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Found 22 result(s)
The tree of life links all biodiversity through a shared evolutionary history. This project will produce the first online, comprehensive first-draft tree of all 1.8 million named species, accessible to both the public and scientific communities. Assembly of the tree will incorporate previously-published results, with strong collaborations between computational and empirical biologists to develop, test and improve methods of data synthesis. This initial tree of life will not be static; instead, we will develop tools for scientists to update and revise the tree as new data come in. Early release of the tree and tools will motivate data sharing and facilitate ongoing synthesis of knowledge.
<<<!!!<<< This repository is no longer available. >>>!!!>>> The programme "International Oceanographic Data and Information Exchange" (IODE) of the "Intergovernmental Oceanographic Commission" (IOC) of UNESCO was established in 1961. Its purpose is to enhance marine research, exploitation and development, by facilitating the exchange of oceanographic data and information between participating Member States, and by meeting the needs of users for data and information products.
The EUROLAS Data Center (EDC) is one of the two data centers of the International Laser Ranging Service (ILRS). It collects, archives and distributes tracking data, predictions and other tracking relevant information from the global SLR network. Additionally EDC holds a mirror of the official Web-Pages of the ILRS at Goddard Space Flight Center (GSFC). And as result of the activities of the Analysis Working Group (AWG) of the ILRS, DGFI has been selected as analysis centers (AC) and as backup combination center (CC). This task includes weekly processing of SLR observations to LAGEOS-1/2 and ETALON-1/2 to compute station coordinates and earth orientation parameters. Additionally the combination of SLR solutions from the various analysis centres to a combinerd ILRS SLR solution.
Galaxies, made up of billions of stars like our Sun, are the beacons that light up the structure of even the most distant regions in space. Not all galaxies are alike, however. They come in very different shapes and have very different properties; they may be large or small, old or young, red or blue, regular or confused, luminous or faint, dusty or gas-poor, rotating or static, round or disky, and they live either in splendid isolation or in clusters. In other words, the universe contains a very colourful and diverse zoo of galaxies. For almost a century, astronomers have been discussing how galaxies should be classified and how they relate to each other in an attempt to attack the big question of how galaxies form. Galaxy Zoo (Lintott et al. 2008, 2011) pioneered a novel method for performing large-scale visual classifications of survey datasets. This webpage allows anyone to download the resulting GZ classifications of galaxies in the project.
coastDat is a model based data bank developed mainly for the assessment of long-term changes in data sparse regions. A sequence of numerical models is employed to reconstruct all aspects of marine climate (such as storms, waves, surges etc.) over many decades of years relying only on large-scale information such as large-scale atmospheric conditions or bathymetry.
University of Alberta Dataverse is a service provided by the University of Albert Library to help researchers publish, analyze, distribute, and preserve data and datasets. Open for University of Alberta-affiliated researchers to deposit data.
WDC for STP, Moscow collects, stores, exchanges with other WDCs, disseminates the publications, sends upon requests data on the following Solar-Terrestrial Physics disciplines: Solar Activity and Interplanetary Medium, Cosmic Rays, Ionospheric Phenomena, Geomagnetic Variations.
The Australian National University undertake work to collect and publish metadata about research data held by ANU, and in the case of four discipline areas, Earth Sciences, Astronomy, Phenomics and Digital Humanities to develop pipelines and tools to enable the publication of research data using a common and repeatable approach. Aims and outcomes: To identify and describe research data held at ANU, to develop a consistent approach to the publication of metadata on the University's data holdings: Identification and curation of significant orphan data sets that might otherwise be lost or inadvertently destroyed, to develop a culture of data data sharing and data re-use.
EartH2Observe brings together the findings from European FP projects DEWFORA, GLOWASIS, WATCH, GEOWOW and others. It will integrate available global earth observations (EO), in-situ datasets and models and will construct a global water resources re-analysis dataset of significant length (several decades). The resulting data will allow for improved insights on the full extent of available water and existing pressures on global water resources in all parts of the water cycle. The project will support efficient and globally consistent water management and decision making by providing comprehensive multi-scale (regional, continental and global) water resources observations. It will test new EO data sources, extend existing processing algorithms and combine data from multiple satellite missions in order to improve the overall resolution and reliability of EO data included in the re-analysis dataset. The resulting datasets will be made available through an open Water Cycle Integrator data portal https://wci.earth2observe.eu/ : the European contribution to the GEOSS/WCI approach. The datasets will be downscaled for application in case-studies at regional and local levels, and optimized based on identified European and local needs supporting water management and decision making . Actual data access: https://wci.earth2observe.eu/data/group/earth2observe
EMSC collects real time parametric data (source parmaters and phase pickings) provided by 65 seismological networks of the Euro-Med region. These data are provided to the EMSC either by email or via QWIDS (Quake Watch Information Distribution System, developped by ISTI). The collected data are automatically archived in a database, made available via an autoDRM, and displayed on the web site. The collected data are automatically merged to produce automatic locations which are sent to several seismological institutes in order to perform quick moment tensors determination.
The Abacus Data Network is a data repository collaboration involving Libraries at Simon Fraser University (SFU), the University of British Columbia (UBC), the University of Northern British Columbia (UNBC) and the University of Victoria (UVic).
Forestry Images provides an accessible and easy to use archive of high quality images related to forest health and silviculture
Nuclear Data Services contains atomic, molecular and nuclear data sets for the development and maintenance of nuclear technologies. It includes energy-dependent reaction probabilities (cross sections), the energy and angular distributions of reaction products for many combinations of target and projectile, and the atomic and nuclear properties of excited states, and their radioactive decay data. Their main concern is providing data required to design a modern nuclear reactor for electricity production. Approximately 11.5 million nuclear data points have been measured and compiled into computerized form.
The Social Science Data Archive is still active and maintained as part of the UCLA Library Data Science Center. SSDA Dataverse is one of the archiving opportunities of SSDA, the others are: Data can be archived by SSDA itself or by ICPSR or by UCLA Library or by California Digital Library. The Social Science Data Archives serves the UCLA campus as an archive of faculty and graduate student survey research. We provide long term storage of data files and documentation. We ensure that the data are useable in the future by migrating files to new operating systems. We follow government standards and archival best practices. The mission of the Social Science Data Archive has been and continues to be to provide a foundation for social science research with faculty support throughout an entire research project involving original data collection or the reuse of publicly available studies. Data Archive staff and researchers work as partners throughout all stages of the research process, beginning when a hypothesis or area of study is being developed, during grant and funding activities, while data collection and/or analysis is ongoing, and finally in long term preservation of research results. Our role is to provide a collaborative environment where the focus is on understanding the nature and scope of research approach and management of research output throughout the entire life cycle of the project. Instructional support, especially support that links research with instruction is also a mainstay of operations.
The International Food Policy Research Institute (IFPRI) seeks sustainable solutions for ending hunger and poverty. In collaboration with institutions throughout the world, IFPRI is often involved in the collection of primary data and the compilation and processing of secondary data. The resulting datasets provide a wealth of information at the local (household and community), national, and global levels. IFPRI freely distributes as many of these datasets as possible and encourages their use in research and policy analysis. IFPRI Dataverse contains following dataverses: Agricultural Science and Knowledge Indicators - ASTI, HarvestChoice, Statistics on Public Expenditures for Economic Development - SPEED, International Model for Policy Analysis of Agricultural Commodities and Trade - IMPACT, Africa RISING Dataverse and Food Security Portal Dataverse.
The GTN-P database is an object-related database open for a diverse range of data. Because of the complexity of the PAGE21 project, data provided in the GTN-P management system are extremely diverse, ranging from active-layer thickness measurements once per year to flux measurement every second and everthing else in between. The data can be assigned to two broad categories: Quantitative data which is all data that can be measured numerically. Quantitative data comprise all in situ measurements, i.e. permafrost temperatures and active layer thickness (mechanical probing, frost/thaw tubes, soil temperature profiles). Qualitative data (knowledge products) are observations not based on measurements, such as observations on soils, vegetation, relief, etc.