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Found 22 result(s)
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One of the world’s largest banks of biological, psychosocial and clinical data on people suffering from mental health problems. The Signature center systematically collects biological, psychosocial and clinical indicators from patients admitted to the psychiatric emergency and at four points throughout their journey in the hospital: upon arrival to the emergency room (state of crisis), at the end of their hospital stay, as well as at the beginning and the end of outpatient treatment. For all hospital clients who agree to participate, blood specimens are collected for the purpose of measuring metabolic, genetic, toxic and infectious biomarkers, while saliva samples are collected to measure sex hormones and hair samples are collected to measure stress hormones. Questionnaire has been selected to cover important dimensional aspects of mental illness such as Behaviour and Cognition (Psychosis, Depression, Anxiety, Impulsiveness, Aggression, Suicide, Addiction, Sleep),Socio-demographic Profile (Spiritual beliefs, Social functioning, Childhood experiences, Demographic, Family background) and Medical Data (Medication, Diagnosis, Long-term health, RAMQ data). On 2016, May there are more than 1150 participants and 400 for the longitudinal Follow-Up
Country
Research Data Centres offer a secure access to detailed microdata from Statistics Canada's surveys, and to Canadian censuses' data, as well as to an increasing number of administrative data sets. The search engine was designed to help you find out more easily which dataset among all the surveys available in the RDCs best suits your research needs.
The Cross-National Equivalent File (CNEF) contains population panel data from Australia, Canada, Germany, Great Britain, Korea, Russia, Switzerland and the United States. Each of these countries undertakes a longitudinal household economic survey. The data are made equivalent, providing a reference dataset which cross-links each of the individual studies and allowing cross-national comparisons.
The Humanitarian Data Exchange (HDX) is an open platform for sharing data across crises and organisations. Launched in July 2014, the goal of HDX is to make humanitarian data easy to find and use for analysis. HDX is managed by OCHA's Centre for Humanitarian Data, which is located in The Hague. OCHA is part of the United Nations Secretariat and is responsible for bringing together humanitarian actors to ensure a coherent response to emergencies. The HDX team includes OCHA staff and a number of consultants who are based in North America, Europe and Africa.
The Fragile Families and Child Wellbeing Study changed its name to The Future of Families and Child Wellbeing Study (FFCWS). Note that all documentation issued prior to January 2023 contains the study’s former name. Any further reference to FFCWS should kindly observe this name change. The Fragile Families & Child Wellbeing Study is following a cohort of nearly 5,000 children born in large U.S. cities between 1998 and 2000 (roughly three-quarters of whom were born to unmarried parents). We refer to unmarried parents and their children as “fragile families” to underscore that they are families and that they are at greater risk of breaking up and living in poverty than more traditional families. The core Study was originally designed to primarily address four questions of great interest to researchers and policy makers: (1) What are the conditions and capabilities of unmarried parents, especially fathers?; (2) What is the nature of the relationships between unmarried parents?; (3) How do children born into these families fare?; and (4) How do policies and environmental conditions affect families and children?
Cell phones have become an important platform for the understanding of social dynamics and influence, because of their pervasiveness, sensing capabilities, and computational power. Many applications have emerged in recent years in mobile health, mobile banking, location based services, media democracy, and social movements. With these new capabilities, we can potentially be able to identify exact points and times of infection for diseases, determine who most influences us to gain weight or become healthier, know exactly how information flows among employees and productivity emerges in our work spaces, and understand how rumors spread. In an attempt to address these challenges, we release several mobile data sets here in "Reality Commons" that contain the dynamics of several communities of about 100 people each. We invite researchers to propose and submit their own applications of the data to demonstrate the scientific and business values of these data sets, suggest how to meaningfully extend these experiments to larger populations, and develop the math that fits agent-based models or systems dynamics models to larger populations. These data sets were collected with tools developed in the MIT Human Dynamics Lab and are now available as open source projects or at cost.
The Common Cold Project began in 2011 with the aim of creating, documenting, and archiving a database that combines final research data from 5 prospective viral-challenge studies that were conducted over the preceding 25 years: the British Cold Study (BCS); the three Pittsburgh Cold Studies (PCS1, PCS2, and PCS3); and the Pittsburgh Mind-Body Center Cold Study (PMBC). These unique studies assessed predictor (and hypothesized mediating) variables in healthy adults aged 18 to 55 years, experimentally exposed them to a virus that causes the common cold, and then monitored them for development of infection and signs and symptoms of illness.
Country
sciencedata.dk is a research data store provided by DTU, the Danish Technical University, specifically aimed at researchers and scientists at Danish academic institutions. The service is intended for working with and sharing active research data as well as for safekeeping of large datasets. The data can be accessed and manipulated via a web interface, synchronization clients, file transfer clients or the command line. The service is built on and with open-source software from the ground up: FreeBSD, ZFS, Apache, PHP, ownCloud/Nextcloud. DTU is actively engaged in community efforts on developing research-specific functionality for data stores. Our servers are attached directly to the 10-Gigabit backbone of "Forskningsnettet" (the National Research and Education Network of Denmark) - implying that up and download speed from Danish academic institutions is in principle comparable to those of an external USB hard drive. Data store for research data allowing private sharing and sharing via links / persistent URLs.
The Mexican Health and Aging Study (MHAS) started as a prospective panel study of health and aging in Mexico. MHAS is nationally representative of the 13 million Mexicans born prior to 1951. The survey has national and urban/rural representation. The baseline survey, in 2001, included a nationally representative sample of Mexicans aged 50 and over and their spouse/partners regardless of their age. A direct interview was sought with each individual and proxy interviews were obtained when poor health or temporary absence precluded a direct interview. The sample was distributed in all 32 states of the country in urban and rural areas. Households in the six states which account for 40% of all migrants to the U.S. were over-sampled. A sub-sample was selected to obtain anthropometric measures.
RUresearch Data Portal is a subset of RUcore (Rutgers University Community Repository), provides a platform for Rutgers researchers to share their research data and supplementary resources with the global scholarly community. This data portal leverages all the capabilities of RUcore with additional tools and services specific to research data. It provides data in different clusters (research-genre) with excellent search facility; such as experimental data, multivariate data, discrete data, continuous data, time series data, etc. However it facilitates individual research portals that include the Video Mosaic Collaborative (VMC), an NSF-funded collection of mathematics education videos for Teaching and Research. Its' mission is to maintain the significant intellectual property of Rutgers University; thereby intended to provide open access and the greatest possible impact for digital data collections in a responsible manner to promote research and learning.
The Constituency-Level Elections Archive (CLEA) is a repository of detailed election results at the constituency level for lower house legislative elections from around the world. Our motivation is to preserve and consolidate these valuable data in one comprehensive and reliable resource that is ready for analysis and publicly available at no cost. This public good is expected to be of use to a range of audiences for research, education, and policy-making.
A service of the Inter-university Consortium for Political and Social Research (ICPSR), openICPSR is a self-publishing repository for social, behavioral, and health sciences research data. openICPSR is particularly well-suited for the deposit of replication data sets for researchers who need to publish their raw data associated with a journal article so that other researchers can replicate their findings.
Country
Supported by the DFG, the project „MO|RE data“ assembles a public eResearch-Infrastructure for motor research data until 2016. It focuses on selected standardized motor tests of wide acceptance. Furthermore MO|RE data generates quality authority control and publishes accompanying material for motor tests.
It is a platform for supporting Open Data initiative of Government of Odisha, intends to publish datasets collected by them for public use. It also supports widely used file formats that are suitable for machine processing, thus gives avenues for many more innovative uses of Government Data in different perspective. This portal has been created under Software as A Service (SaaS) model of Open Government Data (OGD) Platform India of NIC. The data available in the portal are owned by various Departments/Organization of Government of Odisha. It follows principles on which data sharing and accessibility need to be based include: Openness, Flexibility, Transparency, Quality, Security and Machine-readable.
Polish CLARIN node – CLARIN-PL Language Technology Centre – is being built at Wrocław University of Technology. The LTC is addressed to scholars in the humanities and social sciences. Registered users are granted free access to digital language resources and advanced tools to explore them. They can also archive and share their own language data (in written, spoken, video or multimodal form).
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More than a quarter of a million people — one in 10 NSW men and women aged over 45 — have been recruited to our 45 and Up Study, the largest ongoing study of healthy ageing in the Southern Hemisphere. The baseline information collected from all of our participants is available in the Study’s Data Book. This information, which researchers use as the basis for their analyses, contains information on key variables such as height, weight, smoking status, family history of disease and levels of physical activity. By following such a large group of people over the long term, we are developing a world-class research resource that can be used to boost our understanding of how Australians are ageing. This will answer important health and quality-of-life questions and help manage and prevent illness through improved knowledge of conditions such as cancer, heart disease, depression, obesity and diabetes.
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The National Data Archive has been disseminating microdata from surveys and censuses primarily under the Ministry of Statistics and Programme Implementation (MoSPI), Government of India. The archive is powered by the National Data Archive (NADA, ver. 4.3) software with DDI Metadata standard. It serves as a portal for researchers to browse, search, and download relevant datasets freely; even with related documentation (viz. survey methodology, sampling procedures, questionnaires, instructions, survey reports, classifications, code directories, etc). A few data files require the user to apply for approval to access with no charge. Currently, the archive holds more than 144 datasets of the National Sample Surveys (NSS), Annual Survey of Industries (ASI), and the Economic Census as available with the Ministry. However, efforts are being made to include metadata of surveys conducted by the State Governments and other government agencies.
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The Cross-National Time-Series Data Archive (CNTS) was initiated by Arthur S. Banks in 1968 with the aim of assembling, in machine readable, longitudinal format, certain of the aggregate data resources of The Statesman’s Yearbook. The CNTS offers a listing of international and national country-data facts. The dataset contains statistical information on a range of countries, with data entries ranging from 1815 to the present.
The Osteoarthritis Initiative (OAI) is a multi-center, longitudinal, prospective observational study of knee osteoarthritis (OA). The overall aim of the OAI is to develop a public domain research resource to facilitate the scientific evaluation of biomarkers for osteoarthritis as potential surrogate endpoints for disease onset and progression.
Country
The GIGA (German Institute of Global and Area Studies) researchers generate a large number of qualitative and quantitative research data. On this page you will find descriptions of this research data ("metadata") as well as information about the available access options. To facilitate its reuse, and to enhance research transparency, a large part of the GIGA research data is published in datorium, a repository hosted by the GESIS Leibniz Institute for the Social Sciences: https://www.re3data.org/repository/r3d100011062 Our objective is to offer free access to as much of our data as possible, to guarantee the possibility of its citation, and to secure its safe storage. Metadata of research data that cannot be published open access due to its sensitivity is also shown on this page.