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Found 13 result(s)
CLARIN is a European Research Infrastructure for the Humanities and Social Sciences, focusing on language resources (data and tools). It is being implemented and constantly improved at leading institutions in a large and growing number of European countries, aiming at improving Europe's multi-linguality competence. CLARIN provides several services, such as access to language data and tools to analyze data, and offers to deposit research data, as well as direct access to knowledge about relevant topics in relation to (research on and with) language resources. The main tool is the 'Virtual Language Observatory' providing metadata and access to the different national CLARIN centers and their data.
The CLARIN­/Text+ repository at the Saxon Academy of Sciences and Humanities in Leipzig offers long­term preservation of digital resources, along with their descriptive metadata. The mission of the repository is to ensure the availability and long­term preservation of resources, to preserve knowledge gained in research, to aid the transfer of knowledge into new contexts, and to integrate new methods and resources into university curricula. Among the resources currently available in the Leipzig repository are a set of corpora of the Leipzig Corpora Collection (LCC), based on newspaper, Wikipedia and Web text. Furthermore several REST-based webservices are provided for a variety of different NLP-relevant tasks The repository is part of the CLARIN infrastructure and part of the NFDI consortium Text+. It is operated by the Saxon Academy of Sciences and Humanities in Leipzig.
Kaggle is a platform for predictive modelling and analytics competitions in which statisticians and data miners compete to produce the best models for predicting and describing the datasets uploaded by companies and users. This crowdsourcing approach relies on the fact that there are countless strategies that can be applied to any predictive modelling task and it is impossible to know beforehand which technique or analyst will be most effective.
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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GnpIS is a multispecies integrative information system dedicated to plant and fungi pests. It bridges genetic and genomic data, allowing researchers access to both genetic information (e.g. genetic maps, quantitative trait loci, association genetics, markers, polymorphisms, germplasms, phenotypes and genotypes) and genomic data (e.g. genomic sequences, physical maps, genome annotation and expression data) for species of agronomical interest. GnpIS is used by both large international projects and plant science departments at the French National Research Institute for Agriculture, Food and Environment. It is regularly improved and released several times per year. GnpIS is accessible through a web portal and allows to browse different types of data either independently through dedicated interfaces or simultaneously using a quick search ('google like search') or advanced search (Biomart, Galaxy, Intermine) tools.
The UK Data Archive, based at the University of Essex, is curator of the largest collection of digital data in the social sciences and humanities in the United Kingdom. With several thousand datasets relating to society, both historical and contemporary, our Archive is a vital resource for researchers, teachers and learners. We are an internationally acknowledged centre of expertise in the areas of acquiring, curating and providing access to data. We are the lead partner in the UK Data Service (https://service.re3data.org/repository/r3d100010230) through which data users can browse collections online and register to analyse and download them. Open Data collections are available for anyone to use. The UK Data Archive is a Trusted Digital Repository (TDR) certified against the CoreTrustSeal (https://www.coretrustseal.org/) and certified against ISO27001 for Information Security (https://www.iso.org/isoiec-27001-information-security.html).
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.
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.
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The Informatics Research Data Repository is a Japanese data repository that collects data on disciplines within informatics. Such sub-categories are things like consumerism and information diffusion. The primary data within these data sets is from experiments run by IDR on how one group is linked to another.
The Unidata community of over 260 universities is building a system for disseminating near real-time earth observations via the Internet. Unlike other systems, which are based on data centers where the information can be accessed, the Unidata IDD is designed so a university can request that certain data sets be delivered to computers at their site as soon as they are available from the observing system. The IDD system also allows any site with access to specialized observations to inject the dataset into the IDD for delivery to other interested sites.
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The Animal Sound Archive at the Museum für Naturkunde in Berlin is one of the oldest and largest collections of animal sounds. Presently, the collection consists of about 120,000 bioacoustical recordings comprising almost all groups of animals: 1.800 bird species 580 mammalian species more then150 species of invertebrates; some fishes, amphibians and reptiles
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.