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Found 13 result(s)
DARECLIMED data repository consists of three kind of data: (a) climate, (b) water resources, and (c) energy related data. The first part, climate datasets, will include atmospheric and indirect atmospheric data, proxies and reconstructions, terrestrial and oceanic data. Land use, population, economy and development data will be added as well. Datasets can be handled and analyzed by connecting to the Live Access Server (LAS), which enables to visualize data with on-the-fly graphics, request custom subsets of variables in a choice of file formats, access background reference material about the data (metadata), and compare (difference) variables from distributed locations. Access to server is granted upon request by emailing the data repository manager.
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The collection contains stature-related and other anthropometric data of 7686 skeletal individuals (including aggregated information for several individuals) from the prehistory of Southwest Asia and Europe. While the focus period of our collection is the Holocene ca. 10 000 to 1000 BC, the data collection also includes older specimens of anatomically modern humans (dating as early as 110 k BP in the case of Qafzeh). The upper date range in some cases extends to around 100 AD, although the great majority of datasets date no later than 600 BC. Correctness and completeness were pursued for all information relevant to stature, i.e. basic information such as sex (after Sjøvold 1988) and age (after Szilvássy 1988) as well as the long bone measurements, whereas other measurements were merely inherited from the two integrated older data bases and not explicitly checked. All measurements conform to the definitions given by Martin 1928. To grasp common publication practice in the literature, not only left and right body side, but also mean values from both sides as well as measurements with unknown siding have their own separate fields for the stature-related long bone measurements.
IoT Lab is a research platform exploring the potential of crowdsourcing and Internet of Things for multidisciplinary research with more end-user interactions. IoT Lab is a European Research project which aims at researching the potential of crowdsourcing to extend IoT testbed infrastructure for multidisciplinary experiments with more end-user interactions. It addresses topics such as: - Crowdsourcing mechanisms and tools; - “Crowdsourcing-driven research”; - Virtualization of crowdsourcing and testbeds; - Ubiquitous Interconnection and Cloudification of testbeds; - Testbed as a Service platform; - Multidisciplinary experiments; - End-user and societal value creation; - Privacy and personal data protection.
Explore, search, and download data and metadata from your experiments and from public Open Data. The ESRF data repository is intended to store and archive data from photon science experiments done at the ESRF and to store digital material like documents and scientific results which need a DOI and long term preservation. Data are made public after an embargo period of maximum 3 years.
This unique resource covers the entire field of astronomy and astrophysics and this online version includes the full text of over 2,750 articles, plus sophisticated search and retrieval functionality, links to the primary literature, and is frequently updated with new material. An active editorial team, headed by the Encyclopedia's editor-in-chief, Paul Murdin, oversees the continual commissioning, reviewing and loading of new and revised content.In a unique collaboration, Nature Publishing Group and Institute of Physics Publishing published the most extensive and comprehensive reference work in astronomy and astrophysics in both print and online formats. First published as a four volume print edition in 2001, the initial Web version went live in 2002, and contained the original print material and was rapidly supplemented with numerous updates and newly commissioned material. Since July 2006 the Encyclopedia is published solely by Taylor & Francis.
Coronavirus COVID-19 Global Cases by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). Johns Hopkins experts in global public health, infectious disease, and emergency preparedness have been at the forefront of the international response to COVID-19. This website is a resource to help advance the understanding of the virus, inform the public, and brief policymakers in order to guide a response, improve care, and save lives. All data collected and displayed are made freely available through a GitHub repository https://github.com/CSSEGISandData/COVID-19, along with the feature layers of the dashboard, which are now included in the ESRI Living Atlas: https://livingatlas.arcgis.com/en/
>>>!!!<<< As stated 2017-05-16 The BIRN project was finished a few years ago. The web portal is no longer live.>>>!!!<<< BIRN is a national initiative to advance biomedical research through data sharing and online collaboration. It supports multi-site, and/or multi-institutional, teams by enabling researchers to share significant quantities of data across geographic distance and/or incompatible computing systems. BIRN offers a library of data-sharing software tools specific to biomedical research, best practice references, expert advice and other resources.
The IMSR is a searchable online database of mouse strains, stocks, and mutant ES cell lines available worldwide, including inbred, mutant, and genetically engineered strains. The goal of the IMSR is to assist the international scientific community in locating and obtaining mouse resources for research. Note that the data content found in the IMSR is as supplied by strain repository holders. For each strain or cell line listed in the IMSR, users can obtain information about: Where that resource is available (Repository Site); What state(s) the resource is available as (e.g. live, cryopreserved embryo or germplasm, ES cells); Links to descriptive information about a strain or ES cell line; Links to mutant alleles carried by a strain or ES cell line; Links for ordering a strain or ES cell line from a Repository; Links for contacting the Repository to send a query
The Durham High Energy Physics Database (HEPData), formerly: the Durham HEPData Project, has been built up over the past four decades as a unique open-access repository for scattering data from experimental particle physics. It currently comprises the data points from plots and tables related to several thousand publications including those from the Large Hadron Collider (LHC). The Durham HepData Project has for more than 25 years compiled the Reactions Database containing what can be loosly described as cross sections from HEP scattering experiments. The data comprise total and differential cross sections, structure functions, fragmentation functions, distributions of jet measures, polarisations, etc... from a wide range of interactions. In the new HEPData site (hepdata.net), you can explore new functionalities for data providers and data consumers, as well as the submission interface. HEPData is operated by CERN and IPPP at Durham University and is based on the digital library framework Invenio.
The CCHDO's primary mission is to deliver the highest possible quality global CTD and hydrographic data to users. These data are a product of decades of observations related to the physical characteristics of ocean waters carried out during GO-SHIP, WOCE, CLIVAR and numerous other oceanographic research programs. Whenever possible we provide these data in three easy-to-use formats: WHP-Exchange (which we recommend for data submissions to the CCHDO), WOCE, and netCDF. The CCHDO also manages public and non-public CTD data to be used for the global Argo and OceanSITES programs.
Galaxies, made up of billions of stars like our Sun, are the beacons that light up the structure of even the most distant regions in space. Not all galaxies are alike, however. They come in very different shapes and have very different properties; they may be large or small, old or young, red or blue, regular or confused, luminous or faint, dusty or gas-poor, rotating or static, round or disky, and they live either in splendid isolation or in clusters. In other words, the universe contains a very colourful and diverse zoo of galaxies. For almost a century, astronomers have been discussing how galaxies should be classified and how they relate to each other in an attempt to attack the big question of how galaxies form. Galaxy Zoo (Lintott et al. 2008, 2011) pioneered a novel method for performing large-scale visual classifications of survey datasets. This webpage allows anyone to download the resulting GZ classifications of galaxies in the project.
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>>>!!!<<<VENUS coastal network, is now part of the Ocean Networks Canada Observatory>>>!!!<<< VENUS is a cabled undersea laboratory for ocean researchers and explorers. VENUS delivers real time information from seafloor instruments via fibre optic cables to the University of Victoria, BC. You can see ocean data live, recent and archived as well as learn more about on-going research