal Study of Aging (ALSA) is to gain further understanding of how social, biomedical, and environmental factors are associated with age-related changes in the health and well-being of persons aged 70 years and older. Emphasis is given to the effects of social and economic factors on morbidity, disability, acute and long-term care service use, and mortality. The aim is to analyze the complex relationships between individual and social factors and changes in health status, health care needs, and service utilization dimensions. Components of Wave 6 (1999-2000) (Part 1) include a comprehensive personal interview conducted via the Computer-Assisted Personal Interview (CAPI) system, a home-based assessment of physiological functions, self-completed questionnaires, and additional clinical studies. In Part 2, Wave 6 Clinical Data, information about the health histories of the respondents was elicited, including information on medication, blood pressure, and physical and mental disabilities.
description: The sample was randomly generated from within the Adelaide Statistical Division using the State Electoral Data Base as the sampling frame. The sample was stratified by gender and by the age groups 70-74, 75-79, 80-84, and 85 and older. Both community and institutionalized individuals were included. In addition, spouses aged 65 and older of specified persons also were invited to participate, as were other household members aged 70 years and older.
description: Datasets: DS0: Study-Level Files DS1: Wave 6 Data DS2: Wave 6 Clinical Data
description: Persons aged 70 and older living in the metropolitan area of Adelaide, South Australia.
DOI: 10.3886/icpsr03723.v1
title: Uniform Crime Reporting Program Data [United States]: Offenses Known and Clearances by Arrest, 2001
title: Version 1

description: Since 1930, the Federal Bureau of Investigation has compiled the Uniform Crime Reports (UCR) to serve as periodic nationwide assessments of reported crimes not available elsewhere in the criminal justice system. Law enforcement agencies contribute reports either directly or through their state reporting programs. Each year, summary data are reported in four types of files: (1) Offenses Known and Clearances by Arrest, (2) Property Stolen and Recovered, (3) Supplementary Homicide Reports (SHR), and (4) Police Employee (LEOKA) Data. The Offenses Known and Clearances by Arrest data files include monthly data on the number of Crime Index offenses reported and the number of offenses cleared by arrest or other means. The counts include all reports of Index Crimes (excluding arson) received from victims, officers who discovered infractions, or other sources.
description: inap.
description: Datasets: DS1: Uniform Crime Reporting Program Data [United States]: Offenses Known and Clearances by Arrest, 2001
description: Index crimes reported by law enforcement agencies in the United States.
description: Starting with the year 1998, each of the four types of UCR summary data archived by ICPSR is released as a separate study under its own study number. Offenses Known and Clearances by Arrest data for the years 1975-1997 can be found in UNIFORM CRIME REPORTING PROGRAM DATA: [UNITED STATES] (ICPSR 9028).
DOI: 10.3886/icpsr03760.v2
title: Uniform Crime Reporting Program Data [United States]: Arrests by Age, Sex, and Race, 2001
title: Version 2

description: These data provide information on the number of arrests reported to the Federal Bureau of Investigation's Uniform Crime Reporting (UCR) Program each year by police agencies in the United States. These arrest reports provide data on 43 offenses including violent crime, drug use, gambling, and larceny. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, 1 to 12 monthly header records, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.
description: Datasets: DS1: Uniform Crime Reporting Program Data [United States]: Arrests by Age, Sex, and Race, 2001
description: Arrests reported to the Federal Bureau of Investigation's Uniform Crime Reporting program.
description: mail questionnaire
DOI: 10.6084/m9.figshare.19550761.v1
title: SuicideBD: A Suicidal Dataset for Bangladesh

description: This dataset contains individual details who committed suicide in Bangladesh during the Pandemic between February, 2020 to November, 2020. This dataset includes details of every individuals who committed suicide like personal details, family & social life, profession, financial condition, methods of committing suicide, location and weather info. The dataset is freely available. The major fields included in this dataset are: age group, age, gender, profession group, reason, method, suicide date & time, addiction status, mental status, economic condition, marital status, family details, academic qualification, weather. Apart from the above data this dataset also contains a CSV file of a Bengali wordcloud built on social media posts of the suicide victims.
DOI: 10.3886/icpsr03818.v3
title: Harvard School of Public Health College Alcohol Study, 1999
title: Version 3

description: This survey interviewed students at colleges that participated in the first two rounds of the HARVARD SCHOOL OF PUBLIC HEALTH COLLEGE ALCOHOL STUDY, which were conducted in 1993 and 1997 (ICPSR 6577 and 3163). As in the previous surveys, the 1999 survey focused on alcohol use and alcohol problems among undergraduate college students. The survey collected information on students' use of alcohol, tobacco, and illicit drugs, views on campus alcohol policies and student alcohol use, reasons for drinking alcohol and reasons for not drinking or limiting drinking, and personal difficulties caused by drinking problems (e.g., missed classes, trouble with police, and health problems). Additional topics covered by the survey include overall health status, daily activities, satisfaction with education being received, grade-point average, living arrangements, social life, sexual activity (heterosexual, homosexual, and bisexual), use of condoms during sexual intercourse, date rape, drunk driving, and attendance in meetings of Alcoholics Anonymous. Background variables include age, height, weight, sex, marital status, religion, mother's and father's education, mother's and father's drinking habits, race, and Hispanic origin.
description: A random sample of students was selected from 128 schools using probability proportionate to size sampling of colleges and universities. However, the data only include the 119 schools in the analytic sample of the 2001 round of the HARVARD SCHOOL OF PUBLIC HEALTH COLLEGE ALCOHOL STUDY (ICPSR 4291). Of the 120 schools surveyed for the 2001 round, 119 met the response rate cutoff for inclusion in that year's analytic sample. The last ICPSR version of this study (i.e., the first version of ICPSR 3818) only included the 119 schools of the 1999 analytic sample, which were slightly different from the 119 schools in the 2001 analytic sample. In 1999, 119 of the 128 schools surveyed met the response rate cutoff for inclusion in the 1999 analytic sample.
description: Datasets: DS1: Harvard School of Public Health College Alcohol Study, 1999
description: Full-time undergraduate students enrolled in four-year colleges or universities in the United States.
description: mail questionnaireGenerated by the SAS CPORT procedure, the SAS transport file comprises the data and a formats catalog with the value labels.ICPSR did not receive any code descriptions for variable COLL_ID (college ID number). Consequently, individual colleges cannot be identified by name with this variable.This survey is the third round of the HARVARD SCHOOL OF PUBLIC HEALTH COLLEGE ALCOHOL STUDY. The first round was conducted in 1993 (ICPSR 6577), the second in 1997 (ICPSR 3163), and a fourth round was conducted in 2001 (ICPSR 4291).
DOI: 10.6084/m9.figshare.19601460.v1
title: Bayesian Bootstrap Spike-and-Slab LASSO

description: The impracticality of posterior sampling has prevented the widespread adoption of spike-and-slab priors in high-dimensional applications. To alleviate the computational burden, optimization strategies have been proposed that quickly find local posterior modes. Trading off uncertainty quantification for computational speed, these strategies have enabled spike-and-slab deployments at scales that would be previously unfeasible. We build on one recent development in this strand of work: the Spike-and-Slab LASSO procedure. Instead of optimization, however, we explore multiple avenues for posterior sampling, some traditional and some new. Intrigued by the speed of Spike-and-Slab LASSO mode detection, we explore the possibility of sampling from an approximate posterior by performing MAP optimization on many independently perturbed datasets. To this end, we explore Bayesian bootstrap ideas and introduce a new class of jittered Spike-and-Slab LASSO priors with random shrinkage targets. These priors are a key constituent of the <i>Bayesian Bootstrap Spike-and-Slab LASSO</i> (BB-SSL) method proposed here. BB-SSL turns fast optimization into approximate posterior sampling. Beyond its scalability, we show that BB-SSL has a strong theoretical support. Indeed, we find that the induced pseudo-posteriors contract around the truth at a near-optimal rate in sparse normal-means and in high-dimensional regression. We compare our algorithm to the traditional Stochastic Search Variable Selection (under Laplace priors) as well as many state-of-the-art methods for shrinkage priors. We show, both in simulations and on real data, that our method fares very well in these comparisons, often providing substantial computational gains. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.19601460
title: Bayesian Bootstrap Spike-and-Slab LASSO

description: The impracticality of posterior sampling has prevented the widespread adoption of spike-and-slab priors in high-dimensional applications. To alleviate the computational burden, optimization strategies have been proposed that quickly find local posterior modes. Trading off uncertainty quantification for computational speed, these strategies have enabled spike-and-slab deployments at scales that would be previously unfeasible. We build on one recent development in this strand of work: the Spike-and-Slab LASSO procedure. Instead of optimization, however, we explore multiple avenues for posterior sampling, some traditional and some new. Intrigued by the speed of Spike-and-Slab LASSO mode detection, we explore the possibility of sampling from an approximate posterior by performing MAP optimization on many independently perturbed datasets. To this end, we explore Bayesian bootstrap ideas and introduce a new class of jittered Spike-and-Slab LASSO priors with random shrinkage targets. These priors are a key constituent of the <i>Bayesian Bootstrap Spike-and-Slab LASSO</i> (BB-SSL) method proposed here. BB-SSL turns fast optimization into approximate posterior sampling. Beyond its scalability, we show that BB-SSL has a strong theoretical support. Indeed, we find that the induced pseudo-posteriors contract around the truth at a near-optimal rate in sparse normal-means and in high-dimensional regression. We compare our algorithm to the traditional Stochastic Search Variable Selection (under Laplace priors) as well as many state-of-the-art methods for shrinkage priors. We show, both in simulations and on real data, that our method fares very well in these comparisons, often providing substantial computational gains. Supplementary materials for this article are available online.
DOI: 10.5281/zenodo.6459118
title: Raw Sensor Data for STRIDE Project J "Improving Work Zone Mobility through Planning, Design and Operations"

description: This dataset contains the raw traffic data from 9 sensors located on I-59 southbound near Tuscaloosa, Alabama, from October 3 to October 16, 2016. These data were used in the research for STRIDE Project J "Improving Work Zone Mobility through Planning, Design and Operations" and described in the STRIDE Final Project for this project.
DOI: 10.5281/zenodo.6459117
title: Raw Sensor Data for STRIDE Project J "Improving Work Zone Mobility through Planning, Design and Operations"

description: This dataset contains the raw traffic data from 9 sensors located on I-59 southbound near Tuscaloosa, Alabama, from October 3 to October 16, 2016. These data were used in the research for STRIDE Project J "Improving Work Zone Mobility through Planning, Design and Operations" and described in the STRIDE Final Project for this project.
DOI: 10.5517/ccdc.csd.cc28bd56
title: CCDC 2095357: Experimental Crystal Structure Determination

description: Related Article: Tom Cardeynaels, Marc K. Etherington, Simon Paredis, Andrei S. Batsanov, Jasper Deckers, Kleitos Stavrou, Dirk Vanderzande, Andrew P. Monkman, Benoît Champagne, Wouter Maes|2022|J.Mater.Chem.C|10|5840|doi:10.1039/D1TC04913E
DOI: 10.5517/ccdc.csd.cc28bd67
title: CCDC 2095358: Experimental Crystal Structure Determination

description: Related Article: Tom Cardeynaels, Marc K. Etherington, Simon Paredis, Andrei S. Batsanov, Jasper Deckers, Kleitos Stavrou, Dirk Vanderzande, Andrew P. Monkman, Benoît Champagne, Wouter Maes|2022|J.Mater.Chem.C|10|5840|doi:10.1039/D1TC04913E
DOI: 10.5517/ccdc.csd.cc290pyz
title: CCDC 2115841: Experimental Crystal Structure Determination

description: Related Article: Qin Chen, Ziyang Wang, Yipeng Fan, Zhou Li, Shuhua Zhang, Junhua Luo, Chengmin Ji|2022|J.Mater.Chem.C|10|5882|doi:10.1039/D1TC05699A
DOI: 10.5517/ccdc.csd.cc29fk6j
title: CCDC 2128187: Experimental Crystal Structure Determination

description: Related Article: Richard J. Mandle, Laurence C. Abbott, Luma Fritsch, Rachel R. Parker, Sam Hart, Adrian C. Whitwood, Stephen J. Cowling, John N. Moore, John W. Goodby|2022|J.Mater.Chem.C|10|5934|doi:10.1039/D1TC05954H
DOI: 10.5517/ccdc.csd.cc29fk7k
title: CCDC 2128188: Experimental Crystal Structure Determination

description: Related Article: Richard J. Mandle, Laurence C. Abbott, Luma Fritsch, Rachel R. Parker, Sam Hart, Adrian C. Whitwood, Stephen J. Cowling, John N. Moore, John W. Goodby|2022|J.Mater.Chem.C|10|5934|doi:10.1039/D1TC05954H
DOI: 10.5517/ccdc.csd.cc29fk8l
title: CCDC 2128189: Experimental Crystal Structure Determination

description: Related Article: Richard J. Mandle, Laurence C. Abbott, Luma Fritsch, Rachel R. Parker, Sam Hart, Adrian C. Whitwood, Stephen J. Cowling, John N. Moore, John W. Goodby|2022|J.Mater.Chem.C|10|5934|doi:10.1039/D1TC05954H
DOI: 10.5517/ccdc.csd.cc29fk9m
title: CCDC 2128190: Experimental Crystal Structure Determination

description: Related Article: Richard J. Mandle, Laurence C. Abbott, Luma Fritsch, Rachel R. Parker, Sam Hart, Adrian C. Whitwood, Stephen J. Cowling, John N. Moore, John W. Goodby|2022|J.Mater.Chem.C|10|5934|doi:10.1039/D1TC05954H
DOI: 10.5517/ccdc.csd.cc29fkbn
title: CCDC 2128191: Experimental Crystal Structure Determination

description: Related Article: Richard J. Mandle, Laurence C. Abbott, Luma Fritsch, Rachel R. Parker, Sam Hart, Adrian C. Whitwood, Stephen J. Cowling, John N. Moore, John W. Goodby|2022|J.Mater.Chem.C|10|5934|doi:10.1039/D1TC05954H
DOI: 10.5517/ccdc.csd.cc29k1c9
title: CCDC 2131540: Experimental Crystal Structure Determination

description: Related Article: Qichuan Hu, Hailong Yu, Shunfa Gong, Qiuju Han, Wenzhi Wu|2022|J.Mater.Chem.C|10|6002|doi:10.1039/D2TC00382A
DOI: 10.15784/601544
title: AMIGOS-IIIa "Cavity" Seabird CTD data Jan 2020 - Dec 2021

description: Seabird MicroCAT SBE37IMP data spanning two years (with data gaps) at the Cavity site AMIGOS (Automated Meteorology-Ice-Geophysics Observing System) on the Thwaites Eastern Ice Shelf, Antarctica. Data are reported as the uncalibrated numbers from the sensors delivered through the inductive modem to the AMIGOS system and uplinked via Iridium. Calibration information and test runs against a retrieved CTD unit are provided.
DOI: 10.5523/bris.lxp8eavh7wnn2p57q98rcn2go
title: Nucleation increases the visual appeal of lager but does not alter overall likeability or drinking rate (study 2)

description: This human laboratory experimental study investigated whether nucleation texture in drinking glasses alters the time taken to consume an alcoholic beverage. Participants (n = 162) were asked to drink standard strength lager from either a non-nucleated or nucleated glass. Likeability of lager and time to consume the drink were recorded.
DOI: 10.3886/icpsr03952.v1
title: Status of Older Persons in Economic Commission for Europe (ECE) Countries, Census Microdata Samples: Lithuania, 1989
title: Version 1

description: The main objectives of this data collection effort were to assemble a set of cross-nationally comparable microdata samples based on the 1990 national population and housing censuses in countries of Europe and North America, and to use these samples to study the social and economic conditions of older persons. The samples are designed to allow research on a wide range of issues related to aging, as well as on other social phenomena. Data collected in the 1989 Lithuanian census examined the type and size of dwelling units, household composition, and employment history. Also gathered was demographic information on household members, including age, sex, ethnic background, marital status, fertility, education, employment status, income, and occupation.
description: Lithuania's dataset includes the entire population of the country over age 50, as well as persons below that age who co-resided in the same dwelling unit with someone over age 50.
description: Datasets: DS1: Status of Older Persons in Economic Commission for Europe (ECE) Countries, Census Microdata Samples: Lithuania, 1989
description: All persons and housing units in Lithuania in 1989.
description: In addition to the SAS transport file provided by the principal investigator, ICPSR is distributing an ASCII data file with SPSS and SAS program information extracted from the SAS file using StatTransfer. Analysis of the ASCII file may be facilitated by dividing it.The data contain undocumented codes.