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Found 14 result(s)
For datasets big and small; Store your research data online. Quickly and easily upload files of any type and we will host your research data for you. Your experimental research data will have a permanent home on the web that you can refer to.
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GovData the data portal for Germany offers consistent and central access to administrative data at the federal, state, and local level. Objective is to make data more available and easier to use at a single location. As set out in the concept of "open data", we attempt to facilitate the use of open licenses and to increase the supply of machine-readable raw data.
The Brown Digital Repository (BDR) is a place to gather, index, store, preserve, and make available digital assets produced via the scholarly, instructional, research, and administrative activities at Brown.
GeneWeaver combines cross-species data and gene entity integration, scalable hierarchical analysis of user data with a community-built and curated data archive of gene sets and gene networks, and tools for data driven comparison of user-defined biological, behavioral and disease concepts. Gene Weaver allows users to integrate gene sets across species, tissue and experimental platform. It differs from conventional gene set over-representation analysis tools in that it allows users to evaluate intersections among all combinations of a collection of gene sets, including, but not limited to annotations to controlled vocabularies. There are numerous applications of this approach. Sets can be stored, shared and compared privately, among user defined groups of investigators, and across all users.
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depositar — taking the term from the Portuguese/Spanish verb for to deposit — is an online repository for research data. The site is built by the researchers for the researchers. You are free to deposit, discover, and reuse datasets on depositar for all your research purposes.
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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 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.
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.
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.
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With the KIT Whole-Body Human Motion Database, we aim to provide a simple way of sharing high-quality motion capture recordings of human whole-body motion. In addition, with the Motion Annotation Tool (https://motion-annotation.humanoids.kit.edu/ ), we aim to collect a comprehensive set of whole-body motions along with natural language descriptions of these motions (https://motion-annotation.humanoids.kit.edu/dataset/).