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Found 12 result(s)
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The Freshwater Research and Environmental Database is the central data repository for IGB. It is where we store and share environmental data from observations of lakes, rivers, peatlands and other freshwater habitats. In FRED you can find continuous data collected over several decades from our long-term research programme at the lakes Müggelsee, Stechlinsee, Arendsee and the river Spree, as well as environmental data derived from short-term projects in aquatic ecosystems. All data include detailed metadata descriptions in text form to allow reuse of the data. The database can be searched for a range of aspects, such as ecosystem types or abiotic and biotic variables. Data use, where not freely accessible, shall be granted after consulting with the contact person given in the database, and is subject to the IGB Data Policy.
The Museum is committed to open access and open science, and has launched the Data Portal to make its research and collections datasets available online. It allows anyone to explore, download and reuse the data for their own research. Our natural history collection is one of the most important in the world, documenting 4.5 billion years of life, the Earth and the solar system. Almost all animal, plant, mineral and fossil groups are represented. These datasets will increase exponentially. Under the Museum's ambitious digital collections programme we aim to have 20 million specimens digitised in the next five years.
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Discuss Data is an open repository for storing, sharing and discussing research data on Eastern Europe, the South Caucasus and Central Asia. The platform, launched in September 2020, is funded by the German Research Foundation (DFG) and operated by the Research Centre for East European Studies at the University of Bremen (FSO) and the Göttingen State and University Library (SUB). Discuss Data goes beyond ordinary repositories and offers an interactive online platform for the discussion and quality assessment of research data. Our aim is to create a space for academic communication and for the community-specific publication, curation, annotation and discussion of research data.
VertNet is a NSF-funded collaborative project that makes biodiversity data free and available on the web. VertNet is a tool designed to help people discover, capture, and publish biodiversity data. It is also the core of a collaboration between hundreds of biocollections that contribute biodiversity data and work together to improve it. VertNet is an engine for training current and future professionals to use and build upon best practices in data quality, curation, research, and data publishing. Yet, VertNet is still the aggregate of all of the information that it mobilizes. To us, VertNet is all of these things and more.
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.”
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Swedish National Data Service (SND) is a research data infrastructure designed to assist researchers in preserving, maintaining, and disseminating research data in a secure and sustainable manner. The SND Search function makes it easy to find, use, and cite research data from a variety of scientific disciplines. Together with an extensive network of almost 40 Swedish higher education institutions and other research organisations, SND works for increased access to research data, nationally as well as internationally.
RUresearch Data Portal is a subset of RUcore (Rutgers University Community Repository), provides a platform for Rutgers researchers to share their research data and supplementary resources with the global scholarly community. This data portal leverages all the capabilities of RUcore with additional tools and services specific to research data. It provides data in different clusters (research-genre) with excellent search facility; such as experimental data, multivariate data, discrete data, continuous data, time series data, etc. However it facilitates individual research portals that include the Video Mosaic Collaborative (VMC), an NSF-funded collection of mathematics education videos for Teaching and Research. Its' mission is to maintain the significant intellectual property of Rutgers University; thereby intended to provide open access and the greatest possible impact for digital data collections in a responsible manner to promote research and learning.
ODC-TBI is a community platform to Share Data, Publish Data with a DOI, and get Citations. Advancing Traumatic Brain Injury research through sharing of data from basic and clinical research.
LINDAT/CLARIN is designed as a Czech “node” of Clarin ERIC (Common Language Resources and Technology Infrastructure). It also supports the goals of the META-NET language technology network. Both networks aim at collection, annotation, development and free sharing of language data and basic technologies between institutions and individuals both in science and in all types of research. The Clarin ERIC infrastructural project is more focused on humanities, while META-NET aims at the development of language technologies and applications. The data stored in the repository are already being used in scientific publications in the Czech Republic. In 2019 LINDAT/CLARIAH-CZ was established as a unification of two research infrastructures, LINDAT/CLARIN and DARIAH-CZ.
The SICAS Medical Image Repository is a freely accessible repository containing medical research data including medical images, surface models, clinical data, genomics data and statistical shape models. The data can freely be organized and shared on SMIR and made publicly accessible with a DOI. Dedicated data sets are organized as collections of anatomical regions (e.g Cochlea). The data can be filtered using a modular search and accessed on the web or through the SMIR API.