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Found 121 result(s)
VertNet is a NSF-funded collaborative project that makes biodiversity data free and available on the web. VertNet is a tool designed to help people discover, capture, and publish biodiversity data. It is also the core of a collaboration between hundreds of biocollections that contribute biodiversity data and work together to improve it. VertNet is an engine for training current and future professionals to use and build upon best practices in data quality, curation, research, and data publishing. Yet, VertNet is still the aggregate of all of the information that it mobilizes. To us, VertNet is all of these things and more.
This project is an open invitation to anyone and everyone to participate in a decentralized effort to explore the opportunities of open science in neuroimaging. We aim to document how much (scientific) value can be generated from a data release — from the publication of scientific findings derived from this dataset, algorithms and methods evaluated on this dataset, and/or extensions of this dataset by acquisition and incorporation of new data. The project involves the processing of acoustic stimuli. In this study, the scientists have demonstrated an audiodescription of classic "Forrest Gump" to subjects, while researchers using functional magnetic resonance imaging (fMRI) have captured the brain activity of test candidates in the processing of language, music, emotions, memories and pictorial representations.In collaboration with various labs in Magdeburg we acquired and published what is probably the most comprehensive sample of brain activation patterns of natural language processing. Volunteers listened to a two-hour audio movie version of the Hollywood feature film "Forrest Gump" in a 7T MRI scanner. High-resolution brain activation patterns and physiological measurements were recorded continuously. These data have been placed into the public domain, and are freely available to the scientific community and the general public.
Originally named the Radiation Belt Storm Probes (RBSP), the mission was re-named the Van Allen Probes, following successful launch and commissioning. For simplicity and continuity, the RBSP short-form has been retained for existing documentation, file naming, and data product identification purposes. The RBSPICE investigation including the RBSPICE Instrument SOC maintains compliance with requirements levied in all applicable mission control documents.
The Space Physics Data Facility (SPDF) leads in the design and implementation of unique multi-mission and multi-disciplinary data services and software to strategically advance NASA's solar-terrestrial program, to extend our science understanding of the structure, physics and dynamics of the Heliosphere of our Sun and to support the science missions of NASA's Heliophysics Great Observatory. Major SPDF efforts include multi-mission data services such as Heliophysics Data Portal (formerly VSPO), CDAWeb and CDAWeb Inside IDL,and OMNIWeb Plus (including COHOWeb, ATMOWeb, HelioWeb and CGM) , science planning and orbit services such as SSCWeb, data tools such as the CDF software and tools, and a range of other science and technology research efforts. The staff supporting SPDF includes scientists and information technology experts.
iNaturalist is a citizen science project and online social network of naturalists, citizen scientists, and biologists built on the concept of mapping and sharing observations of biodiversity across the globe. iNat is a platform for biodiversity research, where anyone can start up their own science project with a specific purpose and collaborate with other observers.
WikiPathways was established to facilitate the contribution and maintenance of pathway information by the biology community. WikiPathways is an open, collaborative platform dedicated to the curation of biological pathways. WikiPathways thus presents a new model for pathway databases that enhances and complements ongoing efforts, such as KEGG, Reactome and Pathway Commons. Building on the same MediaWiki software that powers Wikipedia, we added a custom graphical pathway editing tool and integrated databases covering major gene, protein, and small-molecule systems. The familiar web-based format of WikiPathways greatly reduces the barrier to participate in pathway curation. More importantly, the open, public approach of WikiPathways allows for broader participation by the entire community, ranging from students to senior experts in each field. This approach also shifts the bulk of peer review, editorial curation, and maintenance to the community.
TreeGenes is a genomic, phenotypic, and environmental data resource for forest tree species. The TreeGenes database and Dendrome project provide custom informatics tools to manage the flood of information.The database contains several curated modules that support the storage of data and provide the foundation for web-based searches and visualization tools. GMOD GUI tools such as CMAP for genetic maps and GBrowse for genome and transcriptome assemblies are implemented here. A sample tracking system, known as the Forest Tree Genetic Stock Center, sits at the forefront of most large-scale projects. Barcode identifiers assigned to the trees during sample collection are maintained in the database to identify an individual through DNA extraction, resequencing, genotyping and phenotyping. DiversiTree, a user-friendly desktop-style interface, queries the TreeGenes database and is designed for bulk retrieval of resequencing data. CartograTree combines geo-referenced individuals with relevant ecological and trait databases in a user-friendly map-based interface. ---- The Conifer Genome Network (CGN) is a virtual nexus for researchers working in conifer genomics. The CGN web site is maintained by the Dendrome Project at the University of California, Davis.
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.
Digital Rocks is a data portal for fast storage and retrieval of images of varied porous micro-structures. It has the purpose of enhancing research resources for modeling/prediction of porous material properties in the fields of Petroleum, Civil and Environmental Engineering as well as Geology. This platform allows managing and preserving available images of porous materials and experiments performed on them, and any accompanying measurements (porosity, capillary pressure, permeability, electrical, NMR and elastic properties, etc.) required for both validation on modeling approaches and the upscaling and building of larger (hydro)geological models. Starting September 2021 we charge fees for publishing larger projects; projects < 2GB remain free: see user agreement https://www.digitalrocksportal.org/user-agreement/
ERDDAP is a data server that gives you a simple, consistent way to download subsets of gridded and tabular scientific datasets in common file formats and make graphs and maps. This particular ERDDAP installation has oceanographic data (for example, data from satellites and buoys).
GeoCommons is the public community of GeoIQ users who are building an open repository of data and maps for the world. The GeoIQ platform includes a large number of features that empower you to easily access, visualize and analyze your data. The GeoIQ platform powers the growing GeoCommons community of over 25,000 members actively creating and sharing hundreds of thousands of datasets and maps across the world. With GeoCommons, anyone can contribute and share open data, easily build shareable maps and collaborate with others.
UltraViolet is part of a suite of repositories at New York University that provide a home for research materials, operated as a partnership of the Division of Libraries and NYU IT's Research and Instruction Technology. UltraViolet provides faculty, students, and researchers within our university community with a place to deposit scholarly materials for open access and long-term preservation. UltraViolet also houses some NYU Libraries collections, including proprietary data collections.
The U.S. Department of Energy’s (DOE) Environmental Systems Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) data archive serves Earth and environmental science data. ESS-DIVE is funded by the Data Management program within the Climate and Environmental Science Division under the DOE’s Office of Biological and Environmental Research program (BER), and is maintained by the Lawrence Berkeley National Laboratory. ESS-DIVE will archive and publicly share data obtained from observational, experimental, and modeling research that is funded by the DOE’s Office of Science under its Subsurface Biogeochemical Research (SBR) and Terrestrial Ecosystem Science (TES) programs within the Environmental Systems Science (ESS) activity. ESS-DIVE was launched in July 2017, and is designed to provide long-term stewardship and use of data from observational, experimental and modeling activities in the DOE in the Subsurface Biogeochemical Research (SBR) and Terrestrial Ecosystem Science (TES) Programs in the Environmental System Science (ESS) activity.
mzCloud is an extensively curated database of high-resolution tandem mass spectra that are arranged into spectral trees. MS/MS and multi-stage MSn spectra were acquired at various collision energies, precursor m/z, and isolation widths using Collision-induced dissociation (CID) and Higher-energy collisional dissociation (HCD). Each raw mass spectrum was filtered and recalibrated giving rise to additional filtered and recalibrated spectral trees that are fully searchable. Besides the experimental and processed data, each database record contains the compound name with synonyms, the chemical structure, computationally and manually annotated fragments (peaks), identified adducts and multiply charged ions, molecular formulas, predicted precursor structures, detailed experimental information, peak accuracies, mass resolution, InChi, InChiKey, and other identifiers. mzCloud is a fully searchable library that allows spectra searches, tree searches, structure and substructure searches, monoisotopic mass searches, peak (m/z) searches, precursor searches, and name searches. mzCloud is free and available for public use online.
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LIAS is a global information system for Lichenized and Non-Lichenized Ascomycetes. It includes several interoperable data repositories. In recent years, the two core components ‘LIAS names’ and ‘LIAS light’ have been much enlarged. LIAS light is storing phenotypic trait data. They includes > 10,700 descriptions (about 2/3 of all known lichen species), each with up to 75 descriptors comprising 2,000 traits (descriptor states and values), including 800 secondary metabolites. 500 traits may have biological functions and more than 1,000 may have phylogenetic relevance. LIAS is thus one of the most comprehensive trait databases in organismal biology. The online interactive identification key for more than 10,700 lichens is powered by the Java applet NaviKey and has been translated into 19 languages (besides English) in cooperation with lichenologists worldwide. The component ‘LIAS names’ is a platform for managing taxonomic names and classifications with currently >50,000 names, including the c. 12,000 accepted species and recognized synonyms. The LIAS portal contents, interfaces, and databases run on servers of the IT Center of the Bavarian Natural History Collections and are maintained there. 'LIAS names' and ‘LIAS light’ also deliver content data to the Catalogue of Life, acting as the Global Species Database (GSD) for lichens. LIAS gtm is a database for visualising the geographic distribution of lichen traits. LIAS is powered by the Diversity Workbench database framework with several interfaces for data management and publication. The LIAS long-term project was initiated in the early 1990s and has since been continued with funding from the DFG, the BMBF, and the EU.
The NCEAS Data Repository contains information about the research data sets collected and collated as part of NCEAS' funded activities. Information in the NCEAS Data Repository is concurrently available through the Knowledge Network for Biocomplexity (KNB), an international data repository. A number of the data sets were synthesized from multiple data sources that originated from the efforts of many contributors, while others originated from a single. Datasets can be found at KNB repository https://knb.ecoinformatics.org/data , creator=NCEAS
Funded by the National Science Foundation (NSF) and proudly operated by Battelle, the National Ecological Observatory Network (NEON) program provides open, continental-scale data across the United States that characterize and quantify complex, rapidly changing ecological processes. The Observatory’s comprehensive design supports greater understanding of ecological change and enables forecasting of future ecological conditions. NEON collects and processes data from field sites located across the continental U.S., Puerto Rico, and Hawaii over a 30-year timeframe. NEON provides free and open data that characterize plants, animals, soil, nutrients, freshwater, and the atmosphere. These data may be combined with external datasets or data collected by individual researchers to support the study of continental-scale ecological change.
EMAGE (e-Mouse Atlas of Gene Expression) is an online biological database of gene expression data in the developing mouse (Mus musculus) embryo. The data held in EMAGE is spatially annotated to a framework of 3D mouse embryo models produced by EMAP (e-Mouse Atlas Project). These spatial annotations allow users to query EMAGE by spatial pattern as well as by gene name, anatomy term or Gene Ontology (GO) term. EMAGE is a freely available web-based resource funded by the Medical Research Council (UK) and based at the MRC Human Genetics Unit in the Institute of Genetics and Molecular Medicine, Edinburgh, UK.
The ColabFit Exchange is an online resource for the discovery, exploration and submission of datasets for data-driven interatomic potential (DDIP) development for materials science and chemistry applications. ColabFit's goal is to increase the Findability, Accessibility, Interoperability, and Reusability (FAIR) of DDIP data by providing convenient access to well-curated and standardized first-principles and experimental datasets. Content on the ColabFit Exchange is open source and freely available.
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 Linguistic Data Consortium (LDC) is an open consortium of universities, libraries, corporations and government research laboratories. It was formed in 1992 to address the critical data shortage then facing language technology research and development. Initially, LDC's primary role was as a repository and distribution point for language resources. Since that time, and with the help of its members, LDC has grown into an organization that creates and distributes a wide array of language resources. LDC also supports sponsored research programs and language-based technology evaluations by providing resources and contributing organizational expertise. LDC is hosted by the University of Pennsylvania and is a center within the University’s School of Arts and Sciences.
Additionally to the institutional repository, current St. Edward's faculty have the option of uploading their work directly to their own SEU accounts on stedwards.figshare.com. Projects created on Figshare will automatically be published on this website as well. For more information, please see documentation
Nuclear Data Services contains atomic, molecular and nuclear data sets for the development and maintenance of nuclear technologies. It includes energy-dependent reaction probabilities (cross sections), the energy and angular distributions of reaction products for many combinations of target and projectile, and the atomic and nuclear properties of excited states, and their radioactive decay data. Their main concern is providing data required to design a modern nuclear reactor for electricity production. Approximately 11.5 million nuclear data points have been measured and compiled into computerized form.
The Sequence Read Archive stores the raw sequencing data from such sequencing platforms as the Roche 454 GS System, the Illumina Genome Analyzer, the Applied Biosystems SOLiD System, the Helicos Heliscope, and the Complete Genomics. It archives the sequencing data associated with RNA-Seq, ChIP-Seq, Genomic and Transcriptomic assemblies, and 16S ribosomal RNA data.