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Found 85 result(s)
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TUL Open Research Data Repository (RDB.open) is a service addressed to the scientific and research community of the Lodz University of Technology. The main purpose of RDB.open is to collect, share and store the open research data, both during the research and after its completion, at least for the minimum period indicated by the funder or the scientists. The RDB.open is a place where research data can be openly shared, accessed and then reused by others.
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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.
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Repository "Open Science Resource Atlas 2.0" aims to increase the accessibility, improve the quality and extend the reusability of science resources. Repository focuses on the digital sharing of resources of great importance to the field of science and economy. These include publications, scripts, lectures, 3D models, audio and video recordings, photos, input and output files of various computer programs, databases collecting data from various fields, machines, systems, language corpora and many others. The target group, apart from academics, students and doctoral students, is everyone interested, including entrepreneurs and, what is important and unique - disabled, blind, visually impaired and deaf people.
The Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC) is a team of researchers, data specialists and computer system developers who are supporting the development of a data management system to store scientific data generated by Gulf of Mexico researchers. The Master Research Agreement between BP and the Gulf of Mexico Alliance that established the Gulf of Mexico Research Initiative (GoMRI) included provisions that all data collected or generated through the agreement must be made available to the public. The Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC) is the vehicle through which GoMRI is fulfilling this requirement. The mission of GRIIDC is to ensure a data and information legacy that promotes continual scientific discovery and public awareness of the Gulf of Mexico Ecosystem.
HunCLARIN is a strategic research infrastructure of Hungary’s leading knowledge centres involved in R&D in speech- and language processing. It contains linguistic resources and tools that form the basis of research. The infrastructure has obtained an “SKI” qualification (Strategic Research Infrastructure) in 2010, and has been significantly expanded since. Currently comprising 36 members, the infrastructure includes several general- and specific-purpose text corpora, different language processing tools and analysers, linguistic databases as well as ontologies. RIL HAS was a co-founder of the European CLARIN project, which aims at supporting humanities and social sciences research with the help of language technology and by making digital linguistic resources more easily available. In accordance with these goals HunClarin makes the research infrastructures developed by the respective centres directly accessible for researchers through a common network entry point. A general goal of the infrastructure is to realise the interoperability of the collected research infrastructures and to enable comparing the performance of the respective alternatives and to coordinate different foci in R&D. The coordinator and contact person of the infrastructure is Tamás Váradi, RIL HAS.
The Registry of Open Data on AWS provides a centralized repository of public data sets that can be seamlessly integrated into AWS cloud-based applications. AWS is hosting the public data sets at no charge to their users. Anyone can access these data sets from their Amazon Elastic Compute Cloud (Amazon EC2) instances and start computing on the data within minutes. Users can also leverage the entire AWS ecosystem and easily collaborate with other AWS users.
Social Computing Data Repository hosts data from a collection of many different social media sites, most of which have blogging capacity. Some of the prominent social media sites included in this repository are BlogCatalog, Twitter, MyBlogLog, Digg, StumbleUpon, del.icio.us, MySpace, LiveJournal, The Unofficial Apple Weblog (TUAW), Reddit, etc. The repository contains various facets of blog data including blog site metadata like, user defined tags, predefined categories, blog site description; blog post level metadata like, user defined tags, date and time of posting; blog posts; blog post mood (which is defined as the blogger's emotions when (s)he wrote the blog post); blogger name; blog post comments; and blogger social network.
The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. It is used by students, educators, and researchers all over the world as a primary source of machine learning data sets. As an indication of the impact of the archive, it has been cited over 1000 times.
Polish CLARIN node – CLARIN-PL Language Technology Centre – is being built at Wrocław University of Technology. The LTC is addressed to scholars in the humanities and social sciences. Registered users are granted free access to digital language resources and advanced tools to explore them. They can also archive and share their own language data (in written, spoken, video or multimodal form).
The Open Science Framework (OSF) is part network of research materials, part version control system, and part collaboration software. The purpose of the software is to support the scientist's workflow and help increase the alignment between scientific values and scientific practices. Document and archive studies. Move the organization and management of study materials from the desktop into the cloud. Labs can organize, share, and archive study materials among team members. Web-based project management reduces the likelihood of losing study materials due to computer malfunction, changing personnel, or just forgetting where you put the damn thing. Share and find materials. With a click, make study materials public so that other researchers can find, use and cite them. Find materials by other researchers to avoid reinventing something that already exists. Detail individual contribution. Assign citable, contributor credit to any research material - tools, analysis scripts, methods, measures, data. Increase transparency. Make as much of the scientific workflow public as desired - as it is developed or after publication of reports. Find public projects here. Registration. Registering materials can certify what was done in advance of data analysis, or confirm the exact state of the project at important points of the lifecycle such as manuscript submission or at the onset of data collection. Discover public registrations here. Manage scientific workflow. A structured, flexible system can provide efficiency gain to workflow and clarity to project objectives, as pictured.
To help flattening the COVID-19 curve public health systems need better information on whether preventive measures are working and how the virus may spread. Facebook Data for Good offer maps on population movement that researchers and nonprofits are already using to understand the coronavirus crisis, using aggregated data to protect people’s privacy.
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HilData is registered by Hildesheim University Library, The access is via registration to the data and to the repository. Research data is with regards to educational science. Research data are sensitive and cannot be made fully open. HILDE Online is integrated in HilData: https://www.uni-hildesheim.de/celeb/projekte/fallarchiv-hilde/hildeonline-streaming-server/ HilData is working on its metadata (exposing metadata via interfaces) w.r.t. the FAIR principles and data citation. HilData and HILDE Online provide long-term storage and access to research data. The research data repository provides restricted access to its data. The research data repository uses DOI to make its provided data persistent, unique and citable.
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.
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.
For datasets from individual researchers or research groups affiliated with Stockholm University, who do not want set up a separate Dataverse for a project or institution. Metadata provisions for Geospatial, Social Science, Humanities, Astronomy, Astrophysics, Life Sciences and Journals (all optional, by choice) are included. Data curation help from Stockholm University Library possible on request.
CLAPOP is the portal of the Dutch CLARIN community. It brings together all relevant resources that were created within the CLARIN NL project and that now are part of the CLARIN NL infrastructure or that were created by other projects but are essential for the functioning of the CLARIN (NL) infrastructure. CLARIN-NL has closely cooperated with CLARIN Flanders in a number of projects. The common results of this cooperation and the results of this cooperation created by CLARIN Flanders are included here as well.
This is the KONECT project, a project in the area of network science with the goal to collect network datasets, analyse them, and make available all analyses online. KONECT stands for Koblenz Network Collection, as the project has roots at the University of Koblenz–Landau in Germany. All source code is made available as Free Software, and includes a network analysis toolbox for GNU Octave, a network extraction library, as well as code to generate these web pages, including all statistics and plots. KONECT contains over a hundred network datasets of various types, including directed, undirected, bipartite, weighted, unweighted, signed and rating networks. The networks of KONECT are collected from many diverse areas such as social networks, hyperlink networks, authorship networks, physical networks, interaction networks and communication networks. The KONECT project has developed network analysis tools which are used to compute network statistics, to draw plots and to implement various link prediction algorithms. The result of these analyses are presented on these pages. Whenever we are allowed to do so, we provide a download of the networks.