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Found 47 result(s)
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The World Atlas of Language Structures (WALS) is a large database of structural (phonological, grammatical, lexical) properties of languages gathered from descriptive materials (such as reference grammars) by a team of 55 authors (many of them the leading authorities on the subject).
The World Ocean Database (WOD) is a collection of scientifically quality-controlled ocean profile and plankton data that includes measurements of temperature, salinity, oxygen, phosphate, nitrate, silicate, chlorophyll, alkalinity, pH, pCO2, TCO2, Tritium, Δ13Carbon, Δ14Carbon, Δ18Oxygen, Freon, Helium, Δ3Helium, Neon, and plankton. WOD contains all data of "World Data Service Oceanography" (WDS-Oceanography).
The RIT DML captures, distributes and preserves RIT's digital products. Here you can find articles, working papers, preprints, technical reports, conference papers and data sets in various digital formats.
The Mikulski Archive for Space Telescopes (MAST) is a NASA funded project to support and provide to the astronomical community a variety of astronomical data archives, with the primary focus on scientifically related data sets in the optical, ultraviolet, and near-infrared parts of the spectrum. MAST is located at the Space Telescope Science Institute (STScI).
The EUDAT project aims to contribute to the production of a Collaborative Data Infrastructure (CDI). The project´s target is to provide a pan-European solution to the challenge of data proliferation in Europe's scientific and research communities. The EUDAT vision is to support a Collaborative Data Infrastructure which will allow researchers to share data within and between communities and enable them to carry out their research effectively. EUDAT aims to provide a solution that will be affordable, trustworthy, robust, persistent and easy to use. EUDAT comprises 26 European partners, including data centres, technology providers, research communities and funding agencies from 13 countries. B2FIND is the EUDAT metadata service allowing users to discover what kind of data is stored through the B2SAFE and B2SHARE services which collect a large number of datasets from various disciplines. EUDAT will also harvest metadata from communities that have stable metadata providers to create a comprehensive joint catalogue to help researchers find interesting data objects and collections.
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jPOSTrepo (Japan ProteOme STandard Repository) is a repository of sharing MS raw/processed data. It consists of a high-speed file upload process, flexible file management system and easy-to-use interfaces. Users can release their "raw/processed" data via this site with a unique identifier number for the paper publication. Users also can suspend (or "embargo") their data until their paper is published. The file transfer from users’ computer to our repository server is very fast (roughly ten times faster than usual file transfer) and uses only web browsers – it does not require installing any additional software.
The WashU Research Data repository accepts any publishable research data set, including textual, tabular, geospatial, imagery, computer code, or 3D data files, from researchers affiliated with Washington University in St. Louis. Datasets include metadata and are curated and assigned a DOI to align with FAIR data principles.
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DataverseNO (https://dataverse.no) is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.
The Southern California Earthquake Data Center (SCEDC) operates at the Seismological Laboratory at Caltech and is the primary archive of seismological data for southern California. The 1932-to-present Caltech/USGS catalog maintained by the SCEDC is the most complete archive of seismic data for any region in the United States. Our mission is to maintain an easily accessible, well-organized, high-quality, searchable archive for research in seismology and earthquake engineering.
Neuroimaging Tools and Resources Collaboratory (NITRC) is currently a free one-stop-shop environment for science researchers that need resources such as neuroimaging analysis software, publicly available data sets, and computing power. Since its debut in 2007, NITRC has helped the neuroscience community to use software and data produced from research that, before NITRC, was routinely lost or disregarded, to make further discoveries. NITRC provides free access to data and enables pay-per-use cloud-based access to unlimited computing power, enabling worldwide scientific collaboration with minimal startup and cost. With NITRC and its components—the Resources Registry (NITRC-R), Image Repository (NITRC-IR), and Computational Environment (NITRC-CE)—a researcher can obtain pilot or proof-of-concept data to validate a hypothesis for a few dollars.
The EUR Data Repository [EDR] is the institutional data repository from the Erasmus University Rotterdam. The EUR Data Repository is an online platform where you showcase your research and make it findable, citable, and reusable for others.
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Kinsources is an open and interactive platform to archive, share, analyze and compare kinship data used in scientific research. Kinsources is not just another genealogy website, but a peer-reviewed repository designed for comparative and collaborative research. The aim of Kinsources is to provide kinship studies with a large and solid empirical base. Kinsources combines the functionality of communal data repository with a toolbox providing researchers with advanced software for analyzing kinship data. The software Puck (Program for the Use and Computation of Kinship data) is integrated in the statistical package and the search engine of the Kinsources website. Kinsources is part of a research perspective that seeks to understand the interaction between genealogy, terminology and space in the emergence of kinship structures. Hosted by the TGIR HumaNum, the platform ensures both security and free access to the scientific data is validated by the research community.
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The GAVO data centre at Zentrum für Astronomie Heidelberg publishes astronomical data of all kinds – e.g., catalogues, images, spectra, time series, simulation results – in accordance with Virtual Observatory standards, making them findable and immediately usable through popular clients like TOPCAT, Aladin, or programatically through the astropy-affiliated package pyVO or the Java library STIL. We pay particular attention to providing thorough metadata to the VO Registry in order to facilitate discovery and reuse. While we have a clear focus on data produced with German contributions, we will usually publish data of other provenance, too. See https://docs.g-vo.org/DaCHS/data_checklist.html for an overview of what resource-level metadata we ask for; contact us for further information on how to publish through the German Astronomical Virtual Observatory.
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SILVA is a comprehensive, quality-controlled web resource for up-to-date aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains alongside supplementary online services. In addition to data products, SILVA provides various online tools such as alignment and classification, phylogenetic tree calculation and viewer, probe/primer matching, and an amplicon analysis pipeline. With every full release a curated guide tree is provided that contains the latest taxonomy and nomenclature based on multiple references. SILVA is an ELIXIR Core Data Resource.
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Research Data Unipd is a data archive and supports research produced by the members of the University of Padova. The service aims to facilitate data discovery, data sharing, and reuse, as required by funding institutions (eg. European Commission). Datasets published in the archive have a set of metadata that ensure proper description and discoverability.
IEEE DataPort™ is a universally accessible online data repository created, owned, and supported by IEEE, the world’s largest technical professional organization. It enables all researchers and data owners to upload their dataset without cost. IEEE DataPort makes data available in three ways: standard datasets, open access datasets, and data competition datasets. By default, all "standard" datasets that are uploaded are accessible to paid IEEE DataPort subscribers. Data owners have an option to pay a fee to make their dataset “open access”, so it is available to all IEEE DataPort users (no subscription required). The third option is to host a "data competition" and make a dataset accessible for free for a specific duration with instructions for the data competition and how to participate. IEEE DataPort provides workflows for uploading data, searching, and accessing data, and initiating or participating in data competitions. All datasets are stored on Amazon AWS S3, and each dataset uploaded by an individual can be up to 2TB in size. Institutional subscriptions are available to the platform to make it easy for all members of a given institution to utilize the platform and upload datasets.
OpenWorm aims to build the first comprehensive computational model of the Caenorhabditis elegans (C. elegans), a microscopic roundworm. With only a thousand cells, it solves basic problems such as feeding, mate-finding and predator avoidance. Despite being extremely well studied in biology, this organism still eludes a deep, principled understanding of its biology. We are using a bottom-up approach, aimed at observing the worm behaviour emerge from a simulation of data derived from scientific experiments carried out over the past decade. To do so we are incorporating the data available in the scientific community into software models. We are engineering Geppetto and Sibernetic, open-source simulation platforms, to be able to run these different models in concert. We are also forging new collaborations with universities and research institutes to collect data that fill in the gaps All the code we produce in the OpenWorm project is Open Source and available on GitHub.
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.
<<<!!!<<< This repository is no longer available. >>>!!!>>> BioVeL is a virtual e-laboratory that supports research on biodiversity issues using large amounts of data from cross-disciplinary sources. BioVeL supports the development and use of workflows to process data. It offers the possibility to either use already made workflows or create own. BioVeL workflows are stored in MyExperiment - Biovel Group http://www.myexperiment.org/groups/643/content. They are underpinned by a range of analytical and data processing functions (generally provided as Web Services or R scripts) to support common biodiversity analysis tasks. You can find the Web Services catalogued in the BiodiversityCatalogue.
The Natural Environment Research Council's Data Repository for Atmospheric Science and Earth Observation. The Centre for Environmental Data Analysis (CEDA) serves the environmental science community through three data centres, data analysis environments, and participation in a host of relevant research projects. We aim to support environmental science, further environmental data archival practices, and develop and deploy new technologies to enhance access to data. Additionally we provide services to aid large scale data analysis.