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Found 19 result(s)
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.
ResearchWorks Archive is the University of Washington’s digital repository (also known as “institutional repository”) for disseminating and preserving scholarly work. ResearchWorks Archive can accept any digital file format or content (examples include numerical datasets, photographs and diagrams, working papers, technical reports, pre-prints and post-prints of published articles).
The Purdue University Research Repository (PURR) provides a virtual research environment and data publication and archiving platform for its campuses. Also supports the publication and online execution of software tools with DataCite DOIs.
The AOML Environmental Data Server (ENVIDS) provides interactive, on-line access to various oceanographic and atmospheric datasets residing at AOML. The in-house datasets include Atlantic Expendable Bathythermograph (XBT), Global Lagrangian Drifting Buoy, Hurricane Flight Level, and Atlantic Hurricane Tracks (North Atlantic Best Track and Synoptic). Other available datasets include Pacific Conductivitiy/Temperature/Depth Recorder (CTD) and World Ocean Atlas 1998.
A data repository and social network so that researchers can interact and collaborate, also offers tutorials and datasets for data science learning. "data.world is designed for data and the people who work with data. From professional projects to open data, data.world helps you host and share your data, collaborate with your team, and capture context and conclusions as you work."
Kaggle is a platform for predictive modelling and analytics competitions in which statisticians and data miners compete to produce the best models for predicting and describing the datasets uploaded by companies and users. This crowdsourcing approach relies on the fact that there are countless strategies that can be applied to any predictive modelling task and it is impossible to know beforehand which technique or analyst will be most effective.
The USGS Alaska Region has the largest geographic extent of the seven regional units within the USGS and represents a dynamic landscape of great natural wonder. It is a transforming landscape shaped by volcanoes, earthquakes, major rivers, and glaciers and a strategic landscape of yet untapped mineral and energy resources. The Region conducts research to help inform management of the extensive national parks and wildlife refuges of the far north and the international birds, fish, and marine mammals that migrate to these lands and waters; informs national Arctic energy policy through research on the National Petroleum Reserve-Alaska and the U.S. Outer Continental Shelf; and provides science to understand, help respond to and mitigate impacts from natural hazards. This work is accomplished in part by the Region's two Science Centers headquartered in Anchorage, the Alaska Science Center and the Volcano Science Center.
Welcome to Smithsonian Open Access, where you can download, share, and reuse millions of the Smithsonian’s images—right now, without asking. With new platforms and tools, you have easier access to nearly 3 million 2D and 3D digital items from our collections—with many more to come. This includes images and data from across the Smithsonian’s 19 museums, nine research centers, libraries, archives, and the National Zoo.
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Dataverse UNIMI is the institutional data repository of the University of Milan. The service aims at facilitating 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.
Using a combination of remote sensing data and ground observations as inputs, CHC scientists have developed rainfall estimation techniques and other resources to support drought monitoring and predict crop performance in parts of the world vulnerable to crop failure. Policymakers within governments and non-governmental organizations rely on CHC decision-support products to make critical resource allocation decisions. The CHC's scientific focus is "geospatial hydroclimatology," with an emphasis on the early detection and forecasting of hydroclimatic hazards related to food-security droughts and floods. Basic research seeks an improved understanding of the climatic processes that govern drought and flood hazards in FEWS NET countries (https://fews.net/). The CHC develops better techniques, algorithms, and modeling applications in order to use remote sensing and other geospatial data for hazards early warning.
The George Mason University Dataverse is available for George Mason faculty, staff, and students to publish, share, and preserve their research data of enduring value. It is a companion to the Mason Archival Repository Service (https://mars.gmu.edu).
Country
The University of Lodz Repository is an institutional repository whose purpose is to disseminate the scholarly output of its staff and promote research conducted at the UL. It is an archive of its own electronic documents – each deposited publication or collection of research data is given a permanent identifier (handle), enabling the document to be cited and indexed in scientific databases. The University of Lodz Repository operates as an institutional repository based on Regulation No. 51 of the Rector of the University of Lodz of 31 March 2015.
<<<!!!<<< Stated 2019-10-30: Dash is no longer available. Researchers are advised to store their research data at Dryad https://www.re3data.org/repository/r3d100000044 >>>!!!>>> Dash is an open data publication platform for upload, access, and re-use of research data. Submissions to Dash may be from researchers at participating UC campuses, researchers in earth science and ecology (DataONE), and researchers submitting to the UC Press journals Elementa and Collabra. Self-service depositing of research data through Dash fulfills publisher, funder, and data management plan requirements regarding data sharing and preservation. When researchers publish their datasets through Dash, their datasets are issued a DOI (DataCite) to optimize citability, and are publicly available for download and re-use under a CC BY 4.0 or CC-0 license. Deposited data are preserved in Merritt, California Digital Library’s preservation repository.
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).