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Found 25 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.
OBIS strives to document the ocean's diversity, distribution and abundance of life. Created by the Census of Marine Life, OBIS is now part of the Intergovernmental Oceanographic Commission (IOC) of UNESCO, under its International Oceanographic Data and Information Exchange (IODE) programme
RAVE (RAdial Velocity Experiment) is a multi-fiber spectroscopic astronomical survey of stars in the Milky Way using the 1.2-m UK Schmidt Telescope of the Anglo-Australian Observatory (AAO). The RAVE collaboration consists of researchers from over 20 institutions around the world and is coordinated by the Leibniz-Institut für Astrophysik Potsdam. As a southern hemisphere survey covering 20,000 square degrees of the sky, RAVE's primary aim is to derive the radial velocity of stars from the observed spectra. Additional information is also derived such as effective temperature, surface gravity, metallicity, photometric parallax and elemental abundance data for the stars. The survey represents a giant leap forward in our understanding of our own Milky Way galaxy; with RAVE's vast stellar kinematic database the structure, formation and evolution of our Galaxy can be studied.
The Arctic Permafrost Geospatial Centre (APGC) is an Open Access Circum-Arctic Geospatial Data Portal that promotes, describes and visualizes geospatial permafrost data. A data catalogue and a WebGIS application allow to easily discover and view data and metadata. Data can be downloaded directly via link to the publishing data repository.
We present the MUSE-Wide survey, a blind, 3D spectroscopic survey in the CANDELS/GOODS-S and CANDELS/COSMOS regions. Each MUSE-Wide pointing has a depth of 1 hour and hence targets more extreme and more luminous objects over 10 times the area of the MUSE-Deep fields (Bacon et al. 2017). The legacy value of MUSE-Wide lies in providing "spectroscopy of everything" without photometric pre-selection. We describe the data reduction, post-processing and PSF characterization of the first 44 CANDELS/GOODS-S MUSE-Wide pointings released with this publication. Using a 3D matched filtering approach we detected 1,602 emission line sources, including 479 Lyman-α (Lya) emitting galaxies with redshifts 2.9≲z≲6.3. We cross-match the emission line sources to existing photometric catalogs, finding almost complete agreement in redshifts and stellar masses for our low redshift (z < 1.5) emitters. At high redshift, we only find ~55% matches to photometric catalogs. We encounter a higher outlier rate and a systematic offset of Δz≃0.2 when comparing our MUSE redshifts with photometric redshifts. Cross-matching the emission line sources with X-ray catalogs from the Chandra Deep Field South, we find 127 matches, including 10 objects with no prior spectroscopic identification. Stacking X-ray images centered on our Lya emitters yielded no signal; the Lya population is not dominated by even low luminosity AGN. A total of 9,205 photometrically selected objects from the CANDELS survey lie in the MUSE-Wide footprint, which we provide optimally extracted 1D spectra of. We are able to determine the spectroscopic redshift of 98% of 772 photometrically selected galaxies brighter than 24th F775W magnitude. All the data in the first data release - datacubes, catalogs, extracted spectra, maps - are available at the website.
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.
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Scans of plates obtained at Landessternwarte Heidelberg-Königstuhl and German-Spanish Astronomical Center (Calar Alto Observatory), Spain, 1900 through 1999.
The Harvard Dataverse is open to all scientific data from all disciplines worldwide. It includes the world's largest collection of social science research data. It is hosting data for projects, archives, researchers, journals, organizations, and institutions.
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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The web service correspSearch aggregates metadata of letters from printed and digital scholarly editions and publications. It offers the aggregated correspondence metadata both via a feature-rich interface and via an API. The letter metadata are provided by scholarly projects of different institutions in a standardised, TEI-XML-based exchange format and and by using IDs from authority files (GeoNames, GND, VIAF etc.). The web service itself does not set a spatial or temporal collection focus. Currently, the time frame of the aggregated correspondence data ranges from 1500 to the 20th century.
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In 2018, the Ministry of Higher Education, Research and Innovation has included in its roadmap the creation of a new infrastructure called the National Biodiversity Data Centre (PNDB). The PNDB's missions are part of a FAIR (Easy to Find, Accessible, Interoperable, Reusable) approach, and consist in - providing access to datasets and metadata, associated services and products derived from the analyses - promoting scientific leadership to identify gaps and foster the emergence of community-driven systems of users and producers - facilitate the sharing of practices with other research communities, encourage the sharing of data and their reuse, and be part of the reflection on the future Earth System infrastructure. - promote coherence with national, European and international efforts concerning access to and use of biodiversity research data and the promotion of products and services. The PNDB is supported by the Muséum national d'Histoire naturelle, more specifically by the UMS 2006 PatriNat, a MNHN CNRS and AFB unit. The project is closely linked with the FRB and several of its founding institutions (AFB, BRGM, CIRAD, CNRS, Ifremer, INERIS, INRA, IRD, IRSTEA, MNHN, Univ. Montpellier).
The EarthChem Library is a data repository that archives, publishes and makes accessible data and other digital content from geoscience research (analytical data, data syntheses, models, technical reports, etc.)
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The purpose of the Social Data Repository (RDS) is to make available in the Internet social data, consisting of data sets and accompanying technical or methodological documentation. The use of Repository is open for everyone. The repository is operated by the University of Warsaw (Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw). Individual collections in the Social Data Repository are subject to editorial review by University of Warsaw or collection administrators, under separate rules for a given collection. In particular, the supervising editor for the collection “Archive of Quantitative Social Data” is the Team of the Archive of Quantitative Social Data.
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.
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The Research Data Repository of FID move is a digital long-term repository for open data from the field of transport and mobility research. All datasets are provided with an open licence and are assigned a persistent DataCite DOI (Digital Object Identifier). Both data search and archiving are free. The Specialised Information Service for Mobility and Transport Research (FID move) has been set up by the Saxon State and University Library Dresden (SLUB) and the German TIB – Leibniz Information Centre for Science and Technology as part of the DFG funding programme "Specialised Information Services".
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German astronomical observatories own considerable collection of photographic plates. While these observations lead to significant discoveries in the past, they are also of interest for scientists today and in the future. In particular, for the study of long-term variability of many types of stars, these measurements are of immense scientific value. There are about 85000 plates in the archives of Hamburger Sternwarte, Dr. Karl Remeis-Sternwarte Bamberg, and Leibniz-Institut für Astrophysik Potsdam (AIP). The plates are digitized with high-resolution flatbed scanners. In addition, the corresponding plate envelopes and observation logbooks are digitized, and further metadata are entered into the database. The work is carried out within the project “Digitalisierung astronomischer Fotoplatten und ihre Integration in das internationale Virtual Observatory”, which is funded by the DFG.
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The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) is a community-driven climate impact modeling initiative that aims to contribute to a quantitative and cross-sectoral synthesis of the various impacts of climate change, including associated uncertainties. It is designed as a continuous model intercomparison and improvement process for climate impact models and is supported by the international climate impact research community. ISIMIP is organized into simulation rounds, for which a simulation protocol specifies a set of common experiments. The protocol further describes a set of climate and direct human forcing data to be used as input data for all ISIMIP simulations. Based on this information, modelling groups from different sectors (e.g. agriculture, biomes, water) perform simulations using various climate impact models. After the simulations are performed, the data is collected by the ISIMIP data team, quality controlled and eventually published on the ISIMIP Repository. From there, it can be freely accessed for further research and analyses. The data is widely used within academia, but also by companies and civil society. ISIMIP was initiated by the Potsdam Institute for Climate Impact Research (PIK) and the International Institute for Applied Systems Analysis (IIASA).
The Astronomy data repository at Harvard is currently open to all scientific data from astronomical institutions worldwide. Incorporating Astroinformatics of galaxies and quasars Dataverse. The Astronomy Dataverse is connected to the indexing services provided by the SAO/NASA Astrophysical Data Service (ADS).
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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The Climate Change Centre Austria - Data Centre provides the central national archive for climate data and information. The data made accessible includes observation and measurement data, scenario data, quantitative and qualitative data, as well as the measurement data and findings of research projects.
Ag Data Commons provides access to a wide variety of open data relevant to agricultural research. We are a centralized repository for data already on the web, as well as for new data being published for the first time. While compliance with the U.S. Federal public access and open data directives is important, we aim to surpass them. Our goal is to foster innovative data re-use, integration, and visualization to support bigger, better science and policy.
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Macromolecular Xtallography Raw Data Repository (MX-RDR) is a domain-specific digital repository of crystallographic open research data. The use of Repository is open for everyone.
GNPS is a web-based mass spectrometry ecosystem that aims to be an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. GNPS aids in identification and discovery throughout the entire life cycle of data; from initial data acquisition/analysis to post publication.
Launched in December 2013, Gaia is destined to create the most accurate map yet of the Milky Way. By making accurate measurements of the positions and motions of stars in the Milky Way, it will answer questions about the origin and evolution of our home galaxy. The first data release (2016) contains three-dimensional positions and two-dimensional motions of a subset of two million stars. The second data release (2018) increases that number to over 1.6 Billion. Gaia’s measurements are as precise as planned, paving the way to a better understanding of our galaxy and its neighborhood. The AIP hosts the Gaia data as one of the external data centers along with the main Gaia archive maintained by ESAC and provides access to the Gaia data releases as part of Gaia Data Processing and Analysis Consortium (DPAC).
<<<!!!<<< This repository is no longer available. >>>!!!>>>The Deep Carbon Observatory (DCO) is a global community of multi-disciplinary scientists unlocking the inner secrets of Earth through investigations into life, energy, and the fundamentally unique chemistry of carbon. Deep Carbon Observatory Digital Object Registry (“DCO-VIVO”) is a centrally-managed digital object identification, object registration and metadata management service for the DCO. Digital object registration includes DCO-ID generation based on the global Handle System infrastructure and metadata collection using VIVO. Users will be able to deposit their data into the DCO Data Repository and have that data discoverable and accessible by others.