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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 Abacus Data Network is a data repository collaboration involving Libraries at Simon Fraser University (SFU), the University of British Columbia (UBC), the University of Northern British Columbia (UNBC) and the University of Victoria (UVic).
The Scientific Data Repository Hosting Service (SARDC) intends to provide a platform for free access to data created and used in the scope of the research work of national institutions. It is characterized by the availability of a repository platform ( DSpace ) and support for the entire data maintenance component, such as backups, monitoring, updating, security, etc., thus keeping researchers out of the concern of these tasks. Finally, the SARDC service intends to make the data deposited in the repository available through the RCAAP Portal.
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Thai National Research Repository (TNRR) is a central database of science, research, and innovation of Thailand managed by the National Research Council of Thailand (NRCT) under the Ministry of Higher Education, Science, Research and Innovation (MHESI) Act B.E. 2562 (2019). The TNRR system serves and disseminates an extensive collection of information to the public as open access to research and innovation knowledge. The goal is to be the system that provides information services on Thailand's research findings. This information is collected from academic institutes and information-oriented government agencies in Thailand. In other words, the data in the TNRR system is accumulated from 3 national databases including 1. National Research Innovation and Information System (NRIIS), 2. Research agencies within Thailand’s research and innovation ecosystem that have agreed to share their data; including research projects, research results, bodies of knowledge, theses, as well as various inventions and innovations; and 3. Other related databases of agencies that have shared their data for audit purposes and to improve the operation of the central database, such as the Department of Provincial Administration, the Department of Intellectual Property, and the Department of Business Development, etc. Thai National Research Repository (TNRR) also provides open data of research findings via API which can be accessed at https://tnrr.nriis.go.th/#/service/opendata and https://opendata.nrct.go.th/en/
The WDC is concerned with the collection, management, distribution and utilization of data from Chinese provinces, autonomous regions and counties,including: Resource data:management,distribution and utlilzation of land, water, climate, forest, grassland, minerals, energy, etc. Environmental data:pollution,environmental quality, change, natural disasters,soli erosion, etc. Biological resources:animals, plants,wildlife Social economy:agriculture, industry, transport, commerce,infrastructure,etc. Population and labor Geographic background data on scales of 1:4M,1:1M, 1:(1/2)M, 1:2500, etc.