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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.
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.
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.
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.
CLARIN.SI is the Slovenian node of the European CLARIN (Common Language Resources and Technology Infrastructure) Centers. The CLARIN.SI repository is hosted at the Jožef Stefan Institute and offers long-term preservation of deposited linguistic resources, along with their descriptive metadata. The integration of the repository with the CLARIN infrastructure gives the deposited resources wide exposure, so that they can be known, used and further developed beyond the lifetime of the projects in which they were produced. Among the resources currently available in the CLARIN.SI repository are the multilingual MULTEXT-East resources, the CC version of Slovenian reference corpus Gigafida, the morphological lexicon Sloleks, the IMP corpora and lexicons of historical Slovenian, as well as many other resources for a variety of languages. Furthermore, several REST-based web services are provided for different corpus-linguistic and NLP tasks.
Additional to the the e-publishing offer for articles, books and journals, Propylaeum provides classical scholars with the opportunity to archive the respective research data permanently. These can be linked directly to online publications hosted on the Heidelberg publishing platforms. All research data – e.g. images, videos, audio files, tables, graphics etc. – receive a DOI (Digital Object Identifiyer). Thus, they can be cited, viewed and permanently linked to as distinct academic output.
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.