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Found 21 result(s)
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Content type(s)
<<<!!!<<< 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.
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myExperiment is a collaborative environment where scientists can safely publish their workflows and in silico experiments, share them with groups and find those of others. Workflows, other digital objects and bundles (called Packs) can now be swapped, sorted and searched like photos and videos on the Web. Unlike Facebook or MySpace, myExperiment fully understands the needs of the researcher and makes it really easy for the next generation of scientists to contribute to a pool of scientific methods, build communities and form relationships — reducing time-to-experiment, sharing expertise and avoiding reinvention. myExperiment is now the largest public repository of scientific workflows.
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A secure platform for developing and sharing reproducible methods. A research protocol is a document that describes the background, rationale, objectives, design, methodology, statistical considerations, and organization of a clinical research project.
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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.
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The CLARIN-D Centre CEDIFOR provides a repository for long-term storage of resources and meta-data. Resources hosted in the repository stem from research of members as well as associated research projects of CEDIFOR. This includes software and web-services as well as corpora of text, lexicons, images and other data.
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Scicat allows users to access the metadata of raw and derived data which is taken at experiment facilities. Scientific datasets are linked to proposals and samples. Scientific datasets are can be linked to publications (DOI, PID). SciCat helps keeping track of data provenance (i.e. the steps leading to the final results). Scicat allows users to find data based on the metadata (both your own data and other peoples’ public data). In the long term, SciCat will help to automate scientific analysis workflows.
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The Department of Energy Systems Biology Knowledgebase (KBase) is a software and data platform designed to meet the grand challenge of systems biology: predicting and designing biological function. KBase integrates data and tools in a unified graphical interface so users do not need to access them from numerous sources or learn multiple systems in order to create and run sophisticated systems biology workflows. Users can perform large-scale analyses and combine multiple lines of evidence to model plant and microbial physiology and community dynamics.
KBase is the first large-scale bioinformatics system that enables users to upload their own data, analyze it (along with collaborator and public data), build increasingly realistic models, and share and publish their workflows and conclusions. KBase aims to provide a knowledgebase: an integrated environment where knowledge and insights are created and multiplied.
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Harmonized, indexed, searchable large-scale human FG data collection with extensive metadata. Provides scalable, unified way to easily access massive functional genomics (FG) and annotation data collections curated from large-scale genomic studies. Direct integration (API) with custom / high-throughput genetic and genomic analysis workflows.
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The German Neuroinformatics Node's data infrastructure (GIN) services provide a platform for comprehensive and reproducible management and sharing of neuroscience data. Building on well established versioning technology, GIN offers the power of a web based repository management service combined with a distributed file storage. The service addresses the range of research data workflows starting from data analysis on the local workstation to remote collaboration and data publication.
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ClinVar is a freely accessible, public archive of reports of the relationships among human variations and phenotypes, with supporting evidence. ClinVar thus facilitates access to and communication about the relationships asserted between human variation and observed health status, and the history of that interpretation. ClinVar processes submissions reporting variants found in patient samples, assertions made regarding their clinical significance, information about the submitter, and other supporting data. The alleles described in submissions are mapped to reference sequences, and reported according to the HGVS standard. ClinVar then presents the data for interactive users as well as those wishing to use ClinVar in daily workflows and other local applications. ClinVar works in collaboration with interested organizations to meet the needs of the medical genetics community as efficiently and effectively as possible
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The Media Repository is a web-based digital asset management system to store, organize and share digital media files. Not only images and documents are directly supported – audio and video content is supported as well. The data can be re-used in other systems. The system manages a variety of file formats and metadata schemes. It stores and organizes media data and helps to manage workflows with them.
Public web presentations are possible as well as collaborative work in restricted groups. The Media Repository helps both small teams and larger research projects in the management of media assets and their long-term storage.
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GESIS preserves (mainly quantitative) social research data to make it available to the scientific research community. The data is described in a standardized way, secured for the long term, provided with a permanent identifier (DOI), and can be easily found and reused through browser-optimized catalogs (https://search.gesis.org/).
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Reference anatomies of the brain and corresponding atlases play a central role in experimental neuroimaging workflows and are the foundation for reporting standardized results. The choice of such references —i.e., templates— and atlases is one relevant source of methodological variability across studies, which has recently been brought to attention as an important challenge to reproducibility in neuroscience. TemplateFlow is a publicly available framework for human and nonhuman brain models. The framework combines an open database with software for access, management, and vetting, allowing scientists to distribute their resources under FAIR —findable, accessible, interoperable, reusable— principles. TemplateFlow supports a multifaceted insight into brains across species, and enables multiverse analyses testing whether results generalize across standard references, scales, and in the long term, species, thereby contributing to increasing the reliability of neuroimaging results.
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National Data Repository (NDR) is a reliable and integrated data repository of Exploration and Production (E&P) data of Indian sedimentary basins. It offers a unique platform to all concerns of E&P with provisions for seamless access to reliable geo-scientific data for India. Streamlining all associated procedures, policies and workflows pertaining to data submission, data management, data retrieval for all concerned pertaining to government agencies, academia and research communities with restrictions. NDR is owned by the Government of India, hosted at Directorate General of Hydrocarbons (DGH), Ministry of Petroleum and Natural Gas (MoPNG). Objectively it operates with geological data, petrophysical data, natural gas, seismic data, well & log data, spatial data, Reservoir data, Gravity & Magnetic data. NDR maintains and preserve hydrocarbon exploration & production data in a standard and reusable manner, but can't made available to entitled users freely. One cannot get access independently.
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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.
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Kadi4Mat instance for use at the Karlsruhe Institute of Technology (KIT) and for cooperations, including the Cluster of Competence for Solid-state Batteries (FestBatt), the Battery Competence Cluster Analytics/Quality Assurance (AQua), and more.
Kadi4Mat is the Karlsruhe Data Infrastructure for Materials Science, an open source software for managing research data. It is being developed as part of several research projects at the Institute for Applied Materials - Microstructure Modelling and Simulation (IAM-MMS) of the Karlsruhe Institute of Technology (KIT).
The goal of this project is to combine the ability to manage and exchange data, the repository , with the possibility to analyze, visualize and transform said data, the electronic lab notebook (ELN). Kadi4Mat supports a close cooperation between experimenters, theorists and simulators, especially in materials science, to enable the acquisition of new knowledge and the development of novel materials. This is made possible by employing a modular and generic architecture, which allows to cover the specific needs of different scientists, each utilizing unique workflows. At the same time, this opens up the possibility of covering other research disciplines as well.
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RADAR offers researchers at publicly funded universities and non-academic research institutions in Germany a customized and user-friendly repository for archiving and publication of research data independent of discipline and format. The administration of the service, the individual workflows for uploading, organising and annotating the research data with metadata as well as the curation of the datasets and optional quality assurance through peer review are the responsibility of the using institution. For data archiving, data providers can flexibly choose retention periods (5, 10, 15 years) and define access rights. Published datasets are kept for at least 25 years, they are always assigned a DOI via DataCite and can thus be internationally identified and cited. RADAR is operated exclusively on servers in Germany. The data are stored in three copies at two locations. All contracts are subject to German law.
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Currently, the IMS repository focuses on resources provided by the Institute for Natural Language Processing in Stuttgart (IMS) and other CLARIN-D related institutions such as the local Collaborative Research Centre 732 (SFB 732) as well as institutions and/or organizations that belong to the CLARIN-D extended scientific community. Comprehensive guidelines and workflows for submission by external contributors are being compiled based on the experiences in archiving such in-house resources.
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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.
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The European Nucleotide Archive (ENA) captures and presents information relating to experimental workflows that are based around nucleotide sequencing. A typical workflow includes the isolation and preparation of material for sequencing, a run of a sequencing machine in which sequencing data are produced and a subsequent bioinformatic analysis pipeline. ENA records this information in a data model that covers input information (sample, experimental setup, machine configuration), output machine data (sequence traces, reads and quality scores) and interpreted information (assembly, mapping, functional annotation).
Data arrive at ENA from a variety of sources. These include submissions of raw data, assembled sequences and annotation from small-scale sequencing efforts, data provision from the major European sequencing centres and routine and comprehensive exchange with our partners in the International Nucleotide Sequence Database Collaboration (INSDC).
Provision of nucleotide sequence data to ENA or its INSDC partners has become a central and mandatory step in the dissemination of research findings to the scientific community. ENA works with publishers of scientific literature and funding bodies to ensure compliance with these principles and to provide optimal submission systems and data access tools that work seamlessly with the published literature.
Subject(s)
- Social and Behavioural Sciences
- Microbiology, Virology and Immunology
- Agriculture, Forestry, Horticulture and Veterinary Medicine
- Chemistry
- Biology
- Geosciences (including Geography)
- Computer Science, Electrical and System Engineering
- Physics
- Humanities and Social Sciences
- Medicine
- Life Sciences
- Agriculture, Forestry, Horticulture and Veterinary Medicine
- Natural Sciences
- Engineering Sciences
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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/).
- Current projects
- EOSC FAIR-IMPACT
- re3data COREF
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- Cite this service: re3data.org - Registry of Research Data Repositories. https://doi.org/10.17616/R3D last accessed: 2024-05-19
