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Found 9 result(s)
The Landcare Research DataStore ('the DataStore') is the general data catalogue and repository for Environmental Research Data from Landcare Research. Much of Landcare Research’s research data is available through specific web pages, but many datasets sit outside these areas. This data repository provides a mechanism for our staff to deposit and document this wider range of datasets so that they may be discovered and potentially re-used.
LinkedEarth is an EarthCube-funded project aiming to better organize and share Earth Science data, especially paleoclimate data. LinkedEarth facilitates the work of scientists by empowering them to curate their own data and to build new tools centered around those.
Yoda publishes research data on behalf of researchers that are affiliated with Utrecht University, its research institutes and consortia where it acts as a coordinating body. Data packages are not limited to a particular field of research or license. Yoda publishes data packages via Datacite. To find data publications use: https://public.yoda.uu.nl/ , or the Datacite search engine: https://search.datacite.org/repositories/delft.uu
REFOLD has merged to REFOLDdb. REFOLDdb is a unique database for the life sciences research community, providing annotated information for designing new refolding protocols and customizing existing methodologies. We envisage that this resource will find wide utility across broad disciplines that rely on the production of pure, active, recombinant proteins. Furthermore, the database also provides a useful overview of the recent trends and statistics in refolding technology development.We based our resource on the existing REFOLD database, which has not been updated since 2009. We redesigned the data format to be more concise, allowing consistent representations among data entries compared with the original REFOLD database. The remodeled data architecture enhances the search efficiency and improves the sustainability of the database. After an exhaustive literature search we added experimental refolding protocols from reports published 2009 to early 2017. In addition to this new data, we fully converted and integrated existing REFOLD data into our new resource.
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Created in 2005 by the CNRS, CNRTL unites in a single portal, a set of linguistic resources and tools for language processing. The CNRTL includes the identification, documentation (metadata), standardization, storage, enhancement and dissemination of resources. The sustainability of the service and the data is guaranteed by the backing of the UMR ATILF (CNRS - Université Nancy), support of the CNRS and its integration in the excellence equipment project ORTOLANG .
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.
The Centre’s vision is a rural transformation in the developing world as smallholder households strategically increase their use of trees in agricultural landscapes to improve their food security, nutrition, income, health, shelter, social cohesion, energy resources and environmental sustainability. The Centre’s mission is to generate science-based knowledge about the diverse roles that trees play in agricultural landscapes, and to use its research to advance policies and practices, and their implementation, that benefit the poor and the environment.
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SAMD is a repository for Standardized Atmospheric Measurement Data: Central Europe is a region with one of the most comprehensive networks for cloud and precipitation observations worldwide. To unify these observations, establish the infrastructure to store it and make it accessible to the research community is the goal of SAMD. SAMD is one result of the project "High Definition of Clouds and Precipitation in advancing Climate Prediction" (HD(CP)²).