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Found 53 result(s)
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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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The JenAge Ageing Factor Database AgeFactDB is aimed at the collection and integration of ageing phenotype and lifespan data. Ageing factors are genes, chemical compounds or other factors such as dietary restriction, for example. In a first step ageing-related data are primarily taken from existing databases. In addition, new ageing-related information is included both by manual and automatic information extraction from the scientific literature. Based on a homology analysis, AgeFactDB also includes genes that are homologous to known ageing-related genes. These homologs are considered as candidate or putative ageing-related genes.
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The TRR228DB is the project-database of the Collaborative Research Centre 228 "Future Rural Africa: Future-making and social-ecological transformation" (CRC/Transregio 228, https://www.crc228.de) funded by the German Research Foundation (DFG, German Research Foundation – Project number 328966760). The project-database is a new implementation of the TR32DB and online since 2018. It handles all data including metadata, which are created by the involved project participants from several institutions (e.g. Universities of Cologne and Bonn) and research fields (e.g. anthropology, agroeconomics, ecology, ethnology, geography, politics and soil sciences). The data is resulting from several field campaigns, interviews, surveys, remote sensing, laboratory studies and modelling approaches. Furthermore, outcomes of the scientists such as publications, conference contributions, PhD reports and corresponding images are collected.
STRING is a database of known and predicted protein interactions. The interactions include direct (physical) and indirect (functional) associations; they are derived from four sources: - Genomic Context - High-throughput Experiments - (Conserved) Coexpression - Previous Knowledge STRING quantitatively integrates interaction data from these sources for a large number of organisms, and transfers information between these organisms where applicable.
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Movebank is an online platform that helps researchers and wildlife managers worldwide manage, share, analyze and archive animal movement data. Movebank's database is designed for locations of individual animals over time, commonly referred to as tracking data, and measurements collected by other sensors attached to animals, as well as information about related animals, tags and deployments. The platform supports public and controlled-access sharing, and offers services for working with data from initial collection through publication, discovery and re-use.
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With Open Science OVGU the Otto-von-Guericke University provides its scientists with a research data repository. Measurement data, laboratory values, survey data, methodical test procedures, etc. can be archived in Open Science OVGU and made available to the scientific community via Open Access.
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The "Flora of Bavaria" initiative with its data portal (14 million occurrence data) and Wiki representation is primarily a citizen science project. Efforts to describe and monitor the flora of Bavaria have been ongoing for 100 years. The goal of these efforts is to record all vascular plants, including newcomers, and to document threatened or former local occurrences. Being geographically largest state of Germany with a broad range of habitats, Bavaria has a special responsibility for documenting and maintaining its plant diversity . About 85% of all German vascular plant species occur in Bavaria, and in addition it has about 50 endemic taxa, only known from Bavaria (most of them occur in the Alps). The Wiki is collaboration of volunteers and local and regional Bavarian botanical societies. Everybody is welcome to contribute, especially with photos or reports of local changes in the flora. The Flora of Bavaria project is providing access to a research data repository for occurrence data powered by the Diversity Workbench database framework.
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.
MetabolomeXchange.org delivers the mechanisms needed for disseminating the data to the metabolomics community at large (both metabolomics researchers and databases). The main objective is to make it easier for metabolomics researchers to become aware of newly released, publicly available, metabolomics datasets that may be useful for their research. MetabolomeXchange contains datasets from different data providers: MetaboLights, Metabolomic Repository Bordeaux, Metabolomics Workbench, and Metabolonote
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The University of Göttingen preserves one of the most important collections of scientific collections. At more than 30 distributed locations on the Göttingen Campus, the collections reflect its disciplinary diversity: the spectrum ranges from archeology to zoology, from astrophysical instruments to the living cell cultures of the algae collection. Historical legacy dating back to the Age of Enlightenment: The founding holdings of the Royal Academic Museum of Georgia Augusta are largely preserved. Research and teaching to date access to the collection objects and increase the stocks. Get to know our collections in this portal, which have been used to create knowledge for three centuries.
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coastMap offers campaign data, model analysis and thematic maps predominantly in the Biogeosciences. Spotlights explain in a nutshell important topics of the research conducted for the interested public. The portal offers applications to visualise and download field and laboratory work and to connect the information with interactive maps. Filter functions allow the user to search for general topics like a marine field of interest or single criteria, for example a specific ship campaign or one of 1000 measured parameters.
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The Leibniz Data Manager (LDM) is a scientific repository for research data from the fields of science and technology. The service supports a better re-usability of research data for scientific projects. The LDM fosters the management and access to heterogeneous research data publications and assists researchers in the selection of relevant data sets for their respective disciplines. The LDM currently offers the following functions for the visualization of research data: · Supports data collections and publications with different formats. · Different views on the same data set (2D and 3D support). · Visualization of Auto CAD files. · Jupyter Notes for demonstrating live code. · RDF Description of data collections.
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The German Central Health Study Hub is a platform that serves two different kinds of users. First, it allows scientists and data holding organizations (data producers) to publish their project characteristics, documents and data related to their research endeavour in a FAIR manner. Obviously, patient-level data cannot be shared publicly, however, metadata describing the patient-level data along with information about data access can be shared via the platform (preservation description information). The other kind of user is a scientist or researcher (data consumer) that likes to find information about past and ongoing studies and is interested in reusing existing patient-level data for their project. To summarize, the platforms connect data providers with data consumers in the domain of clinical, public health and epidemiologic health research to foster reuse. The platform aggregates and harmonizes information already entered in various public repositories such as DRKS, clinicaltrials.gov, WHO ICTRP to provide a holistic view of the German research landscape in the aforementioned research areas. In addition, data stewards actively collect available information from (public) resources such as websites that cannot be automatically integrated. The service started during the COVID-19 pandemic.
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Edmond is the institutional repository of the Max Planck Society for public research data. It enables Max Planck scientists to create citable scientific assets by describing, enriching, sharing, exposing, linking, publishing and archiving research data of all kinds. Further on, all objects within Edmond have a unique identifier and therefore can be clearly referenced in publications or reused in other contexts.
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OpenAgrar is an open access repository which publishes, stores, archives and distributes publications, publication references and research data. Its resources can be searched and used by everyone. It contains amongst others theses, reports, conference proceedings, journal articles, books, institutional documents, research datasets, videos and interviews.
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The GISAID Initiative promotes the international sharing of all influenza virus sequences, related clinical and epidemiological data associated with human viruses, and geographical as well as species-specific data associated with avian and other animal viruses, to help researchers understand how the viruses evolve, spread and potentially become pandemics. *** GISAID does so by overcoming disincentives/hurdles or restrictions, which discourage or prevented sharing of influenza data prior to formal publication. *** The Initiative ensures that open access to data in GISAID is provided free-of-charge and to everyone, provided individuals identify themselves and agree to uphold the GISAID sharing mechanism governed through its Database Access Agreement. GISAID calls on all users to agree to the basic premise of upholding scientific etiquette, by acknowledging the originating laboratories providing the specimen and the submitting laboratories who generate the sequence data, ensuring fair exploitation of results derived from the data, and that all users agree that no restrictions shall be attached to data submitted to GISAID, to promote collaboration among researchers on the basis of open sharing of data and respect for all rights and interests.
STOREDB is a platform for the archiving and sharing of primary data and outputs of all kinds, including epidemiological and experimental data, from research on the effects of radiation. It also provides a directory of bioresources and databases containing information and materials that investigators are willing to share. STORE supports the creation of a radiation research commons.
The human pluripotent stem cell registry (hPSCreg) is a public registry and data portal for human embryonic and induced pluripotent stem cell lines (hESC and hiPSC). The Registry provides comprehensive and standardized biological and legal information as well as tools to search and compare information from multiple hPSC sources and hence addresses a translational research need. To facilitate unambiguous identification over different resources, hPSCreg automatically creates a unique standardized name (identifier) for each cell line registered. In addition to biological information, hPSCreg stores extensive data about ethical standards regarding cell sourcing and conditions for application and privacy protection. hPSCreg is the first global registry that holds both, manually validated scientific and ethical information on hPSC lines, and provides access by means of a user-friendly, mobile-ready web application.
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Jülich DATA is a registry service to index all research data created at or in the context of Forschungszentrum Jülich. As an institutionial repository, it may also be used for data and software publications.
The Bremen Core Repository - BCR, for International Ocean Discovery Program (IODP), Integrated Ocean Discovery Program (IODP), Ocean Drilling Program (ODP), and Deep Sea Drilling Project (DSDP) cores from the Atlantic Ocean, Mediterranean and Black Seas and Arctic Ocean is operated at University of Bremen within the framework of the German participation in IODP. It is one of three IODP repositories (beside Gulf Coast Repository (GCR) in College Station, TX, and Kochi Core Center (KCC), Japan). One of the scientific goals of IODP is to research the deep biosphere and the subseafloor ocean. IODP has deep-frozen microbiological samples from the subseafloor available for interested researchers and will continue to collect and preserve geomicrobiology samples for future research.
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The data repository of the Helmholtz Centre for Environmental Research. The Data Investigation Portal (DRP) provides the opportunity to publicly access the administered data in the Data Management Portal and search them. The presentation is here limited to metadata and non-restricted information. DRP users can thus gain an overview of the data sets and, if necessary, contact the author to gain access to the data.
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Plastics are widely used in our economy and each year, at least 350-400 million tons are being produced at a global level. Due to poor recycling and low circular use, tens of millions of tons accumulate annually in marine and terrestrial environments. While it has become obvious that micro and macroplastics contaminate our environments recent research has identified few bacteria and fungi actively degrading plastics by enzymatic reactions. In general these are promiscuous enzymes (hydrolases) acting on low crystaline and mostly low density polymers of PET, ester-based PUR and oligomers of PA. Notably today, no enzymes have been characterized on a biochemical level for polymeric and crystaline PE, ether-based PUR, PS, PVC, PP. While many publications report on plastic degradation often, no convincing biochemical data have been published. Therefore the PAZy database lists exclusively biochemically characterized plastic-active enzymes. Predicted and putative enzymes that were not characterized on a biochemical, functional or structural level are not included in the PAZy database. The entries are manually curated.
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The public MorpheusML model repository collects, curates, documents and tests computational models for multi-scale and multicellular biological systems. Model must be encoded in the model description language MorpheusML. Subsections of the repository distinguish published models from contributed non-published and example models. New models are simulated in Morpheus or Artistoo independently from the authors and results are compared to published results. Successful reproduction is documented on the model's webpage. Models in this repository are included into the CI and test pipelines for each release of the model simulator Morpheus to check and guarantee reproducibility of results across future simulator updates. The model’s webpage provides a History-link to all past model versions and edits that are automatically tracked via Git. Each model is registered with a unique and persistent ID of the format M..... The model description page (incl. the biological context and key results of that model), the model’s XML file, the associated paper, and all further files (often simulation result videos) connected with that model can be retrieved via a persistent URL of the format https://identifiers.org/morpheus/M..... - for technical details on the citable ModelID please see https://registry.identifiers.org/registry/morpheus - for the model definition standard MorpheusML please see https://doi.org/10.25504/FAIRsharing.78b6a6 - for the model simulator Morpheus please see https://morpheus.gitlab.io - for the model simulator Artistoo please see https://artistoo.net/converter.html