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Found 18 result(s)
The Scholarly Database (SDB) at Indiana University aims to serve researchers and practitioners interested in the analysis, modeling, and visualization of large-scale scholarly datasets. The online interface provides access to six datasets: MEDLINE papers, registered Clinical Trials, U.S. Patent and Trademark Office patents (USPTO), National Science Foundation (NSF) funding, National Institutes of Health (NIH) funding, and National Endowment for the Humanities funding – over 26 million records in total.
Yoda publishes research data on behalf of researchers that are affiliated with Utrecht University, its research institutes and consortia where it acts as a coordinating body. Data packages are not limited to a particular field of research or license. Yoda publishes data packages via Datacite. To find data publications use: https://public.yoda.uu.nl/ , or the Datacite search engine: https://search.datacite.org/repositories/delft.uu
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One of the world’s largest banks of biological, psychosocial and clinical data on people suffering from mental health problems. The Signature center systematically collects biological, psychosocial and clinical indicators from patients admitted to the psychiatric emergency and at four points throughout their journey in the hospital: upon arrival to the emergency room (state of crisis), at the end of their hospital stay, as well as at the beginning and the end of outpatient treatment. For all hospital clients who agree to participate, blood specimens are collected for the purpose of measuring metabolic, genetic, toxic and infectious biomarkers, while saliva samples are collected to measure sex hormones and hair samples are collected to measure stress hormones. Questionnaire has been selected to cover important dimensional aspects of mental illness such as Behaviour and Cognition (Psychosis, Depression, Anxiety, Impulsiveness, Aggression, Suicide, Addiction, Sleep),Socio-demographic Profile (Spiritual beliefs, Social functioning, Childhood experiences, Demographic, Family background) and Medical Data (Medication, Diagnosis, Long-term health, RAMQ data). On 2016, May there are more than 1150 participants and 400 for the longitudinal Follow-Up
The National Science Foundation (NSF) Ultraviolet (UV) Monitoring Network provides data on ozone depletion and the associated effects on terrestrial and marine systems. Data are collected from 7 sites in Antarctica, Argentina, United States, and Greenland. The network is providing data to researchers studying the effects of ozone depletion on terrestrial and marine biological systems. Network data is also used for the validation of satellite observations and for the verification of models describing the transfer of radiation through the atmosphere.
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<<<!!!<<< This repository is no longer available. >>>!!!>>> C3-Grid is an ALREADY FINISHED project within D-Grid, the initiative to promote a grid-based e-Science framework in Germany. The goal of C3-Grid is to support the workflow of Earth system researchers. A grid infrastructure will be implemented that allows efficient distributed data processing and inter-institutional data exchange. Aim of the effort was to develop an infrastructure for uniform access to heterogeneous data and distributed data processing. The work was structured in two projects funded by the Federal Ministry of Education and Research. The first project was part of the D-Grid initiative and explored the potential of grid technology for climate research and developed a prototype infrastructure. Details about the C3Grid architecture are described in “Earth System Modelling – Volume 6”. In the second phase "C3Grid - INAD: Towards an Infrastructure for General Access to Climate Data" this infrastructure was improved especially with respect to interoperability to Earth System Grid Federation (ESGF). Further the portfolio of available diagnostic workflows was expanded. These workflows can be re-used now in adjacent infrastructures MiKlip Evaluation Tool (http://www.fona-miklip.de/en/index.php) and as Web Processes within the Birdhouse Framework (http://bird-house.github.io/). The Birdhouse Framework is now funded as part of the European Copernicus Climate Change Service (https://climate.copernicus.eu/) managed by ECMWF and will be extended to provide scalable processing services for ESGF hosted data at DKRZ as well as IPSL and BADC.
The Virtual Research Environment (VRE) is an open-source data management platform that enables medical researchers to store, process and share data in compliance with the European Union (EU) General Data Protection Regulation (GDPR). The VRE addresses the present lack of digital research data infrastructures fulfilling the need for (a) data protection for sensitive data, (b) capability to process complex data such as radiologic imaging, (c) flexibility for creating own processing workflows, (d) access to high performance computing. The platform promotes FAIR data principles and reduces barriers to biomedical research and innovation. The VRE offers a web portal with graphical and command-line interfaces, segregated data zones and organizational measures for lawful data onboarding, isolated computing environments where large teams can collaboratively process sensitive data privately, analytics workbench tools for processing, analyzing, and visualizing large datasets, automated ingestion of hospital data sources, project-specific data warehouses for structured storage and retrieval, graph databases to capture and query ontology-based metadata, provenance tracking, version control, and support for automated data extraction and indexing. The VRE is based on a modular and extendable state-of-the art cloud computing framework, a RESTful API, open developer meetings, hackathons, and comprehensive documentation for users, developers, and administrators. The VRE with its concerted technical and organizational measures can be adopted by other research communities and thus facilitates the development of a co-evolving interoperable platform ecosystem with an active research community.
MEMENTO aims to become a valuable tool for identifying regions of the world ocean that should be targeted in future work to improve the quality of air-sea flux estimates.
In 2003, the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) at NIH established Data, Biosample, and Genetic Repositories to increase the impact of current and previously funded NIDDK studies by making their data and biospecimens available to the broader scientific community. These Repositories enable scientists not involved in the original study to test new hypotheses without any new data or biospecimen collection, and they provide the opportunity to pool data across several studies to increase the power of statistical analyses. In addition, most NIDDK-funded studies are collecting genetic biospecimens and carrying out high-throughput genotyping making it possible for other scientists to use Repository resources to match genotypes to phenotypes and to perform informative genetic analyses.
The Central Neuroimaging Data Archive (CNDA) allows for sharing of complex imaging data to investigators around the world, through a simple web portal. The CNDA is an imaging informatics platform that provides secure data management services for Washington University investigators, including source DICOM imaging data sharing to external investigators through a web portal, cnda.wustl.edu. The CNDA’s services include automated archiving of imaging studies from all of the University’s research scanners, automated quality control and image processing routines, and secure web-based access to acquired and post-processed data for data sharing, in compliance with NIH data sharing guidelines. The CNDA is currently accepting datasets only from Washington University affiliated investigators. Through this platform, the data is available for broad sharing with researchers both internal and external to Washington University.. The CNDA overlaps with data in oasis-brains.org https://www.re3data.org/repository/r3d100012182, but CNDA is a larger data set.
ETH Data Archive is ETH Zurich's long-term preservation solution for digital information such as research data, digitised content, archival records, or images. It serves as the backbone of data curation and for most of its content, it is a “dark archive” without public access. In this capacity, the ETH Data Archive also archives the content of ETH Zurich’s Research Collection which is the primary repository for members of the university and the first point of contact for publication of data at ETH Zurich. All data that was produced in the context of research at the ETH Zurich, can be published and archived in the Research Collection. An automated connection to the ETH Data Archive in the background ensures the medium to long-term preservation of all publications and research data. Direct access to the ETH Data Archive is intended only for customers who need to deposit software source code within the framework of ETH transfer Software Registration. Open Source code packages and other content from legacy workflows can be accessed via ETH Library @ swisscovery (https://library.ethz.ch/en/).
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sciencedata.dk is a research data store provided by DTU, the Danish Technical University, specifically aimed at researchers and scientists at Danish academic institutions. The service is intended for working with and sharing active research data as well as for safekeeping of large datasets. The data can be accessed and manipulated via a web interface, synchronization clients, file transfer clients or the command line. The service is built on and with open-source software from the ground up: FreeBSD, ZFS, Apache, PHP, ownCloud/Nextcloud. DTU is actively engaged in community efforts on developing research-specific functionality for data stores. Our servers are attached directly to the 10-Gigabit backbone of "Forskningsnettet" (the National Research and Education Network of Denmark) - implying that up and download speed from Danish academic institutions is in principle comparable to those of an external USB hard drive. Data store for research data allowing private sharing and sharing via links / persistent URLs.
The Cancer Cell Line Encyclopedia project is a collaboration between the Broad Institute, and the Novartis Institutes for Biomedical Research and its Genomics Institute of the Novartis Research Foundation to conduct a detailed genetic and pharmacologic characterization of a large panel of human cancer models, to develop integrated computational analyses that link distinct pharmacologic vulnerabilities to genomic patterns and to translate cell line integrative genomics into cancer patient stratification. The CCLE provides public access to genomic data, analysis and visualization for about 1000 cell lines.
The FREEBIRD website aims to facilitate data sharing in the area of injury and emergency research in a timely and responsible manner. It has been launched by providing open access to anonymised data on over 30,000 injured patients (the CRASH-1 and CRASH-2 trials).
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The Marine Data Archive (MDA) is an online repository specifically developed to independently archive data files in a fully documented manner. The MDA can serve individuals, consortia, working groups and institutes to manage data files and file versions for a specific context (project, report, analysis, monitoring campaign), as a personal or institutional archive or back-up system and as an open repository for data publication.
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 !!!
BeiDare2 is currently at beta version. All new users should try the new service as we no longer provide training for the classic BioDare. - BioDare stands for Biological Data Repository, its main focus is data from circadian experiments. BioDare is an online facility to share, store, analyse and disseminate timeseries data, focussing on circadian clock data, with browser and web service interfaces. Toolbox features include an improved, speedier FFT-NLLs routine and ROBuST’s Spectrum Resampling tool that will analyse rhythmic time series data.