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Found 9 result(s)

Controlled Fusion Atomic Data Center

CFADC

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<<<!!!<<< 2018-12-31: no more access to Controlled Fusion Atomic Data Center>>>!!!>>>

Continental Scientific Drilling Facility

formerly: NSF Facilities for Continental Scientific & Drilling & Coring

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US National Science Foundation (NSF) facility to support drilling and coring in continental locations worldwide. Drill core metadata and data, borehole survey data, geophysical site survey data, drilling metadata, software code. The CSD Facility offers repositories with samples, data, publications and reference collections from scientific drilling and coring.

Sloan Digital Sky Survey

SDSS

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The Sloan Digital Sky Survey (SDSS) is one of the most ambitious and influential surveys in the history of astronomy. Over eight years of operations (SDSS-I, 2000-2005; SDSS-II, 2005-2008; SDSS-III 2008-2014; SDSS-IV 2013 ongoing), it obtained deep, multi-color images covering more than a quarter of the sky and created 3-dimensional maps containing more than 930,000 galaxies and more than 120,000 quasars. DSS-IV is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration including the Carnegie Institution for Science, Carnegie Mellon University, the Chilean Participation Group, Harvard-Smithsonian Center for Astrophysics, Instituto de Astrofísica de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU) / University of Tokyo, Lawrence Berkeley National Laboratory, Leibniz Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astrophysik (MPA Garching), Max-Planck-Institut für Extraterrestrische Physik (MPE), Max-Planck-Institut für Astronomie (MPIA Heidelberg), National Astronomical Observatory of China, New Mexico State University, New York University, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Portsmouth, University of Utah, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University.

HDAP

Heidelberg Digitized Astronomical Plates

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Scans of plates obtained at Landessternwarte Heidelberg-Königstuhl and German-Spanish Astronomical Center (Calar Alto Observatory), Spain, 1900 through 1999.

BioModels

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BioModels is a repository of mathematical models of biological and biomedical systems. It hosts a vast selection of existing literature-based physiologically and pharmaceutically relevant mechanistic models in standard formats. Our mission is to provide the systems modelling community with reproducible, high-quality, freely-accessible models published in the scientific literature.

ECHO – Cultural Heritage Online

Open Access Infrastructure for a Future Web of Culture and Science

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The ECHO initiative aims to create an infrastructure to bring cultural heritage on the Internet, and builds up a network of institutions, research projects and other users which provide content and technology for the common infrastructure, with the aim to enrich the "agora" and to create a future Web of Culture and Science.

VecNet

Vector-Borne Disease Network

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<<<!!!<<< The repository is no longer available. 2019-09-06: no more access to VecNet >>>!!!>>>

Registry of Open Data on AWS

Registry of Open Data on Amazon Web Services

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The Registry of Open Data on AWS provides a centralized repository of public data sets that can be seamlessly integrated into AWS cloud-based applications. AWS is hosting the public data sets at no charge to their users. Anyone can access these data sets from their Amazon Elastic Compute Cloud (Amazon EC2) instances and start computing on the data within minutes. Users can also leverage the entire AWS ecosystem and easily collaborate with other AWS users.

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.