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Found 25 result(s)
The Arizona State University (ASU) Research Data Repository provides a platform for ASU-affiliated researchers to share, preserve, cite, and make research data accessible and discoverable. The ASU Research Data Repository provides a permanent digital identifier for research data, which complies with data sharing policies. The repository is powered by the Dataverse open-source application, developed and used by Harvard University. Both the ASU Research Data Repository and the KEEP Institutional Repository are managed by the ASU Library to ensure research produced at Arizona State University is discoverable and accessible to the global community.
<<<!!!<<< CRAWDAD has moved to IEEE-Dataport https://www.re3data.org/repository/r3d100012569 The datasets in the Community Resource for Archiving Wireless Data at Dartmouth (CRAWDAD) repository are now hosted as the CRAWDAD Collection on IEEE Dataport. After nearly two decades as a stand-alone archive at crawdad.org, the migration of the collection to IEEE DataPort provides permanence and new visibility. >>>!!!>>>
RAVE (RAdial Velocity Experiment) is a multi-fiber spectroscopic astronomical survey of stars in the Milky Way using the 1.2-m UK Schmidt Telescope of the Anglo-Australian Observatory (AAO). The RAVE collaboration consists of researchers from over 20 institutions around the world and is coordinated by the Leibniz-Institut für Astrophysik Potsdam. As a southern hemisphere survey covering 20,000 square degrees of the sky, RAVE's primary aim is to derive the radial velocity of stars from the observed spectra. Additional information is also derived such as effective temperature, surface gravity, metallicity, photometric parallax and elemental abundance data for the stars. The survey represents a giant leap forward in our understanding of our own Milky Way galaxy; with RAVE's vast stellar kinematic database the structure, formation and evolution of our Galaxy can be studied.
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PARADISEC (the Pacific And Regional Archive for Digital Sources in Endangered Cultures) offers a facility for digital conservation and access to endangered materials from all over the world. Our research group has developed models to ensure that the archive can provide access to interested communities, and conforms with emerging international standards for digital archiving. We have established a framework for accessioning, cataloguing and digitising audio, text and visual material, and preserving digital copies. The primary focus of this initial stage is safe preservation of material that would otherwise be lost, especially field tapes from the 1950s and 1960s.
The Keck Observatory Archive (KOA)is a collaboration between the NASA Exoplanet Science Institute (NExScI) and the W. M. Keck Observatory (WMKO). This collaboration is founded by the NASA. KOA has been archiving data from the High Resolution Echelle Spectrograph (HIRES) since August 2004 and data acquired with the Near InfraRed echelle SPECtrograph (NIRSPEC) since May 2010. The archived data extend back to 1994 for HIRES and 1999 for NIRSPEC. The W. M. Keck Observatory Archive (KOA) ingests and curates data from the following instruments: DEIMOS, ESI, HIRES, KI, LRIS, MOSFIRE, NIRC2, and NIRSPEC.
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.
IBICT is providing a research data repository that takes care of long-term preservation and archiving of good practices, so that researchers can share, maintain control and get recognition for your data. The repository supports research data sharing with Quote persistent data, allowing them to be played. The Dataverse is a large open data repository of all disciplines, created by the Institute for Quantitative Social Science at Harvard University. IBICT the Dataverse repository provides a means available for free to deposit and find specific data sets stored by employees of the institutions participating in the Cariniana network.
The Language Bank features text and speech corpora with different kinds of annotations in over 60 languages. There is also a selection of tools for working with them, from linguistic analyzers to programming environments. Corpora are also available via web interfaces, and users can be allowed to download some of them. The IP holders can monitor the use of their resources and view user statistics.
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PUB represents the central publication data service of Bielefeld University. It serves Bielefeld academics to easily create and administer their personal publication lists and make them available on the web. The University Bielefeld encourages scientists to publish their research data on research data archives. The publications are intended to take account into personal and business related interests and carried out unter mandatory license conditions. The Bielefeld University supports faculties and scientific institutions to link their offerings with global data archives. The university-wide service " PUB - Publications at Bielefeld University " allows the primary publication of research data.
The Pennsieve platform is a cloud-based scientific data management platform focused on integrating complex datasets, fostering collaboration and publishing scientific data according to all FAIR principles of data sharing. The platform is developed to enable individual labs, consortiums, or inter-institutional projects to manage, share and curate data in a secure cloud-based environment and to integrate complex metadata associated with scientific files into a high-quality interconnected data ecosystem. The platform is used as the backend for a number of public repositories including the NIH SPARC Portal and Pennsieve Discover repositories. It supports flexible metadata schemas and a large number of scientific file-formats and modalities.
The KNB Data Repository is an international repository intended to facilitate ecological, environmental and earth science research in the broadest senses. For scientists, the KNB Data Repository is an efficient way to share, discover, access and interpret complex ecological, environmental, earth science, and sociological data and the software used to create and manage those data. Due to rich contextual information provided with data in the KNB, scientists are able to integrate and analyze data with less effort. The data originate from a highly-distributed set of field stations, laboratories, research sites, and individual researchers. The KNB supports rich, detailed metadata to promote data discovery as well as automated and manual integration of data into new projects. The KNB supports a rich set of modern repository services, including the ability to assign Digital Object Identifiers (DOIs) so data sets can be confidently referenced in any publication, the ability to track the versions of datasets as they evolve through time, and metadata to establish the provenance relationships between source and derived data.
The repository of the Hamburg Centre for Speech Corpora is used for archiving, maintenance, distribution and development of spoken language corpora. These usually consist of audio and / or video recordings, transcriptions and other data and structured metadata. The corpora treat the focus on multilingualism and are generally freely available for research and teaching. Most of the measures maintained by the HZSK corpora were created in the years 2000-2011 in the framework of the SFB 538 "Multilingualism" at the University of Hamburg. The HZSK however also strives to take linguistic data from other projects or contexts, and to provide also the scientific community for research and teaching are available, provided that they are compatible with the current focus of HZSK, ie especially spoken language and multilingualism.
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The data repository aims to store, preserve and make available research data generated by the academic community, in open access - as open as possible, as closed as necessary.
The Bavarian Archive for Speech Signals (BAS) is a public institution hosted by the University of Munich. This institution was founded with the aim of making corpora of current spoken German available to both the basic research and the speech technology communities via a maximally comprehensive digital speech-signal database. The speech material will be structured in a manner allowing flexible and precise access, with acoustic-phonetic and linguistic-phonetic evaluation forming an integral part of it.
The Open Science Framework (OSF) is part network of research materials, part version control system, and part collaboration software. The purpose of the software is to support the scientist's workflow and help increase the alignment between scientific values and scientific practices. Document and archive studies. Move the organization and management of study materials from the desktop into the cloud. Labs can organize, share, and archive study materials among team members. Web-based project management reduces the likelihood of losing study materials due to computer malfunction, changing personnel, or just forgetting where you put the damn thing. Share and find materials. With a click, make study materials public so that other researchers can find, use and cite them. Find materials by other researchers to avoid reinventing something that already exists. Detail individual contribution. Assign citable, contributor credit to any research material - tools, analysis scripts, methods, measures, data. Increase transparency. Make as much of the scientific workflow public as desired - as it is developed or after publication of reports. Find public projects here. Registration. Registering materials can certify what was done in advance of data analysis, or confirm the exact state of the project at important points of the lifecycle such as manuscript submission or at the onset of data collection. Discover public registrations here. Manage scientific workflow. A structured, flexible system can provide efficiency gain to workflow and clarity to project objectives, as pictured.
>>>!!!<<< caArray Retirement Announcement >>>!!!<<< The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) instance of the caArray database was retired on March 31st, 2015. All publicly-accessible caArray data and annotations will be archived and will remain available via FTP download https://wiki.nci.nih.gov/x/UYHeDQ and is also available at GEO http://www.ncbi.nlm.nih.gov/geo/ . >>>!!!<<< While NCI will not be able to provide technical support for the caArray software after the retirement, the source code is available on GitHub https://github.com/NCIP/caarray , and we encourage continued community development. Molecular Analysis of Brain Neoplasia (Rembrandt fine-00037) gene expression data has been loaded into ArrayExpress: http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-3073 >>>!!!<<< caArray is an open-source, web and programmatically accessible microarray data management system that supports the annotation of microarray data using MAGE-TAB and web-based forms. Data and annotations may be kept private to the owner, shared with user-defined collaboration groups, or made public. The NCI instance of caArray hosts many cancer-related public datasets available for download.
The project is set up in order to improve the infrastructure for text-based linguistic research and development by building a huge, automatically annotated German text corpus and the corresponding tools for corpus annotation and exploitation. DeReKo constitutes the largest linguistically motivated collection of contemporary German texts, contains fictional, scientific and newspaper texts, as well as several other text types, contains only licenced texts, is encoded with rich meta-textual information, is fully annotated morphosyntactically (three concurrent annotations), is continually expanded, with a focus on size and stratification of data, may be analyzed free of charge via the query system COSMAS II, serves as a 'primordial sample' from which users may draw specialized sub-samples (socalled 'virtual corpora') to represent the language domain they wish to investigate. !!! Access to data of Das Deutsche Referenzkorpus is also provided by: IDS Repository https://www.re3data.org/repository/r3d100010382 !!!
CLARIN.SI is the Slovenian node of the European CLARIN (Common Language Resources and Technology Infrastructure) Centers. The CLARIN.SI repository is hosted at the Jožef Stefan Institute and offers long-term preservation of deposited linguistic resources, along with their descriptive metadata. The integration of the repository with the CLARIN infrastructure gives the deposited resources wide exposure, so that they can be known, used and further developed beyond the lifetime of the projects in which they were produced. Among the resources currently available in the CLARIN.SI repository are the multilingual MULTEXT-East resources, the CC version of Slovenian reference corpus Gigafida, the morphological lexicon Sloleks, the IMP corpora and lexicons of historical Slovenian, as well as many other resources for a variety of languages. Furthermore, several REST-based web services are provided for different corpus-linguistic and NLP tasks.
The LINZ Data Service provides free online access to New Zealand’s most up-to-date land and seabed data. The data can be searched, browsed and downloaded. The LINZ web services can be also integrated into other applications.
GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over three million people use GitHub to build amazing things together. With the collaborative features of GitHub.com, our desktop and mobile apps, and GitHub Enterprise, it has never been easier for individuals and teams to write better code, faster. Originally founded by Tom Preston-Werner, Chris Wanstrath, and PJ Hyett to simplify sharing code, GitHub has grown into the largest code host in the world.
When published in 2005, the Millennium Run was the largest ever simulation of the formation of structure within the ΛCDM cosmology. It uses 10(10) particles to follow the dark matter distribution in a cubic region 500h(−1)Mpc on a side, and has a spatial resolution of 5h−1kpc. Application of simplified modelling techniques to the stored output of this calculation allows the formation and evolution of the ~10(7) galaxies more luminous than the Small Magellanic Cloud to be simulated for a variety of assumptions about the detailed physics involved. As part of the activities of the German Astrophysical Virtual Observatory we have created relational databases to store the detailed assembly histories both of all the haloes and subhaloes resolved by the simulation, and of all the galaxies that form within these structures for two independent models of the galaxy formation physics. We have implemented a Structured Query Language (SQL) server on these databases. This allows easy access to many properties of the galaxies and halos, as well as to the spatial and temporal relations between them. Information is output in table format compatible with standard Virtual Observatory tools. With this announcement (from 1/8/2006) we are making these structures fully accessible to all users. Interested scientists can learn SQL and test queries on a small, openly accessible version of the Millennium Run (with volume 1/512 that of the full simulation). They can then request accounts to run similar queries on the databases for the full simulations. In 2008 and 2012 the simulations were repeated.
GNPS is a web-based mass spectrometry ecosystem that aims to be an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. GNPS aids in identification and discovery throughout the entire life cycle of data; from initial data acquisition/analysis to post publication.
Launched in December 2013, Gaia is destined to create the most accurate map yet of the Milky Way. By making accurate measurements of the positions and motions of stars in the Milky Way, it will answer questions about the origin and evolution of our home galaxy. The first data release (2016) contains three-dimensional positions and two-dimensional motions of a subset of two million stars. The second data release (2018) increases that number to over 1.6 Billion. Gaia’s measurements are as precise as planned, paving the way to a better understanding of our galaxy and its neighborhood. The AIP hosts the Gaia data as one of the external data centers along with the main Gaia archive maintained by ESAC and provides access to the Gaia data releases as part of Gaia Data Processing and Analysis Consortium (DPAC).