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Found 11 result(s)

Global Trade Analysis Project

The GTAP Data Base

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The centerpiece of the Global Trade Analysis Project is a global data base describing bilateral trade patterns, production, consumption and intermediate use of commodities and services. The GTAP Data Base consists of bilateral trade, transport, and protection matrices that link individual country/regional economic data bases. The regional data bases are derived from individual country input-output tables, from varying years.

META-SHARE

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META-SHARE, the open language resource exchange facility, is devoted to the sustainable sharing and dissemination of language resources (LRs) and aims at increasing access to such resources in a global scale. META-SHARE is an open, integrated, secure and interoperable sharing and exchange facility for LRs (datasets and tools) for the Human Language Technologies domain and other applicative domains where language plays a critical role. META-SHARE is implemented in the framework of the META-NET Network of Excellence. It is designed as a network of distributed repositories of LRs, including language data and basic language processing tools (e.g., morphological analysers, PoS taggers, speech recognisers, etc.). Data and tools can be both open and with restricted access rights, free and for-a-fee.

WorldData.AI

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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.

DSpace@MIT

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DSpace@MIT is a service of the MIT Libraries to provide MIT faculty, researchers and their supporting communities stable, long-term storage for their digital research and teaching output and to maximize exposure of their content to a world audience. DSpace@MIT content includes conference papers, images, peer-reviewed scholarly articles, preprints, technical reports, theses, working papers, research datasets and more. This collection of more than 60,000 high-quality works is recognized as among the world's premier scholarly repositories and receives, on average, more than 1 million downloads per month.

Wolfram Data Repository

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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.

Linguistic Data Consortium

LDC

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The Linguistic Data Consortium (LDC) is an open consortium of universities, libraries, corporations and government research laboratories. It was formed in 1992 to address the critical data shortage then facing language technology research and development. Initially, LDC's primary role was as a repository and distribution point for language resources. Since that time, and with the help of its members, LDC has grown into an organization that creates and distributes a wide array of language resources. LDC also supports sponsored research programs and language-based technology evaluations by providing resources and contributing organizational expertise. LDC is hosted by the University of Pennsylvania and is a center within the University’s School of Arts and Sciences.

Banco de Información para la Investigación Aplicada en Ciencias Sociales, Repositorio Institucional

BIIACS

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<<<!!!<<< This repository is no longer available. >>>!!!>>>

Arca Dados

Arca Data

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Arca Data is Fiocruz's official repository for archiving, publishing, disseminating, preserving and sharing digital research data produced by the Fiocruz community or in partnership with other research institutes or bodies, with the aim of promoting new research, ensuring the reproducibility or replicability of existing research and promoting an Open and Citizen Science. Its objective is to stimulate the wide circulation of scientific knowledge, strengthening the institutional commitment to Open Science and free access to health information, in addition to providing transparency and fostering collaboration between researchers, educators, academics, managers and graduate students, to the advancement of knowledge and the creation of solutions that meet the demands of society.

Europeana collections

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Europeana is the trusted source of cultural heritage brought to you by the Europeana Foundation and a large number of European cultural institutions, projects and partners. It’s a real piece of team work. Ideas and inspiration can be found within the millions of items on Europeana. These objects include: Images - paintings, drawings, maps, photos and pictures of museum objects Texts - books, newspapers, letters, diaries and archival papers Sounds - music and spoken word from cylinders, tapes, discs and radio broadcasts Videos - films, newsreels and TV broadcasts All texts are CC BY-SA, images and media licensed individually.

Code Ocean

CO

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Code Ocean is a cloud-based computational reproducibility platform that provides researchers an easy way to share, discover and run code published in academic journals and conferences.

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.