4 datasets found
  1. n

    Coronavirus (Covid-19) Data in the United States

    • nytimes.com
    • openicpsr.org
    • +3more
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    New York Times, Coronavirus (Covid-19) Data in the United States [Dataset]. https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html
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    Dataset provided by
    New York Times
    Description

    The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

    Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

    We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

    The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

  2. Z

    Albero study: a longitudinal database of the social network and personal...

    • data.niaid.nih.gov
    • zenodo.org
    Updated Mar 26, 2021
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    Maya Jariego, Isidro (2021). Albero study: a longitudinal database of the social network and personal networks of a cohort of students at the end of high school [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_3532047
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    Dataset updated
    Mar 26, 2021
    Dataset provided by
    Maya Jariego, Isidro
    Alieva, Deniza
    Holgado Ramos, Daniel
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    ABSTRACT

    The Albero study analyzes the personal transitions of a cohort of high school students at the end of their studies. The data consist of (a) the longitudinal social network of the students, before (n = 69) and after (n = 57) finishing their studies; and (b) the longitudinal study of the personal networks of each of the participants in the research. The two observations of the complete social network are presented in two matrices in Excel format. For each respondent, two square matrices of 45 alters of their personal networks are provided, also in Excel format. For each respondent, both psychological sense of community and frequency of commuting is provided in a SAV file (SPSS). The database allows the combined analysis of social networks and personal networks of the same set of individuals.

    INTRODUCTION

    Ecological transitions are key moments in the life of an individual that occur as a result of a change of role or context. This is the case, for example, of the completion of high school studies, when young people start their university studies or try to enter the labor market. These transitions are turning points that carry a risk or an opportunity (Seidman & French, 2004). That is why they have received special attention in research and psychological practice, both from a developmental point of view and in the situational analysis of stress or in the implementation of preventive strategies.

    The data we present in this article describe the ecological transition of a group of young people from Alcala de Guadaira, a town located about 16 kilometers from Seville. Specifically, in the “Albero” study we monitored the transition of a cohort of secondary school students at the end of the last pre-university academic year. It is a turning point in which most of them began a metropolitan lifestyle, with more displacements to the capital and a slight decrease in identification with the place of residence (Maya-Jariego, Holgado & Lubbers, 2018).

    Normative transitions, such as the completion of studies, affect a group of individuals simultaneously, so they can be analyzed both individually and collectively. From an individual point of view, each student stops attending the institute, which is replaced by new interaction contexts. Consequently, the structure and composition of their personal networks are transformed. From a collective point of view, the network of friendships of the cohort of high school students enters into a gradual process of disintegration and fragmentation into subgroups (Maya-Jariego, Lubbers & Molina, 2019).

    These two levels, individual and collective, were evaluated in the “Albero” study. One of the peculiarities of this database is that we combine the analysis of a complete social network with a survey of personal networks in the same set of individuals, with a longitudinal design before and after finishing high school. This allows combining the study of the multiple contexts in which each individual participates, assessed through the analysis of a sample of personal networks (Maya-Jariego, 2018), with the in-depth analysis of a specific context (the relationships between a promotion of students in the institute), through the analysis of the complete network of interactions. This potentially allows us to examine the covariation of the social network with the individual differences in the structure of personal networks.

    PARTICIPANTS

    The social network and personal networks of the students of the last two years of high school of an institute of Alcala de Guadaira (Seville) were analyzed. The longitudinal follow-up covered approximately a year and a half. The first wave was composed of 31 men (44.9%) and 38 women (55.1%) who live in Alcala de Guadaira, and who mostly expect to live in Alcala (36.2%) or in Seville (37.7%) in the future. In the second wave, information was obtained from 27 men (47.4%) and 30 women (52.6%).

    DATE STRUCTURE AND ARCHIVES FORMAT

    The data is organized in two longitudinal observations, with information on the complete social network of the cohort of students of the last year, the personal networks of each individual and complementary information on the sense of community and frequency of metropolitan movements, among other variables.

    Social network

    The file “Red_Social_t1.xlsx” is a valued matrix of 69 actors that gathers the relations of knowledge and friendship between the cohort of students of the last year of high school in the first observation. The file “Red_Social_t2.xlsx” is a valued matrix of 57 actors obtained 17 months after the first observation.

    The data is organized in two longitudinal observations, with information on the complete social network of the cohort of students of the last year, the personal networks of each individual and complementary information on the sense of community and frequency of metropolitan movements, among other variables.

    In order to generate each complete social network, the list of 77 students enrolled in the last year of high school was passed to the respondents, asking that in each case they indicate the type of relationship, according to the following values: 1, “his/her name sounds familiar"; 2, "I know him/her"; 3, "we talk from time to time"; 4, "we have good relationship"; and 5, "we are friends." The two resulting complete networks are represented in Figure 2. In the second observation, it is a comparatively less dense network, reflecting the gradual disintegration process that the student group has initiated.

    Personal networks

    Also in this case the information is organized in two observations. The compressed file “Redes_Personales_t1.csv” includes 69 folders, corresponding to personal networks. Each folder includes a valued matrix of 45 alters in CSV format. Likewise, in each case a graphic representation of the network obtained with Visone (Brandes and Wagner, 2004) is included. Relationship values range from 0 (do not know each other) to 2 (know each other very well).

    Second, the compressed file “Redes_Personales_t2.csv” includes 57 folders, with the information equivalent to each respondent referred to the second observation, that is, 17 months after the first interview. The structure of the data is the same as in the first observation.

    Sense of community and metropolitan displacements

    The SPSS file “Albero.sav” collects the survey data, together with some information-summary of the network data related to each respondent. The 69 rows correspond to the 69 individuals interviewed, and the 118 columns to the variables related to each of them in T1 and T2, according to the following list:

     • Socio-economic data.
    
    
     • Data on habitual residence.
    
    
     • Information on intercity journeys.
    
    
     • Identity and sense of community.
    
    
     • Personal network indicators.
    
    
     • Social network indicators.
    

    DATA ACCESS

    Social networks and personal networks are available in CSV format. This allows its use directly with UCINET, Visone, Pajek or Gephi, among others, and they can be exported as Excel or text format files, to be used with other programs.

    The visual representation of the personal networks of the respondents in both waves is available in the following album of the Graphic Gallery of Personal Networks on Flickr: https://www.flickr.com/photos/25906481@N07/albums/72157667029974755.

    In previous work we analyzed the effects of personal networks on the longitudinal evolution of the socio-centric network. It also includes additional details about the instruments applied. In case of using the data, please quote the following reference:

    Maya-Jariego, I., Holgado, D. & Lubbers, M. J. (2018). Efectos de la estructura de las redes personales en la red sociocéntrica de una cohorte de estudiantes en transición de la enseñanza secundaria a la universidad. Universitas Psychologica, 17(1), 86-98. https://doi.org/10.11144/Javeriana.upsy17-1.eerp

    The English version of this article can be downloaded from: https://tinyurl.com/yy9s2byl

    CONCLUSION

    The database of the “Albero” study allows us to explore the co-evolution of social networks and personal networks. In this way, we can examine the mutual dependence of individual trajectories and the structure of the relationships of the cohort of students as a whole. The complete social network corresponds to the same context of interaction: the secondary school. However, personal networks collect information from the different contexts in which the individual participates. The structural properties of personal networks may partly explain individual differences in the position of each student in the entire social network. In turn, the properties of the entire social network partly determine the structure of opportunities in which individual trajectories are displayed.

    The longitudinal character and the combination of the personal networks of individuals with a common complete social network, make this database have unique characteristics. It may be of interest both for multi-level analysis and for the study of individual differences.

    ACKNOWLEDGEMENTS

    The fieldwork for this study was supported by the Complementary Actions of the Ministry of Education and Science (SEJ2005-25683), and was part of the project “Dynamics of actors and networks across levels: individuals, groups, organizations and social settings” (2006 -2009) of the European Science Foundation (ESF). The data was presented for the first time on June 30, 2009, at the European Research Collaborative Project Meeting on Dynamic Analysis of Networks and Behaviors, held at the Nuffield College of the University of Oxford.

    REFERENCES

    Brandes, U., & Wagner, D. (2004). Visone - Analysis and Visualization of Social Networks. In M. Jünger, & P. Mutzel (Eds.), Graph Drawing Software (pp. 321-340). New York: Springer-Verlag.

    Maya-Jariego, I. (2018). Why name generators with a fixed number of alters may be

  3. t

    Police Incidents

    • data.townofcary.org
    • s.cnmilf.com
    • +2more
    csv, excel, geojson +1
    Updated Feb 27, 2025
    + more versions
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    (2025). Police Incidents [Dataset]. https://data.townofcary.org/explore/dataset/cpd-incidents/
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    json, csv, excel, geojsonAvailable download formats
    Dataset updated
    Feb 27, 2025
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This dataset contains Crime and Safety data from the Cary Police Department.

    This data is extracted by the Town of Cary's Police Department's RMS application. The police incidents will provide data on the Part I crimes of arson, motor vehicle thefts, larcenies, burglaries, aggravated assaults, robberies and homicides. Sexual assaults and crimes involving juveniles will not appear to help protect the identities of victims.

    This dataset includes criminal offenses in the Town of Cary for the previous 10 calendar years plus the current year. The data is based on the National Incident Based Reporting System (NIBRS) which includes all victims of person crimes and all crimes within an incident. The data is dynamic, which allows for additions, deletions and/or modifications at any time, resulting in more accurate information in the database. Due to continuous data entry, the number of records in subsequent extractions are subject to change. Crime data is updated daily however, incidents may be up to three days old before they first appear.

    About Crime Data

    The Cary Police Department strives to make crime data as accurate as possible, but there is no avoiding the introduction of errors into this process, which relies on data furnished by many people and that cannot always be verified. Data on this site are updated daily, adding new incidents and updating existing data with information gathered through the investigative process.

    This dynamic nature of crime data means that content provided here today will probably differ from content provided a week from now. Additional, content provided on this site may differ somewhat from crime statistics published elsewhere by other media outlets, even though they draw from the same database.

    Withheld Data

    In accordance with legal restrictions against identifying sexual assault and child abuse victims and juvenile perpetrators, victims, and witnesses of certain crimes, this site includes the following precautionary measures: (a) Addresses of sexual assaults are not included. (b) Child abuse cases, and other crimes which by their nature involve juveniles, or which the reports indicate involve juveniles as victims, suspects, or witnesses, are not reported at all.

    Certain crimes that are under current investigation may be omitted from the results in avoid comprising the investigative process.

    Incidents five days old or newer may not be included until the internal audit process has been completed.

    This data is updated daily.

  4. c

    European Values Study 2017: Integrated Dataset (EVS 2017)

    • datacatalogue.cessda.eu
    • search.gesis.org
    • +1more
    Updated Mar 15, 2023
    + more versions
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    Gedeshi, Ilir; Pachulia, Merab; Poghosyan, Gevorg; Rotman, David; Kritzinger, Sylvia; Fotev, Georgy; Kolenović-Đapo, Jadranka; Baloban, Josip; Baloban, Stjepan; Rabušic, Ladislav; Frederiksen, Morten; Saar, Erki; Ketola, Kimmo; Wolf, Christof; Pachulia, Merab; Bréchon, Pierre; Voas, David; Rosta, Gergely; Jónsdóttir, Guðbjörg A.; Rovati, Giancarlo; Ziliukaite, Ruta; Petkovska, Antoanela; Komar, Olivera; Reeskens, Tim; Jenssen, Anders T.; Soboleva, Natalia; Marody, Mirosława; Voicu, Bogdan; Strapcová, Katarina; Bešić, Miloš; Uhan, Samo; Silvestre Cabrera, María; Wallman-Lundåsen, Susanne; Ernst Stähli, Michèle; Ramos, Alice; Balakireva, Olga; Mieriņa, Inta (2023). European Values Study 2017: Integrated Dataset (EVS 2017) [Dataset]. http://doi.org/10.4232/1.13897
    Explore at:
    Dataset updated
    Mar 15, 2023
    Dataset provided by
    Kirkon tutkimuskeskus, Tampere, Finland
    Institut d’études politiques de Grenoble, Grenoble, France
    Center for Economic and Social Studies (CESS), Tirana, Albania
    Catholic Faculty of Theology, University of Zagreb, Zagreb, Croatia (since September 2019)
    Department of Sociology, Catholic University of the Sacred Heart, Milan, Italy
    Research institute for Quality of Life, Romanian Academy of Science, Bucharest, Romania
    Catholic Faculty of Theology, University of Zagreb, Zagreb, Croatia
    De Facto Consultancy, Podgorica, Montenegro
    Department of Sociology, Pázmány Péter Catholic University, Budapest, Hungary
    Faculty for Social Wellbeing, New Bulgarian University, Sofia, Bulgaria
    Department of Social Science, University College London, Great Britain
    Faculty of Social Sciences, Public Opinion and Mass Communication Research, University of Ljubljana, Ljubljana, Slovenia
    Faculty of Political Sciences and Sociology, Deusto University, Bilbao, Spain
    Laboratory for Comparative Social Research, Higher School of Economics, Moscow, Russia
    Institute Economy and Prognoses, National Academy of Ukraine, Department of Monitoring Research of the Social and Economic Process, Kiev, Ukraine
    Social Science Research Institute, University of Iceland, Reykjavik, Iceland
    Saar Poll, Tallinn, Estonia
    Department of Social Sciences, GESIS - Leibniz Institute for the Social Sciences, Mannheim, Germany
    GORBI (Georgian Opinion Research Business International), Tbilisi, Georgia
    Department of Sociology, Tilburg University, Tilburg, Netherlands
    Department of Social Sciences, Mid Sweden University, Sundsvall, Sweden
    Instituto de Ciências Sociais, Universidade de Lisboa, Portugal
    Faculty of Philosophy, University of Sarajevo, Bosnia and Herzegovina
    Department of Sociology, Ss. Cyril and Methodius University, Skopje, North Macedonia
    Faculty of Political Sciences, University of Belgrade, Serbia
    SORGU, Baku, Azerbaijan
    Department of Sociology and Political Science, Norwegian University of Science and Technology, Norway
    Department of Government, University of Vienna, Vienna, Austria
    University of Latvia, Riga, Latvia
    Statistics Denmark, Copenhagen, Denmark
    Institute of Philosophy, Sociology and Law, Armenian National Academy of Sciences, Yerevan, Armenia
    Institute for Sociology, Slovak Academy of Sciences, Bratislava, Slovak Republic
    The Center of Sociological and Political Research, Belarus State University, Minsk, Belarus
    Department of Sociology, Vilnius University, Lithuania
    FORS, Swiss Foundation for Research in Social Sciences, Université de Lausanne, Lausanne, Switzerland
    Institute of Sociology, University of Warsaw
    Faculty of Social Studies, Masaryk University, Brno, Czech Republic
    Authors
    Gedeshi, Ilir; Pachulia, Merab; Poghosyan, Gevorg; Rotman, David; Kritzinger, Sylvia; Fotev, Georgy; Kolenović-Đapo, Jadranka; Baloban, Josip; Baloban, Stjepan; Rabušic, Ladislav; Frederiksen, Morten; Saar, Erki; Ketola, Kimmo; Wolf, Christof; Pachulia, Merab; Bréchon, Pierre; Voas, David; Rosta, Gergely; Jónsdóttir, Guðbjörg A.; Rovati, Giancarlo; Ziliukaite, Ruta; Petkovska, Antoanela; Komar, Olivera; Reeskens, Tim; Jenssen, Anders T.; Soboleva, Natalia; Marody, Mirosława; Voicu, Bogdan; Strapcová, Katarina; Bešić, Miloš; Uhan, Samo; Silvestre Cabrera, María; Wallman-Lundåsen, Susanne; Ernst Stähli, Michèle; Ramos, Alice; Balakireva, Olga; Mieriņa, Inta
    Time period covered
    Jun 19, 2017 - Oct 1, 2021
    Area covered
    France, Serbia, Georgia, Latvia, Finland, Belarus, Austria, Slovakia, North Macedonia, Sweden
    Measurement technique
    Face-to-face interview: Computer-assisted (CAPI/CAMI), Face-to-face interview: Paper-and-pencil (PAPI), Telephone interview: Computer-assisted (CATI), Self-administered questionnaire: Web-based (CAWI), Self-administered questionnaire: Paper, Mode of collection: mixed modeFace-to-face interview: CAPI (Computer Assisted Personal Interview)Face-to-face interview: PAPI (Paper and Pencil Interview)Telephone interview: CATI (Computer Assisted Telephone Interview) Self-administered questionnaire: CAWI (Computer-Assisted Web Interview)Self-administered questionnaire: PaperIn all countries, fieldwork was conducted on the basis of detailed and uniform instructions prepared by the EVS advisory groups. The main mode in EVS 2017 is face to face (interviewer-administered). An alternative self-administered form was possible but as a parallel mixed mode, i.e. there was no choice for the respondent between modes: either s/he was assigned to face to face, either s/he was assigned to web or web/mail format. In all countries included in the first pre-release, the EVS questionnaire was administered as face-to-face interview (CAPI or/and PAPI).The EVS 2017 Master Questionnaire was provided in English and each national Programme Director had to ensure that the questionnaire was translated into all the languages spoken by 5% or more of the population in the country. A central team monitored the translation process by means of the Translation Management Tool (TMT), developed by CentERdata (Tilburg).
    Description

    The European Values Study is a large-scale, cross-national and longitudinal survey research program on how Europeans think about family, work, religion, politics, and society. Repeated every nine years in an increasing number of countries, the survey provides insights into the ideas, beliefs, preferences, attitudes, values, and opinions of citizens all over Europe.

    As previous waves conducted in 1981, 1990, 1999, 2008, the fifth EVS wave maintains a persistent focus on a broad range of values. Questions are highly comparable across waves and regions, making EVS suitable for research aimed at studying trends over time.

    The new wave has seen a strengthening of the methodological standards. The full release of the EVS 2017 includes data and documentation of altogether 37 participating countries. For more information, please go to the EVS website.

    Morale, religious, societal, political, work, and family values of Europeans.

    Topics: 1. Perceptions of life: importance of work, family, friends and acquaintances, leisure time, politics and religion; happiness; self-assessment of own health; memberships in voluntary organisations (religious or church organisations, cultural activities, trade unions, political parties or groups, environment, ecology, animal rights, professional associations, sports, recreation, or other groups, none); active or inactive membership of humanitarian or charitable organisation, consumer organisation, self-help group or mutual aid; voluntary work in the last six months; tolerance towards minorities (people of a different race, heavy drinkers, immigrants, foreign workers, drug addicts, homosexuals, Christians, Muslims, Jews, and gypsies - social distance); trust in people; estimation of people´s fair and helpful behavior; internal or external control; satisfaction with life; importance of educational goals: desirable qualities of children.

    1. Work: attitude towards work (job needed to develop talents, receiving money without working is humiliating, people turn lazy not working, work is a duty towards society, work always comes first); importance of selected aspects of occupational work; give priority to nationals over foreigners as well as men over women in jobs.

    2. Religion and morale: religious denomination; current and former religious denomination; current frequency of church attendance and at the age of 12; self-assessment of religiousness; belief in God, life after death, hell, heaven, and re-incarnation; personal god vs. spirit or life force; importance of God in one´s life (10-point-scale); frequency of prayers; morale attitudes (scale: claiming state benefits without entitlement, cheating on taxes, taking soft drugs, accepting a bribe, homosexuality, abortion, divorce, euthanasia, suicide, paying cash to avoid taxes, casual sex, avoiding fare on public transport, prostitution, in-vitro fertilization, political violence, death penalty).

    3. Family: trust in family; most important criteria for a successful marriage or partnership (faithfulness, adequate income, good housing, sharing household chores, children, time for friends and personal hobbies); marriage is an outdated institution; attitude towards traditional understanding of one´s role of man and woman in occupation and family (gender roles); homosexual couples are as good parents as other couples; duty towards society to have children; responsibility of adult children for their parents when they are in need of long-term care; to make own parents proud is a main goal in life.

    4. Politics and society: political interest; political participation; preference for individual freedom or social equality; self-assessment on a left-right continuum (10-point-scale) (left-right self-placement); individual vs. state responsibility for providing; take any job vs. right to refuse job when unemployed; competition good vs. harmful for people; equal incomes vs. incentives for individual effort; private vs. government ownership of business and industry; postmaterialism (scale); most important aims of the country for the next ten years; willingness to fight for the country; expectation of future development (less importance placed on work and greater respect for authority); trust in institutions; essential characteristics of democracy; importance of democracy for the respondent; rating democracy in own country; satisfaction with the political system in the country; preferred type of political system (strong leader, expert decisions, army should rule the country, or democracy); vote in elections on local level, national level and European level; political party with the most appeal; another political party that most appeals; assessment of country´s elections (votes are counted fairly, opposition candidates are prevented from running, TV news favors the governing party, voters are bribed, journalists provide fair coverage of elections, election officials are fair, rich people buy elections, voters are threatened with violence at the...

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New York Times, Coronavirus (Covid-19) Data in the United States [Dataset]. https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html

Coronavirus (Covid-19) Data in the United States

Explore at:
Dataset provided by
New York Times
Description

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

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