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Found 49 result(s)

Global Biodiversity Information Facility

Data index of the Global Biodiversity Information Facility

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GBIF is an international organisation that is working to make the world's biodiversity data accessible everywhere in the world. GBIF and its many partners work to mobilize the data, and to improve search mechanisms, data and metadata standards, web services, and the other components of an Internet-based information infrastructure for biodiversity. GBIF makes available data that are shared by hundreds of data publishers from around the world. These data are shared according to the GBIF Data Use Agreement, which includes the provision that users of any data accessed through or retrieved via the GBIF Portal will always give credit to the original data publishers.

MUSE-Wide

MUSE-Wide archive

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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.

HepSim

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HepSim is a public repository with Monte Carlo simulations for particle-collision experiments. It contains predictions from leading-order (LO) parton shower models, next-to-leading order (NLO) and NLO with matched parton showers. It also includes Monte Carlo events after fast ("parametric") and full (Geant4) detector simulations and event reconstruction.

opendata@uni-kiel

Forschungsdatenrepositorium der CAU

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opendata@uni-kiel is the open research data repository of Kiel University for FAIR data.

ENCODE

Encyclopedia of DNA Elements

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The ENCODE Encyclopedia organizes the most salient analysis products into annotations, and provides tools to search and visualize them. The Encyclopedia has two levels of annotations: Integrative-level annotations integrate multiple types of experimental data and ground level annotations. Ground-level annotations are derived directly from the experimental data, typically produced by uniform processing pipelines.

University of Hertfordshire Research Archive

UHRA

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University repository containing publication data and datasets.

PRISM Dataverse

University of Calgary Data Repository

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PRISM Dataverse is the institutional data repository of the University of Calgary, which has its purpose in digital archiving and sharing of research data from researchers. PRISM Dataverse is a data repository hosted through Borealis, a service of the Ontario Council of University Libraries and supported by University of Calgary's Libraries and Cultural Resources. PRISM Dataverse enables scholars to easily deposit data, create data-specific metadata for searchability and publish their datasets.

Open Forest Data

e-Puszcza

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Podlasie digital repository of natural science data

Inspire-HEP

Inspire-High Energy Physics

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CERN, DESY, Fermilab and SLAC have built the next-generation High Energy Physics (HEP) information system, INSPIRE. It combines the successful SPIRES database content, curated at DESY, Fermilab and SLAC, with the Invenio digital library technology developed at CERN. INSPIRE is run by a collaboration of CERN, DESY, Fermilab, IHEP, IN2P3 and SLAC, and interacts closely with HEP publishers, arXiv.org, NASA-ADS, PDG, HEPDATA and other information resources. INSPIRE represents a natural evolution of scholarly communication, built on successful community-based information systems, and provides a vision for information management in other fields of science.

NeuroVault

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A place where researchers can publicly store and share unthresholded statistical maps, parcellations, and atlases produced by MRI and PET studies.

B2SHARE Server Forschungszentrum Jülich

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B2SHARE allows publishing research data and belonging metadata. It supports different research communities with specific metadata schemas. This server is provided for researchers of the Research Centre Juelich and related communities.

ScienceDB

Science Data Bank

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Science Data Bank is an open generalist data repository developed and maintained by the Chinese Academy of Sciences Computing and Network Information Center (CNIC). It promotes the publication and reuse of scientific data. Researchers and journal publishers can use it to store, manage and share science data.

DataverseNO

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DataverseNO (https://dataverse.no) is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.

RODARE

Rossendorf Data Repository

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Rodare is the institutional research data repository at HZDR (Helmholtz-Zentrum Dresden-Rossendorf). Rodare allows HZDR researchers to upload their research software and data and enrich those with metadata to make them findable, accessible, interoperable and retrievable (FAIR). By publishing all associated research software and data via Rodare research reproducibility can be improved. Uploads receive a Digital Object Identfier (DOI) and can be harvested via a OAI-PMH interface.

University of Warsaw Research Data Repository

Dane Badawcze Uniwersytetu Warszawskiego. Repozytorium

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University of Warsaw Research Data Repository aims to collect, archive, preserve and make available all types of research data. Storing and making data available is possible for users affiliated with the University of Warsaw, Poland, or those involved in projects carried out in partnership with the University of Warsaw. Browsing and downloading publicly available research data is open to all interested.

Research Data Unipd

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Research Data Unipd is a data archive and supports research produced by the members of the University of Padova. The service aims to facilitate data discovery, data sharing, and reuse, as required by funding institutions (eg. European Commission). Datasets published in the archive have a set of metadata that ensure proper description and discoverability.

Jülich DATA

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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.

WikiPathways

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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.

KNMI Data Platform

formerly: KDC

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KDP has replaced the KNMI Data Centre (KDC), which was turned off on the 27th of July 2020. Not only a change of name, but also a transition to new technologies. Initially, the KDP will be more primitive than KDC. To fulfill future ambitions, a digital KNMI transformation has been initiated. Part of this transition is the development of a new KDP as a successor of the KDC. All data on the KNMI Data Platform is free to use. For some datasets a service agreement is available, which is indicated on the page of the dataset. The KNMI Data platform provides access to KNMI data on weather, climate and seismology. Here you will find KNMI data on various subjects such as the most recent 10-minute observations, historical series, data about meteorological measuring stations, model calculations, earthquake data and satellite products. In addition to KNMI datasets, we also make datasets from other parties available, such as ECMWF, ECOMET, EUMETSAT and WMO.

TemplateFlow

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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.

depositar

研究資料寄存所

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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.

MIDAS

Nacionalinis atviros prieigos mokslinių tyrimų duomenų archyvas

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MIDAS is a national research data repository. The aim of MIDAS is to collect, process, store and analyse research data and other relevant information in all fields of knowledge, enabling free, easy and convenient access to the data via the Internet. MIDAS provides services for registered and unregistered users: students, listeners, academics, researchers, scientists, research administrators, other actors of the research and studies ecosystem, and all individuals interested in research data. MIDAS consists of the MIDAS portal and MIDAS user account. The MIDAS portal is a public space accessible to anyone interested in discovering and viewing published research Data and their metadata, whereas MIDAS user account is available to registered users only. MIDAS is managed by Vilnius University.

ESS-DIVE

formerly: CDIAC

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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.

RADAR4Culture

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RADAR4Culture is a low-threshold and easy-to use service for sustainable publication and preservation of cultural heritage research data. It offers free publication for any data type and format according to the FAIR principles, independent of the researcher´s institutional affiliation. Through persistent identifiers (DOI) and a guaranteed retention period of at least 25 years, the research data remain available, citable and findable long-term. Currently, the offer is aimed exclusively at researchers at publicly funded research institutions and (art) universities as well as non-commercial academies, galleries, libraries, archives and museums in Germany. No contract is required and no data publication fees are charged. The researchers are responsible for the upload, organisation, annotation and curation of research data as well as the peer-review process (as an optional step) and finally their publication.

BioModels

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BioModels is a repository of mathematical models of biological and biomedical systems. It hosts a vast selection of existing literature-based physiologically and pharmaceutically relevant mechanistic models in standard formats. Our mission is to provide the systems modelling community with reproducible, high-quality, freely-accessible models published in the scientific literature.