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Found 8 result(s)

Metropolitan Travel Survey Archive

MTSA

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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.

INDEPTH Data Repository

International Network for the Demographic Evaluation of Populations and Their Health Data Repository

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INDEPTH is a global network of research centres that conduct longitudinal health and demographic evaluation of populations in low- and middle-income countries (LMICs). INDEPTH aims to strengthen global capacity for Health and Demographic Surveillance Systems (HDSSs), and to mount multi-site research to guide health priorities and policies in LMICs, based on up-to-date scientific evidence. The data collected by the INDEPTH Network members constitute a valuable resource of population and health data for LMIC countries. This repository aims to make well documented anonymised longitudinal microdata from these Centres available to data users.

Migration data portal

IOM's Global Migration Data Portal

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The Portal aims to serve as a unique access point to timely, comprehensive migration statistics and reliable information about migration data globally. The site is designed to help policy makers, national statistics officers, journalists and the general public interested in the field of migration to navigate the increasingly complex landscape of international migration data, currently scattered across different organisations and agencies. Especially in critical times, such as those faced today, it is essential to ensure that responses to migration are based on sound facts and accurate analysis. By making the evidence about migration issues accessible and easy to understand, the Portal aims to contribute to a more informed public debate. The Portal was launched in December 2017 and is managed and developed by IOM’s Global Migration Data Analysis Centre (GMDAC), with the guidance of its Advisory Board, and was supported in its conception by the Economist Intelligence Unit (EIU). The Portal is supported financially by the Governments of Germany, the United States of America and the UK Department for International Development (DFID).

City of Victoria Open Data Portal

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The City of Victoria’s Open Data Portal allows you to explore and download open data, discover and analyze datasets using maps, and develop new web and mobile applications.

BAOBAB

Base Afrique de l'Ouest Beyond AMMA Base

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The projects include airborne, ground-based and ocean measurements, social science surveys, satellite data use, modelling studies and value-added product development. Therefore, the BAOBAB data portal enables to access a great amount and a large variety of data: - 250 local observation datasets, that have been collected by operational networks since 1850, long term monitoring research networks and intensive scientific campaigns; - 1350 outputs of a socio-economics questionnaire; - 60 operational satellite products and several research products; - 10 output sets of meteorological and ocean operational models and 15 of research simulations. Data documentation complies with metadata international standards, and data are delivered into standard formats. The data request interface takes full advantage of the database relational structure and enables users to elaborate multicriteria requests (period, area, property…).

AfDB Statistical Data Portal

formerly: Open data for Africa

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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)

Knoema

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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.

OpenML

Open Machine Learning

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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.