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Found 27 result(s)
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Risklayer Explorer is a collaboration between Risklayer GmbH and the Karlsruhe Institute of Technology's Center for Disaster Risk Management and Risk Reduction Technology (CEDIM). This website is still under development, but we are going live with it already, because we want to present data on the Novel Coronavirus (COVID-19) to help inform the public of the current situation. You will be able to track disaster events and read about our analysis here. Our work is a continuation of a new style of disaster research started by CEDIM in 2011 to analyze disasters immediately after their occurrence, assess the impacts, and retrace the temporal development of disaster events. We are already analyzing damaging earthquakes globally, providing you with event characteristics, earthquake's intensity footprints, as well as the population affected by earthquakes. In addition to earthquake events, we expect to be tracking and analyzing tropical cyclone, volcano and extreme weather events in 2020.
WorldData.AI comes with a built-in workspace – the next-generation hyper-computing platform powered by a library of 3.3 billion curated external trends. WorldData.AI allows you to save your models in its “My Models Trained” section. You can make your models public and share them on social media with interesting images, model features, summary statistics, and feature comparisons. Empower others to leverage your models. For example, if you have discovered a previously unknown impact of interest rates on new-housing demand, you may want to share it through “My Models Trained.” Upload your data and combine it with external trends to build, train, and deploy predictive models with one click! WorldData.AI inspects your raw data, applies feature processors, chooses the best set of algorithms, trains and tunes multiple models, and then ranks model performance.
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The German Socio-Economic Panel Study (SOEP) is a wide-ranging representative longitudinal study of private households, located at the German Institute for Economic Research, DIW Berlin. Every year, there were nearly 11,000 households, and more than 20,000 persons sampled by the fieldwork organization TNS Infratest Sozialforschung. The data provide information on all household members, consisting of Germans living in the Old and New German States, Foreigners, and recent Immigrants to Germany. The Panel was started in 1984. Some of the many topics include household composition, occupational biographies, employment, earnings, health and satisfaction indicators.
The Wolfram Data Repository is a public resource that hosts an expanding collection of computable datasets, curated and structured to be suitable for immediate use in computation, visualization, analysis and more. Building on the Wolfram Data Framework and the Wolfram Language, the Wolfram Data Repository provides a uniform system for storing data and making it immediately computable and useful. With datasets of many types and from many sources, the Wolfram Data Repository is built to be a global resource for public data and data-backed publication.
Government of Yukon open data provides an easy way to find, access and reuse the government's public datasets. This service brings all of the government's data together in one searchable website. Our datasets are created and managed by different government departments. We cannot guarantee the quality or timeliness of all data. If you have any feedback you can get in touch with the department that produced the dataset. This is a pilot project. We are in the process of adding a quality framework to make it easier for you to access high quality, reliable data.
Teesside University Research Data Repository links to the University's Research Portal and enables your datasets to be linked to your staff profile. It helps prevent data loss by storing it in a safe secure environment and enables your research data to be open access. https://researchdata.tees.ac.uk/about.
Kaggle is a platform for predictive modelling and analytics competitions in which statisticians and data miners compete to produce the best models for predicting and describing the datasets uploaded by companies and users. This crowdsourcing approach relies on the fact that there are countless strategies that can be applied to any predictive modelling task and it is impossible to know beforehand which technique or analyst will be most effective.
Science Photo Library (SPL) provides creative professionals with striking specialist imagery, unrivalled in quality, accuracy and depth of information. We have more than 600,000 images and 40,000 clips to choose from, with hundreds of new submissions uploaded to the website each week.
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DBIE is a data warehouse of the Department of Statistics and Information Management (DSIM), under the Reserve Bank of India. It disseminates data on various aspects of the Indian Economy through several of its publications, by means of it’s three parts – namely has mainly three parts Home, Statistics and Time-series Publications. Again, Home is divided into two parts viz. Important Economic Indicators & Economy at a Glance through dashboards. The entire statistics have been presented in seven subject areas - Real Sector, Corporate Sector, Financial Sector, Financial Market, External Sector, Public Finance, Socio-Economic Indicators. Sectors have different sub-sectors and reports under the sub-sectors have been organized on periodicity wise. Downloading of data can be possible into Excel, CSV, PDF formats. User can use the data for their research work with courtesy to the Database on Indian Economy, Reserve Bank of India.
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The Institutional Repository of the Universidad Santo Tomás manages, preserves, stores, disseminates and provides access to digital objects, the product of all academic and administrative production.
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<<<!!!<<< The pages were merged. Please use "Forschungsdaten- und Servicezentrum der Bundesbank" https://www.re3data.org/repository/r3d100012252 >>>!!!<<<
As 3D and reality capture strategies for heritage documentation become more widespread and available, there has emerged a growing need to assist with guiding and facilitating accessibility to data, while maintaining scientific rigor, cultural and ethical sensitivity, discoverability, and archival standards. In response to these areas of need, The Open Heritage 3D Alliance (OHA) has developed as an advisory group governing the Open Heritage 3D initiative. This collaborative advisory group are among some of the earliest adopters of 3D heritage documentation technologies, and offer first-hand guidance for best practices in data management, sharing, and dissemination approaches for 3D cultural heritage projects. The founding members of the OHA, consist of experts and organizational leaders from CyArk, Historic Environment Scotland, and the University of South Florida Libraries, who together have significant repositories of legacy and on-going 3D research and documentation projects. These groups offer unique insight into not only the best practices for 3D data capture and sharing, but also have come together around concerns dealing with standards, formats, approach, ethics, and archive commitment. Together, the OHA has begun the journey to provide open access to cultural heritage 3D data, while maintaining integrity, security, and standards relating to discoverable dissemination. Together, the OHA will work to provide democratized access to primary heritage 3D data submitted from donors and organizations, and will help to facilitate an operation platform, archive, and organization of resources into the future.
Provided by the University Libraries, KiltHub is the comprehensive institutional repository and research collaboration platform for research data and scholarly outputs produced by members of Carnegie Mellon University and their collaborators. KiltHub collects, preserves, and provides stable, long-term global open access to a wide range of research data and scholarly outputs created by faculty, staff, and student members of Carnegie Mellon University in the course of their research and teaching.
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A databank on the economy, agriculture, tourism, infrastructure, industry, and natural resources of the North Eastern Region of India; comprises seven states namely Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, Tripura (popularly known as Seven Sisters of India). The region (holds 7.9% of the total land space of the country) is of strategic importance for the country on account of the fact that nearly 90% of its borders form India's international boundaries. Thus information about population distribution, migration of peoples, vast natural resources, literacy rate, infrastructure development, cultural diversity, economy, etc. of this region are quite different from rest of the country.NER databank intends to provide information on multifarious activities of North Eastern states of India, thereby make it accessible to social commons. The North East Databank is a web portal created to provide a regional resource database for the North Eastern Region (NER).
the Data Hub is a community-run catalogue of useful sets of data on the Internet. You can collect links here to data from around the web for yourself and others to use, or search for data that others have collected. Depending on the type of data (and its conditions of use), the Data Hub may also be able to store a copy of the data or host it in a database, and provide some basic visualisation tools.
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ResearchGate is a network where 15+ million scientists and researchers worldwide connect to share their work. Researchers can upload data of any type and receive DOIs, detailed statistics and real-time feedback. In Data discovery Section of ResearchGate you can explore the added datasets.
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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.
Provides free and open access to over 155 city datasets with new ones added regularly. Open data is anonymized (not personally identifiable), free, and available to everyone in one or more open and accessible formats.
The Association of Religion Data Archives (ARDA) strives to democratize access to the best data on religion. Founded as the American Religion Data Archive in 1997 and going online in 1998, the initial archive was targeted at researchers interested in American religion. The targeted audience and the data collection have both greatly expanded since 1998, now including American and international collections and developing features for educators, journalists, religious congregations, and researchers. Data included in the ARDA are submitted by the foremost religion scholars and research centers in the world.