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Found 15 result(s)
!!! >>> the repository is offline, data can be found here: https://osf.io/gjp53/ <<< !!! Our lab investigates how cognition manifests in, and is influenced by, the social contexts in which it occurs. We focus: 1) on how conversational interactions can reshape memory, by promoting shared remembering and shared forgetting, and 2) on how socio-cognitive processes affect the formation of collective memories and beliefs, and the dynamics of collective decisions. In exploring these issues, while maintaining high ecological validity, our lab integrates a wide range of methodologies, including laboratory experiments, field studies, social network analysis, and agent-based simulations.
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.
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.
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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 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.
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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.
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DataDOI is an institutional research data repository managed by University of Tartu Library. DataDOI gathers all fields of research data and stands for encouraging open science and FAIR (Findable, Accessible, Interoperable, Reusable) principles. DataDOI is made for long-term preservation of research data. Each dataset is given a DOI (Digital Object Identifier) through DataCite Estonia Concortium.
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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 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.