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Found 181 result(s)
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The GAVO data centre at Zentrum für Astronomie Heidelberg publishes astronomical data of all kinds – e.g., catalogues, images, spectra, time series, simulation results – in accordance with Virtual Observatory standards, making them findable and immediately usable through popular clients like TOPCAT, Aladin, or programatically through the astropy-affiliated package pyVO or the Java library STIL. We pay particular attention to providing thorough metadata to the VO Registry in order to facilitate discovery and reuse. While we have a clear focus on data produced with German contributions, we will usually publish data of other provenance, too. See https://docs.g-vo.org/DaCHS/data_checklist.html for an overview of what resource-level metadata we ask for; contact us for further information on how to publish through the German Astronomical Virtual Observatory.
The range of CIRAD's research has given rise to numerous datasets and databases associating various types of data: primary (collected), secondary (analysed, aggregated, used for scientific articles, etc), qualitative and quantitative. These "collections" of research data are used for comparisons, to study processes and analyse change. They include: genetics and genomics data, data generated by trials and measurements (using laboratory instruments), data generated by modelling (interpolations, predictive models), long-term observation data (remote sensing, observatories, etc), data from surveys, cohorts, interviews with players.
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The National High Energy Physics Science Data Center (NHEPSDC) is a repository for high-energy physics. In 2019, it was designated as a scientific data center at the national level by the Ministry of Science and Technology of China (MOST). NHEPSDC is constructed and operated by the Institute of High Energy Physics (IHEP) of the Chinese Academy of Sciences (CAS). NHEPSDC consists of a main data center in Beijing, a branch center in Guangdong-Hong Kong-Macao Greater Bay Area, and a branch center in Huairou District of Beijing. The mission of NHEPSDC is to provide the services of data collection, archiving, long-term preservation, access and sharing, software tools, and data analysis. The services of NHEPSDC are mainly for high-energy physics and related scientific research activities. The data collected can be roughly divided into the following two categories: one is the raw data from large scientific facilities, and the other is data generated from general scientific and technological projects (usually supported by government funding), hereafter referred to as generic data. More than 70 people work in NHEPSDC now, with 18 in high-energy physics, 17 in computer science, 15 in software engineering, 20 in data management and some other operation engineers. NHEPSDC is equipped with a hierarchical storage system, high-performance computing power, high bandwidth domestic and international network links, and a professional service support system. In the past three years, the average data increment is about 10 PB per year. By integrating data resources with the IT environment, a state-of-art data process platform is provided to users for scientific research, the volume of data accessed every year is more than 400 PB with more than 10 million visits.
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SILVA is a comprehensive, quality-controlled web resource for up-to-date aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains alongside supplementary online services. In addition to data products, SILVA provides various online tools such as alignment and classification, phylogenetic tree calculation and viewer, probe/primer matching, and an amplicon analysis pipeline. With every full release a curated guide tree is provided that contains the latest taxonomy and nomenclature based on multiple references. SILVA is an ELIXIR Core Data Resource.
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Research Data Unipd is a data archive and supports research produced by the members of the University of Padova. The service aims to facilitate 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.
IEEE DataPort™ is a universally accessible online data repository created, owned, and supported by IEEE, the world’s largest technical professional organization. It enables all researchers and data owners to upload their dataset without cost. IEEE DataPort makes data available in three ways: standard datasets, open access datasets, and data competition datasets. By default, all "standard" datasets that are uploaded are accessible to paid IEEE DataPort subscribers. Data owners have an option to pay a fee to make their dataset “open access”, so it is available to all IEEE DataPort users (no subscription required). The third option is to host a "data competition" and make a dataset accessible for free for a specific duration with instructions for the data competition and how to participate. IEEE DataPort provides workflows for uploading data, searching, and accessing data, and initiating or participating in data competitions. All datasets are stored on Amazon AWS S3, and each dataset uploaded by an individual can be up to 2TB in size. Institutional subscriptions are available to the platform to make it easy for all members of a given institution to utilize the platform and upload datasets.
Brainlife promotes engagement and education in reproducible neuroscience. We do this by providing an online platform where users can publish code (Apps), Data, and make it "alive" by integragrate various HPC and cloud computing resources to run those Apps. Brainlife also provide mechanisms to publish all research assets associated with a scientific project (data and analyses) embedded in a cloud computing environment and referenced by a single digital-object-identifier (DOI). The platform is unique because of its focus on supporting scientific reproducibility beyond open code and open data, by providing fundamental smart mechanisms for what we refer to as “Open Services.”
The German Text Archive (Deutsches Textarchiv, DTA) presents online a selection of key German-language works in various disciplines from the 17th to 19th centuries. The electronic full-texts are indexed linguistically and the search facilities tolerate a range of spelling variants. The DTA presents German-language printed works from around 1650 to 1900 as full text and as digital facsimile. The selection of texts was made on the basis of lexicographical criteria and includes scientific or scholarly texts, texts from everyday life, and literary works. The digitalisation was made from the first edition of each work. Using the digital images of these editions, the text was first typed up manually twice (‘double keying’). To represent the structure of the text, the electronic full-text was encoded in conformity with the XML standard TEI P5. The next stages complete the linguistic analysis, i.e. the text is tokenised, lemmatised, and the parts of speech are annotated. The DTA thus presents a linguistically analysed, historical full-text corpus, available for a range of questions in corpus linguistics. Thanks to the interdisciplinary nature of the DTA Corpus, it also offers valuable source-texts for neighbouring disciplines in the humanities, and for scientists, legal scholars and economists.
Established in 1965, the CSD is the world’s repository for small-molecule organic and metal-organic crystal structures. Containing the results of over one million x-ray and neutron diffraction analyses this unique database of accurate 3D structures has become an essential resource to scientists around the world. The CSD records bibliographic, chemical and crystallographic information for:organic molecules, metal-organic compounds whose 3D structures have been determined using X-ray diffraction, neutron diffraction. The CSD records results of: single crystal studies, powder diffraction studies which yield 3D atomic coordinate data for at least all non-H atoms. In some cases the CCDC is unable to obtain coordinates, and incomplete entries are archived to the CSD. The CSD includes crystal structure data arising from: publications in the open literature and Private Communications to the CSD (via direct data deposition). The CSD contains directly deposited data that are not available anywhere else, known as CSD Communications.
Academic Torrents is a distributed data repository. The academic torrents network is built for researchers, by researchers. Its distributed peer-to-peer library system automatically replicates your datasets on many servers, so you don't have to worry about managing your own servers or file availability. Everyone who has data becomes a mirror for those data so the system is fault-tolerant.
The University of Cape Town (UCT) uses Figshare for institutions for their data repository, which was launched in 2017 and is called ZivaHub: Open Data UCT. ZivaHub serves principal investigators at the University of Cape Town who are in need of a repository to store and openly disseminate the data that support their published research findings. The repository service is provided in terms of the UCT Research Data Management Policy. It provides open access to supplementary research data files and links to their respective scholarly publications (e.g. theses, dissertations, papers et al) hosted on other platforms, such as OpenUCT.
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Rodare is the institutional research data repository at HZDR (Helmholtz-Zentrum Dresden-Rossendorf). Rodare allows HZDR researchers to upload their research software and data and enrich those with metadata to make them findable, accessible, interoperable and retrievable (FAIR). By publishing all associated research software and data via Rodare research reproducibility can be improved. Uploads receive a Digital Object Identfier (DOI) and can be harvested via a OAI-PMH interface.
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Jülich DATA is a registry service to index all research data created at or in the context of Forschungszentrum Jülich. As an institutionial repository, it may also be used for data and software publications.
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Figshare has been chosen as the University of Adelaide's official data and digital object repository with unlimited local storage. All current staff and HDR students can access and publish research data and digital objects on the University of Adelaide's Figshare site. Because Figshare is cloud-based, you can access it anywhere and at any time.
The CLARIN-D Centre CEDIFOR provides a repository for long-term storage of resources and meta-data. Resources hosted in the repository stem from research of members as well as associated research projects of CEDIFOR. This includes software and web-services as well as corpora of text, lexicons, images and other data.
The JPL Tropical Cyclone Information System (TCIS) was developed to support hurricane research. There are three components to TCIS; a global archive of multi-satellite hurricane observations 1999-2010 (Tropical Cyclone Data Archive), North Atlantic Hurricane Watch and ASA Convective Processes Experiment (CPEX) aircraft campaign. Together, data and visualizations from the real time system and data archive can be used to study hurricane process, validate and improve models, and assist in developing new algorithms and data assimilation techniques.
Central data management of the USGS for water data that provides access to water-resources data collected at approximately 1.5 million sites in all 50 States, the District of Columbia, Puerto Rico, the Virgin Islands, Guam, American Samoa and the Commonwealth of the Northern Mariana Islands. Includes data on water use and quality, groundwater, and surface water.
DATA.NASA.GOV is NASA's clearinghouse site for open-data provided to the public. Tens of thousands of datasets are available for you. This site is a continually growing catalog of publicly available NASA Datasets, APIs, Visualizations, and more.
OpenWorm aims to build the first comprehensive computational model of the Caenorhabditis elegans (C. elegans), a microscopic roundworm. With only a thousand cells, it solves basic problems such as feeding, mate-finding and predator avoidance. Despite being extremely well studied in biology, this organism still eludes a deep, principled understanding of its biology. We are using a bottom-up approach, aimed at observing the worm behaviour emerge from a simulation of data derived from scientific experiments carried out over the past decade. To do so we are incorporating the data available in the scientific community into software models. We are engineering Geppetto and Sibernetic, open-source simulation platforms, to be able to run these different models in concert. We are also forging new collaborations with universities and research institutes to collect data that fill in the gaps All the code we produce in the OpenWorm project is Open Source and available on GitHub.
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Reptiles and amphibians are collectively known as herpetofauna and are a unique part of Ontario’s biodiversity. An earlier atlas, called the Ontario Herpetofaunal Summary Atlas, provided extensive information about where many of the province’s reptiles and amphibians occurred. The Atlas is transitioning into a new era, with Ontario Nature wrapping-up the data collection phase of this project as of December 1, 2019. Now that we have discontinued our app and online form, we encourage you to continue submitting any future observations through the ‘Herps of Ontario’ project (https://www.inaturalist.org/projects/herps-of-ontario) on iNaturalist or directly to the Natural Heritage Information Centre (nhicrequests@ontario.ca) for species at risk. To learn more about the transition, read our blog (https://ontarionature.org/ontario-reptile-and-amphibian-atlas-changes/)
The datacommons@psu was developed in 2005 to provide a resource for data sharing, discovery, and archiving for the Penn State research and teaching community. Access to information is vital to the research, teaching, and outreach conducted at Penn State. The datacommons@psu serves as a data discovery tool, a data archive for research data created by PSU for projects funded by agencies like the National Science Foundation, as well as a portal to data, applications, and resources throughout the university. The datacommons@psu facilitates interdisciplinary cooperation and collaboration by connecting people and resources and by: Acquiring, storing, documenting, and providing discovery tools for Penn State based research data, final reports, instruments, models and applications. Highlighting existing resources developed or housed by Penn State. Supporting access to project/program partners via collaborative map or web services. Providing metadata development citation information, Digital Object Identifiers (DOIs) and links to related publications and project websites. Members of the Penn State research community and their affiliates can easily share and house their data through the datacommons@psu. The datacommons@psu will also develop metadata for your data and provide information to support your NSF, NIH, or other agency data management plan.
MODES focuses on the representation of the inertio-gravity circulation in numerical weather prediction models, reanalyses, ensemble prediction systems and climate simulations. The project methodology relies on the decomposition of global circulation in terms of 3D orthogonal normal-mode functions. It allows quantification of the role of inertio-gravity waves in atmospheric varibility across the whole spectrum of resolved spatial and temporal scales. MODES is compiled by using gfortran although other options have been succesfully tested. The application requires the use of the netcdf and (optionally) grib-api libraries.