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Found 11 result(s)

Ozone Mapping and Profiler Suite

OMPS

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The Ozone Mapping and Profiler Suite measures the ozone layer in our upper atmosphere—tracking the status of global ozone distributions, including the ‘ozone hole.’ It also monitors ozone levels in the troposphere, the lowest layer of our atmosphere. OMPS extends out 40-year long record ozone layer measurements while also providing improved vertical resolution compared to previous operational instruments. Closer to the ground, OMPS’s measurements of harmful ozone improve air quality monitoring and when combined with cloud predictions; help to create the Ultraviolet Index, a guide to safe levels of sunlight exposure. OMPS has two sensors, both new designs, composed of three advanced hyperspectralimaging spectrometers.The three spectrometers: a downward-looking nadir mapper, nadir profiler and limb profiler. The entire OMPS suite currently fly on board the Suomi NPP spacecraft and are scheduled to fly on the JPSS-2 satellite mission. NASA will provide the OMPS-Limb profiler.

UC San Diego Library Digital Collections

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The UC San Diego Library Digital Collections website gathers two categories of content managed by the Library: library collections (including digitized versions of selected collections covering topics such as art, film, music, history and anthropology) and research data collections (including research data generated by UC San Diego researchers).

DataverseNO

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DataverseNO (https://dataverse.no) is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.

IMPACT

IMPACT Cyber Trust

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The Information Marketplace for Policy and Analysis of Cyber-risk & Trust (IMPACT) program supports global cyber risk research & development by coordinating, enhancing and developing real world data, analytics and information sharing capabilities, tools, models, and methodologies. In order to accelerate solutions around cyber risk issues and infrastructure security, IMPACT makes these data sharing components broadly available as national and international resources to support the three-way partnership among cyber security researchers, technology developers and policymakers in academia, industry and the government.

Federated Research Data Repository

Dépôt fédéré de données de recherche

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The Federated Research Data Repository (FRDR) is a bilingual publishing platform for sharing and preserving Canadian research data. It is a curated, general-purpose repository, custom built for large datasets.

BioVel

Biodiversity Virtual e-Laboratory

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<<<!!!<<< This repository is no longer available. >>>!!!>>> BioVeL is a virtual e-laboratory that supports research on biodiversity issues using large amounts of data from cross-disciplinary sources. BioVeL supports the development and use of workflows to process data. It offers the possibility to either use already made workflows or create own. BioVeL workflows are stored in MyExperiment - Biovel Group http://www.myexperiment.org/groups/643/content. They are underpinned by a range of analytical and data processing functions (generally provided as Web Services or R scripts) to support common biodiversity analysis tasks. You can find the Web Services catalogued in the BiodiversityCatalogue.

DR-NTU (Data)

Data repository - Nanyang Technological University

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DR-NTU (Data) is the institutional open access research data repository for Nanyang Technological University (NTU), Singapore. NTU researchers are encouraged to use DR-NTU (Data) to deposit, publish and archive their final research data in order to make their research data discoverable, accessible and reusable.

INPTDAT

The Data Platform for Plasma Technology

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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.

OpenKIM

Knowledgebase of Interatomic Models

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OpenKIM is an online suite of open source tools for molecular simulation of materials. These tools help to make molecular simulation more accessible and more reliable. Within OpenKIM, you will find an online resource for standardized testing and long-term warehousing of interatomic models and data, and an application programming interface (API) standard for coupling atomistic simulation codes and interatomic potential subroutines.

Ag Data Commons

USDA’s Open Research Data

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Ag Data Commons provides access to a wide variety of open data relevant to agricultural research. We are a centralized repository for data already on the web, as well as for new data being published for the first time. While compliance with the U.S. Federal public access and open data directives is important, we aim to surpass them. Our goal is to foster innovative data re-use, integration, and visualization to support bigger, better science and policy.

OpenML

Open Machine Learning

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OpenML is an open ecosystem for machine learning. By organizing all resources and results online, research becomes more efficient, useful and fun. OpenML is a platform to share detailed experimental results with the community at large and organize them for future reuse. Moreover, it will be directly integrated in today’s most popular data mining tools (for now: R, KNIME, RapidMiner and WEKA). Such an easy and free exchange of experiments has tremendous potential to speed up machine learning research, to engender larger, more detailed studies and to offer accurate advice to practitioners. Finally, it will also be a valuable resource for education in machine learning and data mining.