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Found 25 result(s)
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.
IsoArcH is an open access isotope web-database for bioarchaeological samples from prehistoric and historical periods all over the world. With 40,000+ isotope related data obtained on 13,000+ specimens (i.e., humans, animals, plants and organic residues) coming from 500+ archaeological sites, IsoArcH is now one of the world's largest repositories for isotopic data and metadata deriving from archaeological contexts. IsoArcH allows to initiate big data initiatives but also highlights research lacks in certain regions or time periods. Among others, it supports the creation of sound baselines, the undertaking of multi-scale analysis, and the realization of extensive studies and syntheses on various research issues such as paleodiet, food production, resource management, migrations, paleoclimate and paleoenvironmental changes.
The figshare service for the University of Sheffield allows researchers to store, share and publish research data. It helps the research data to be accessible by storing Metadata alongside datasets. Additionally, every uploaded item receives a Digital Object identifier (DOI), which allows the data to be citable and sustainable. If there are any ethical or copyright concerns about publishing a certain dataset, it is possible to publish the metadata associated with the dataset to help discoverability while sharing the data itself via a private channel through manual approval.
Content type(s)
The IDR makes datasets that have never previously been accessible publicly available, allowing the community to search, view, mine and even process and analyze large, complex, multidimensional life sciences image data. Sharing data promotes the validation of experimental methods and scientific conclusions, the comparison with new data obtained by the global scientific community, and enables data reuse by developers of new analysis and processing tools.
The Biodiversity Research Program (PPBio) was created in 2004 with the aims of furthering biodiversity studies in Brazil, decentralizing scientific production from already-developed academic centers, integrating research activities and disseminating results across a variety of purposes, including environmental management and education. PPBio contributes its data to the DataONE network as a member node: https://search.dataone.org/#profile/PPBIO
The Bavarian Natural History Collections (Staatliche Naturwissenschaftliche Sammlungen Bayerns, SNSB) are a research institution for natural history in Bavaria. They encompass five State Collections (zoology, botany, paleontology and geology, mineralogy, anthropology and paleoanatomy), the Botanical Garden Munich-Nymphenburg and eight museums with public exhibitions in Munich, Bamberg, Bayreuth, Eichstätt and Nördlingen. Our research focuses mainly on the past and present bio- and geodiversity and the evolution of animals and plants. To achieve this we have large scientific collections (almost 35,000,000 specimens), see "joint projects".
SHARE - Stations at High Altitude for Research on the Environment - is an integrated Project for environmental monitoring and research in the mountain areas of Europe, Asia, Africa and South America responding to the call for improving environmental research and policies for adaptation to the effects of climate changes, as requested by International and Intergovernmental institutions.
ReefTEMPS is a temperature, pressure, salinity and other observables sensor network in coastal area of South, West and South West of Pacific ocean, driven by UMR ENTROPIE. It is an observatory service from the French national research infrastructure ILICO for “coastal environments”. Some of the network’s sensors have been deployed since 1958. Nearly hundred sensors are actually deployed in 14 countries covering an area of more than 8000 km from East to West. The data are acquired at different rates (from 1sec to 30 mn) depending on sensors and sites. They are processed and described using Climate and Forecast Metadata Convention at the end of oceanographic campaigns organized for sensors replacement every 6 months to 2 years.
The mission of World Data Center for Climate (WDCC) is to provide central support for the German and European climate research community. The WDCC is member of the ISC's World Data System. Emphasis is on development and implementation of best practice methods for Earth System data management. Data for and from climate research are collected, stored and disseminated. The WDCC is restricted to data products. Cooperations exist with thematically corresponding data centres of, e.g., earth observation, meteorology, oceanography, paleo climate and environmental sciences. The services of WDCC are also available to external users at cost price. A special service for the direct integration of research data in scientific publications has been developed. The editorial process at WDCC ensures the quality of metadata and research data in collaboration with the data producers. A citation code and a digital identifier (DOI) are provided and registered together with citation information at the DOI registration agency DataCite.
The Analytical Geomagnetic Data Center of the Trans-Regional INTERMAGNET Segment is operated by the Geophysical Center of the Russian Academy of Sciences (GC RAS). Geomagnetic data are transmitted from observatories and stations located in Russia and near-abroad countries. The Center also provides access to spaceborne data products. The MAGNUS hardware-software system underlies the operation of the Center. Its particular feature is the automated real-time recognition of artificial (anthropogenic) disturbances in incoming data. Being based on fuzzy logic approach, this quality control service facilitates the preparation of the definitive magnetograms from preliminary records carried out by data experts manually. The MAGNUS system also performs on-the-fly multi-criteria estimation of geomagnetic activity using several indicators and provides online tools for modeling electromagnetic parameters in the near-Earth space. The collected geomagnetic data are stored using relational database management system. The geomagnetic database is intended for storing both 1-minute and 1-second data. The results of anthropogenic and natural disturbance recognition are also stored in the database.
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
The FigShare service for University of Auckland, New Zealand was launched in January 2015 and allows researchers to store, share and publish research data. It helps the research data to be accessible by storing Metadata alongside datasets. Additionally, every uploaded item recieves a Digital Object identifier (DOI), which allows the data to be cited. If there are any ethical or copyright concerns about publishing a certain dataset, it is possible to publish the metadata associated with the dataset to help discoverability while sharing the data itself via a private channel through manual approval.
Provided by the University Libraries, KiltHub is the comprehensive institutional repository and research collaboration platform for research data and scholarly outputs produced by members of Carnegie Mellon University and their collaborators. KiltHub collects, preserves, and provides stable, long-term global open access to a wide range of research data and scholarly outputs created by faculty, staff, and student members of Carnegie Mellon University in the course of their research and teaching.
The aim of the Freshwater Biodiversity Data Portal is to integrate and provide open and free access to freshwater biodiversity data from all possible sources. To this end, we offer tools and support for scientists interested in documenting/advertising their dataset in the metadatabase, in submitting or publishing their primary biodiversity data (i.e. species occurrence records) or having their dataset linked to the Freshwater Biodiversity Data Portal. This information portal serves as a data discovery tool, and allows scientists and managers to complement, integrate, and analyse distribution data to elucidate patterns in freshwater biodiversity. The Freshwater Biodiversity Data Portal was initiated under the EU FP7 BioFresh project and continued through the Freshwater Information Platform (http://www.freshwaterplatform.eu). To ensure the broad availability of biodiversity data and integration in the global GBIF index, we strongly encourages scientists to submit any primary biodiversity data published in a scientific paper to national nodes of GBIF or to thematic initiatives such as the Freshwater Biodiversity Data Portal.
The NDEx Project provides an open-source framework where scientists and organizations can share, store, manipulate, and publish biological network knowledge. The NDEx Project maintains a free, public website; alternatively, users can also decide to run their own copies of the NDEx Server software in cases where the stored networks must be kept in a highly secure environment (such as for HIPAA compliance) or where high application load is incompatible with a shared public resource.
CORD is Cranfield University's research data repository, for secure preservation of institutional research data outputs. Cranfield is an exclusively postgraduate university that is a global leader for transformational research in technology and management. We are focused on the specialist themes of aerospace, defence and security, energy and power, environment and agrifood, manufacturing, transport systems, and water. The Cranfield School of Management is world leader in management education and research.
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.
figshare allows researchers to publish all of their research outputs in an easily citable, sharable and discoverable manner. All file formats can be published, including videos and datasets. Optional peer review process. figshare uses creative commons licensing. figshare+ repository allows figshare users to share larger datasets, over 20GB up to many TBs, see: https://plus.figshare.com/