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Found 24 result(s)
The Digital Archaeological Record (tDAR) is an international digital repository for the digital records of archaeological investigations. tDAR’s use, development, and maintenance are governed by Digital Antiquity, an organization dedicated to ensuring the long-term preservation of irreplaceable archaeological data and to broadening the access to these data.
The Magnetics Information Consortium (MagIC) improves research capacity in the Earth and Ocean sciences by maintaining an open community digital data archive for rock magnetic, geomagnetic, archeomagnetic (archaeomagnetic) and paleomagnetic (palaeomagnetic) data. Different parts of the website allow users access to archive, search, visualize, and download these data. MagIC supports the international rock magnetism, geomagnetism, archeomagnetism (archaeomagnetism), and paleomagnetism (palaeomagnetism) research and endeavors to bring data out of private archives, making them accessible to all and (re-)useable for new, creative, collaborative scientific and educational activities. The data in MagIC is used for many types of studies including tectonic plate reconstructions, geomagnetic field models, paleomagnetic field reversal studies, magnetohydrodynamical studies of the Earth's core, magnetostratigraphy, and archeology. MagIC is a domain-specific data repository and directed by PIs who are both producers and consumers of rock, geo, and paleomagnetic data. Funded by NSF since 2003, MagIC forms a major part of https://earthref.org which integrates four independent cyber-initiatives rooted in various parts of the Earth, Ocean and Life sciences and education.
<<<!!!<<< As stated 2017-08-28 NEEShub is no longer available. The NEES published projects from the Project Warehouse can be found in the DesignSafe Data Depot https://www.designsafe-ci.org/data/browser/public/nees.public/. The NEES Databases https://datacenterhub.org/resources/395 are being transitioned to DataHub https://datacenterhub.org/ . Please visit DesignSafe https://www.designsafe-ci.org/ for all other inquiries. >>>!!!<<< NEES network features 14 geographically-distributed, shared-use laboratories that support several types of experimental work: geotechnical centrifuge research, shake table tests, large-scale structural testing, tsunami wave basin experiments, and field site research >>>!!!>>>
PQR is an online database of molecular properties predicted from quantum mechanics with integrated capabilities for molecular visualization and data sharing. ased on the number of molecules, PQR is currently the largest open database of molecular quantum calculations. PQR features interactive high-quality rendering of molecular structures and properties on computers, tablets, and cell phones and allows to efficiently share data via digital object identifiers (DOI) and scannable QR barcodes.
Research data from University of Pretoria. This data repository facilitates data publishing, sharing and collaboration of academic research, allowing UP to manage and in some cases showcase its data to the wider research community. Previously UPSpace (https://repository.up.ac.za/) was used for both datasets and research outputs. Now UP Research Data Repository is dedicated for datasets.
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.
Country
Australian Ocean Data Network (AODN) provides data collected by the Australian marine community. AODN's data is searchable via map interface and metadata catalogue. AODN is Australia's exhaustive repository for marine and climate data. AODN has merged with IMOS eMarine Information Infrastructure (eMII) Facility in May 2016. IMOS is a multi-institutional collaboration with a focus on open data access. It is ideally placed to manage the AODN on behalf of the Australian marine and climate community.
Country
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 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.
Data Observation Network for Earth (DataONE) is the foundation of new innovative environmental science through a distributed framework and sustainable cyberinfrastructure that meets the needs of science and society for open, persistent, robust, and secure access to well-described and easily discovered Earth observational data. Supported by the U.S. National Science Foundation (Grant #OCI-0830944) as one of the initial DataNets, DataONE will ensure the preservation, access, use and reuse of multi-scale, multi-discipline, and multi-national science data via three primary cyberinfrastucture elements and a broad education and outreach program.
Yoda is a research data management service that enables researchers to deposit, share, publish and preserve large amounts of research data during all stages of a research project. This service is managed and supported by an interdisciplinary team of university employees. The software has been developed at Utrecht University and is used by multiple organisations, both in the Netherlands and abroad. Yoda publishes data packages via Datacite. To find data publications use: https://public.yoda.uu.nl/, or the Datacite search engine: https://commons.datacite.org/doi.org?query=client.uid:delft.uu
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.
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.
Biological collections are replete with taxonomic, geographic, temporal, numerical, and historical information. This information is crucial for understanding and properly managing biodiversity and ecosystems, but is often difficult to access. Canadensys, operated from the Université de Montréal Biodiversity Centre, is a Canada-wide effort to unlock the biodiversity information held in biological collections.
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.
Country
The interdisciplinary data platform INPTDAT provides easy access to research data and information from all fields of applied plasma physics and plasma medicine. It aims to support the findability, accessibility, interoperability and re-use of data for the low-temperature plasma physics community.
The CERN Open Data portal is the access point to a growing range of data produced through the research performed at CERN. It disseminates the preserved output from various research activities, including accompanying software and documentation which is needed to understand and analyze the data being shared.
ZENODO builds and operates a simple and innovative service that enables researchers, scientists, EU projects and institutions to share and showcase multidisciplinary research results (data and publications) that are not part of the existing institutional or subject-based repositories of the research communities. ZENODO enables researchers, scientists, EU projects and institutions to: easily share the long tail of small research results in a wide variety of formats including text, spreadsheets, audio, video, and images across all fields of science. display their research results and get credited by making the research results citable and integrate them into existing reporting lines to funding agencies like the European Commission. easily access and reuse shared research results.
The Stanford Digital Repository (SDR) is Stanford Libraries' digital preservation system. The core repository provides “back-office” preservation services – data replication, auditing, media migration, and retrieval -- in a secure, sustainable, scalable stewardship environment. Scholars and researchers across disciplines at Stanford use SDR repository services to provide ongoing, persistent, reliable access to their research outputs.
The Arctic Data Center is the primary data and software repository for the Arctic section of NSF Polar Programs. The Center helps the research community to reproducibly preserve and discover all products of NSF-funded research in the Arctic, including data, metadata, software, documents, and provenance that links these together. The repository is open to contributions from NSF Arctic investigators, and data are released under an open license (CC-BY, CC0, depending on the choice of the contributor). All science, engineering, and education research supported by the NSF Arctic research program are included, such as Natural Sciences (Geoscience, Earth Science, Oceanography, Ecology, Atmospheric Science, Biology, etc.) and Social Sciences (Archeology, Anthropology, Social Science, etc.). Key to the initiative is the partnership between NCEAS at UC Santa Barbara, DataONE, and NOAA’s NCEI, each of which bring critical capabilities to the Center. Infrastructure from the successful NSF-sponsored DataONE federation of data repositories enables data replication to NCEI, providing both offsite and institutional diversity that are critical to long term preservation.
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).