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Found 78 result(s)
The International Service of Geomagnetic Indices (ISGI) is in charge of the elaboration and dissemination of geomagnetic indices, and of tables of remarkable magnetic events, based on the report of magnetic observatories distributed all over the planet, with the help of ISGI Collaborating Institutes. The interaction between the solar wind, including plasma and interplanetary magnetic field, and the Earth's magnetosphere results in a transfer of energy and particles inside the magnetosphere. Solar wind characteristics are highly variable, and they have actually a direct influence on the shape and size of the magnetosphere, on the amount of transferred energy, and on the way this energy is dissipated. It is clear that the great diversity of sources of magnetic variations give rise to a great complexity in ground magnetic signatures. Geomagnetic indices aim at describing the geomagnetic activity or some of its components. Each geomagnetic index is related to different phenomena occurring in the magnetosphere, ionosphere and deep in the Earth in its own unique way. The location of a measurement, the timing of the measurement and the way the index is calculated all affect the type of phenomenon the index relates to. The IAGA endorsed geomagnetic indices and lists of remarkable geomagnetic events constitute unique temporal and spatial coverage data series homogeneous since middle of 19th century.
The Carleton University Data Repository Dataverse is the research data repository for Carleton University. It is managed by the Data Services in the MacOdrum Library. The repository also houses the MacOdrum Library Dataverse Collection which contains numerous public opinion polls.
The Tropospheric Ozone Assessment Report (TOAR) database of global surface observations is the world's most extensive collection of surface ozone measurements and includes also data on other air pollutants and on weather for some regions. Measurements from 1970 to 2019 (Version 1) have been collected in a relational database, and are made available via a graphical web interface, a REST service (https://toar-data.fz-juelich.de/api/v1) and as aggregated products on PANGAEA (https://doi.pangaea.de/10.1594/PANGAEA.876108). Measurements from 1970 to present (Version 2) are being collected in a relational database, and are made available via a REST service (https://toar-data.fz-juelich.de/api/v2).
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.
VAMDC aims to be an interoperable e-infrastructure that provides the international research community with access to a broad range of atomic and molecular (A&M) data compiled within a set of A&M databases accessible through the provision of this portal and of user software. Furthermore VAMDC aims to provide A&M data providers and compilers with a large dissemination platform for their work. VAMDC infrastructure was established to provide a service to a wide international research community and has been developed in conjunction with consultations and advice from the A&M user community.
Data deposit is supported for University of Ottawa faculty, students, and affiliated researchers. The repository is multidisciplinary and hosted on Canadian servers. It includes features such as permanent links (DOIs) which encourage citation of your dataset and help you set terms for access and reuse of your data. uOttawa Dataverse is currently optimal for small to medium datasets.
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.
The ACSS Dataverse is a repository of interdisciplinary social science research data produced in and on the Arab region. The ACSS Dataverse, part of an initiative of the Arab Council for the Social Sciences in collaboration with the Odum Institute for Research in Social Science at the University of North Carolina at Chapel Hill, preserves and facilitates access to social science datasets in and on the Arab region and is open to relevant research data deposits.
UniProtKB/Swiss-Prot is the manually annotated and reviewed section of the UniProt Knowledgebase (UniProtKB). It is a high quality annotated and non-redundant protein sequence database, which brings together experimental results, computed features and scientific conclusions. Since 2002, it is maintained by the UniProt consortium and is accessible via the UniProt website.
IntAct provides a freely available, open source database system and analysis tools for molecular interaction data. All interactions are derived from literature curation or direct user submissions and are freely available.
The US Virtual Astronomical Observatory (VAO) is the VO effort based in the US, and it is one of many VO projects currently underway worldwide. The primary emphasis of the VAO is to provide new scientific research capabilities to the astronomy community. Thus an essential component of the VAO activity is obtaining input from US astronomers about the research tools that are most urgently needed in their work, and this information will guide the development efforts of the VAO. >>>!!!<<< Funding discontinued in 2014 and all software, documentation, and other digital assets developed under the VAO are stored in the VAO Project Repository https://sites.google.com/site/usvirtualobservatory/ . Code is archived on Github https://github.com/TomMcGlynn/usvirtualobservatory . >>>!!!<<<
The DIP database catalogs experimentally determined interactions between proteins. It combines information from a variety of sources to create a single, consistent set of protein-protein interactions. The data stored within the DIP database were curated, both, manually by expert curators and also automatically using computational approaches that utilize the the knowledge about the protein-protein interaction networks extracted from the most reliable, core subset of the DIP data. Please, check the reference page to find articles describing the DIP database in greater detail. The Database of Ligand-Receptor Partners (DLRP) is a subset of DIP (Database of Interacting Proteins). The DLRP is a database of protein ligand and protein receptor pairs that are known to interact with each other. By interact we mean that the ligand and receptor are members of a ligand-receptor complex and, unless otherwise noted, transduce a signal. In some instances the ligand and/or receptor may form a heterocomplex with other ligands/receptors in order to be functional. We have entered the majority of interactions in DLRP as full DIP entries, with links to references and additional information
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
DBpedia is a crowd-sourced community effort to extract structured information from Wikipedia and make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia, and to link the different data sets on the Web to Wikipedia data. We hope that this work will make it easier for the huge amount of information in Wikipedia to be used in some new interesting ways. Furthermore, it might inspire new mechanisms for navigating, linking, and improving the encyclopedia itself.
The global data compilation consisting of ca. 60,000 data points may be downloaded in csv/xml format. This compilation does not contain the descriptive codes relating to metadata that were included in the previous compilations. Users are advised to consult the references and make their own interpretations as to the quality of the data.
The CBU Dataverse is a research data repository for Cape Breton University. Files are held securely on Canadian servers, and can be made openly accessible to further research, gain citations and promote our world class research.
Our research focuses mainly on the past and present bio- and geodiversity and the evolution of animals and plants. The Information Technology Center of the Staatliche Naturwissenschaftliche Sammlungen Bayerns is the institutional repository for scientific data of the SNSB. Its major tasks focus on the management of bio- and geodiversity data using different kinds of information technological structures. The facility guarantees a sustainable curation, storage, archiving and provision of such data.
The University of Toronto Dataverse is a research data repository for our faculty, students, and staff. Files are held in a secure environment on Canadian servers. Researchers can choose to make content available publicly, to specific individuals, or to restrict access.
GeneCards is a searchable, integrative database that provides comprehensive, user-friendly information on all annotated and predicted human genes. It automatically integrates gene-centric data from ~125 web sources, including genomic, transcriptomic, proteomic, genetic, clinical and functional information.
The IERS provides data on Earth orientation, on the International Celestial Reference System/Frame, on the International Terrestrial Reference System/Frame, and on geophysical fluids. It maintains also Conventions containing models, constants and standards.
DEIMS-SDR (Dynamic Ecological Information Management System - Site and dataset registry) is an information management system that allows you to discover long-term ecosystem research sites around the globe, along with the data gathered at those sites and the people and networks associated with them. DEIMS-SDR describes a wide range of sites, providing a wealth of information, including each site’s location, ecosystems, facilities, parameters measured and research themes. It is also possible to access a growing number of datasets and data products associated with the sites. All sites and dataset records can be referenced using unique identifiers that are generated by DEIMS-SDR. It is possible to search for sites via keyword, predefined filters or a map search. By including accurate, up to date information in DEIMS, site managers benefit from greater visibility for their LTER site, LTSER platform and datasets, which can help attract funding to support site investments. The aim of DEIMS-SDR is to be the globally most comprehensive catalogue of environmental research and monitoring facilities, featuring foremost but not exclusively information about all LTER sites on the globe and providing that information to science, politics and the public in general.
In keeping with the open data policies of the U.S. Agency for International Development (USAID) and Bill & Melinda Gates Foundation, the Cereal Systems Initiative for South Asia (CSISA) has launched the CSISA Data Repository to ensure public accessibility to key data sets, including crop cut data- directly observed, crop yield estimates, on-station and on-farm research trial data and socioeconomic surveys. CSISA is a science-driven and impact-oriented regional initiative for increasing the productivity of cereal-based cropping systems in Bangladesh, India and Nepal, thus improving food security and farmers’ livelihoods. CSISA generates data that is of value and interest to a diverse audience of researchers, policymakers and the public. CSISA’s data repository is hosted on Dataverse, an open source web application developed at Harvard University to share, preserve, cite, explore and analyze research data. CSISA’s repository contains rich datasets, including on-station trial data from 2009–17 about crop and resource management practices for sustainable future cereal-based cropping systems. Collection of this data occurred during the long-term, on-station research trials conducted at the Indian Council of Agricultural Research – Research Complex for the Eastern Region in Bihar, India. The data include information on agronomic management for the sustainable intensification of cropping systems, mechanization, diversification, futuristic approaches to sustainable intensification, long-term effects of conservation agriculture practices on soil health and the pest spectrum. Additional trial data in the repository includes nutrient omission plot technique trials from Bihar, eastern Uttar Pradesh and Odisha, India, covering 2012–15, which help determine the indigenous nutrient supplying ability of the soil. This data helps develop precision nutrient management approaches that would be most effective in different types of soils. CSISA’s most popular dataset thus far includes crop cut data on maize in Odisha, India and rice in Nepal. Crop cut datasets provide ground-truthed yield estimates, as well as valuable information on relevant agronomic and socioeconomic practices affecting production practices and yield. A variety of research data on wheat systems are also available from Bangladesh and India. Additional crop cut data will also be coming online soon. Cropping system-related data and socioeconomic data are in the repository, some of which are cross-listed with a Dataverse run by the International Food Policy Research Institute. The socioeconomic datasets contain baseline information that is crucial for technology targeting, as well as to assess the adoption and performance of CSISA-supported technologies under smallholder farmers’ constrained conditions, representing the ultimate litmus test of their potential for change at scale. Other highly interesting datasets include farm composition and productive trajectory information, based on a 20-year panel dataset, and numerous wheat crop cut and maize nutrient omission trial data from across Bangladesh.