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Found 10 result(s)

ILC-CNR for CLARIN-IT repository

ILC4CLARIN

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ILC-CNR for CLARIN-IT repository is a library for linguistic data and tools. Including: Text Processing and Computational Philology; Natural Language Processing and Knowledge Extraction; Resources, Standards and Infrastructures; Computational Models of Language Usage. The studies carried out within each area are highly interdisciplinary and involve different professional skills and expertises that extend across the disciplines of Linguistics, Computational Linguistics, Computer Science and Bio-Engineering.

nanoHUB

nanoHUB.org

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nanoHUB.org is the premier place for computational nanotechnology research, education, and collaboration. Our site hosts a rapidly growing collection of Simulation Programs for nanoscale phenomena that run in the cloud and are accessible through a web browser. In addition to simulation devices, nanoHUB provides Online Presentations, Courses, Learning Modules, Podcasts, Animations, Teaching Materials, and more. These resources help users learn about our simulation programs and about nanotechnology in general. Our site offers researchers a venue to explore, collaborate, and publish content, as well. Much of these collaborative efforts occur via Workspaces and User groups.

CLARIN-LV repository

CLARIN Latvia repository

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CLARIN-LV is a national node of Clarin ERIC (Common Language Resources and Technology Infrastructure). The mission of the repository is to ensure the availability and long­ term preservation of language resources. The data stored in the repository are being actively used and cited in scientific publications.

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.

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.

Reality Commons

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Cell phones have become an important platform for the understanding of social dynamics and influence, because of their pervasiveness, sensing capabilities, and computational power. Many applications have emerged in recent years in mobile health, mobile banking, location based services, media democracy, and social movements. With these new capabilities, we can potentially be able to identify exact points and times of infection for diseases, determine who most influences us to gain weight or become healthier, know exactly how information flows among employees and productivity emerges in our work spaces, and understand how rumors spread. In an attempt to address these challenges, we release several mobile data sets here in "Reality Commons" that contain the dynamics of several communities of about 100 people each. We invite researchers to propose and submit their own applications of the data to demonstrate the scientific and business values of these data sets, suggest how to meaningfully extend these experiments to larger populations, and develop the math that fits agent-based models or systems dynamics models to larger populations. These data sets were collected with tools developed in the MIT Human Dynamics Lab and are now available as open source projects or at cost.

Repository CLARIN Centre Leipzig

CLARIN repository at the Saxon Academy of Sciences and Humanities

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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.

LINDAT/CLARIAH-CZ repository

LINDAT/CLARIN repository

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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.

CEPDB

The Harvard Clean Energy Project Database

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-----<<<<< The repository is no longer available. This record is out-dated. The Matter lab provides the archived database version of 2012 and 2013 at https://www.matter.toronto.edu/basic-content-page/data-download. Data linked from the World Community Grid - The Clean Energy Project see at https://www.worldcommunitygrid.org/research/cep1/overview.do and on fighshare https://figshare.com/articles/dataset/moldata_csv/9640427 >>>>>----- The Clean Energy Project Database (CEPDB) is a massive reference database for organic semiconductors with a particular emphasis on photovoltaic applications. It was created to store and provide access to data from computational as well as experimental studies, on both known and virtual compounds. It is a free and open resource designed to support researchers in the field of organic electronics in their scientific pursuits. The CEPDB was established as part of the Harvard Clean Energy Project (CEP), a virtual high-throughput screening initiative to identify promising new candidates for the next generation of carbon-based solar cell materials.

CLARIN repository at the University of Tübingen

CLARIN Center Tübingen

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The repository is part of the National Research Data Infrastructure initiative Text+, in which the University of Tübingen is a partner. It is housed at the Department of General and Computational Linguistics. The infrastructure is maintained in close cooperation with the Digital Humanities Centre, which is a core facility of the university, colaborating with the library and computing center of the university. Integration of the repository into the national CLARIN-D and international CLARIN infrastructures gives it wide exposure, increasing the likelihood that the resources will be used and further developed beyond the lifetime of the projects in which they were developed. Among the resources currently available in the Tübingen Center Repository, researchers can find widely used treebanks of German (e.g. TüBa-D/Z), the German wordnet (GermaNet), the first manually annotated digital treebank (Index Thomisticus), as well as descriptions of the tools used by the WebLicht ecosystem for natural language processing.