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Found 12 result(s)
The Metropolitan Travel Survey Archive (MTSA) includes travel surveys from numerous public agencies across the United States. The Transportation Secure Data Center has archived these surveys to ensure their continued public availability. The survey data have been converted to a standard file format and cleansed to remove personally identifiable information, including any detailed spatial data regarding individual trips.
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 African Development Bank Group (AfDB) is committed to supporting statistical development in Africa as a sound basis for designing and managing effective development policies for reducing poverty on the continent. Reliable and timely data is critical to setting goals and targets as well as evaluating project impact. Reliable data constitutes the single most convincing way of getting the people involved in what their leaders and institutions are doing. It also helps them to get involved in the development process, thus giving them a sense of ownership of the entire development process. The AfDB has a large team of researchers who focus on the production of statistical data on economic and social situations. The data produced by the institution’s statistics department constitutes the background information in the Bank’s flagship development publications. Besides its own publication, the AfDB also finances studies in collaboration with its partners. The Statistics Department aims to stand as the primary source of relevant, reliable and timely data on African development processes, starting with the data generated from its current management of the Africa component of the International Comparison Program (ICP-Africa). The Department discharges its responsibilities through two divisions: The Economic and Social Statistics Division (ESTA1); The Statistical Capacity Building Division (ESTA2)
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Arachne is the central object-database of the German Archaeological Institute (DAI). In 2004 the DAI and the Research Archive for Ancient Sculpture at the University of Cologne (FA) joined the effort to support Arachne as a tool for free internet-based research. Arachne's database design uses a model that builds on one of the most basic assumptions one can make about archaeology, classical archaeology or art history: all activities in these areas can most generally be described as contextualizing objects. Arachne tries to avoid the basic mistakes of earlier databases, which limited their object modeling to specific project-oriented aspects, thus creating separated containers of only a small number of objects. All objects inside Arachne share a general part of their object model, to which a more class-specific part is added that describes the specialised properties of a category of material like architecture or topography. Seen on the level of the general part, a powerful pool of material can be used for general information retrieval, whereas on the level of categories and properties, very specific structures can be displayed.
ScholarSphere is an institutional repository managed by Penn State University Libraries. Anyone with a Penn State Access ID can deposit materials relating to the University’s teaching, learning, and research mission to ScholarSphere. All types of scholarly materials, including publications, instructional materials, creative works, and research data are accepted. ScholarSphere supports Penn State’s commitment to open access and open science. Researchers at Penn State can use ScholarSphere to satisfy open access and data availability requirements from funding agencies and publishers.
Knoema is a knowledge platform. The basic idea is to connect data with analytical and presentation tools. As a result, we end with one uniformed platform for users to access, present and share data-driven content. Within Knoema, we capture most aspects of a typical data use cycle: accessing data from multiple sources, bringing relevant indicators into a common space, visualizing figures, applying analytical functions, creating a set of dashboards, and presenting the outcome.
DIAMM (the Digital Image Archive of Medieval Music) is a leading resource for the study of medieval manuscripts. We present images and metadata for thousands of manuscripts on this website. We also provide a home for scholarly resources and editions, undertake digital restoration of damaged manuscripts and documents, publish high-quality facsimiles, and offer our expertise as consultants.
OpenML is an open ecosystem for machine learning. By organizing all resources and results online, research becomes more efficient, useful and fun. OpenML is a platform to share detailed experimental results with the community at large and organize them for future reuse. Moreover, it will be directly integrated in today’s most popular data mining tools (for now: R, KNIME, RapidMiner and WEKA). Such an easy and free exchange of experiments has tremendous potential to speed up machine learning research, to engender larger, more detailed studies and to offer accurate advice to practitioners. Finally, it will also be a valuable resource for education in machine learning and data mining.
Data.gov increases the ability of the public to easily find, download, and use datasets that are generated and held by the Federal Government. Data.gov provides descriptions of the Federal datasets (metadata), information about how to access the datasets, and tools that leverage government datasets