Filter
Reset all

Subjects

Content Types

Countries

AID systems

API

Data access

Data access restrictions

Database access

Data licenses

Data upload

Data upload restrictions

Enhanced publication

Institution responsibility type

Institution type

Keywords

Metadata standards

PID systems

Provider types

Quality management

Repository languages

Software

Repository types

Versioning

  • * at the end of a keyword allows wildcard searches
  • " quotes can be used for searching phrases
  • + represents an AND search (default)
  • | represents an OR search
  • - represents a NOT operation
  • ( and ) implies priority
  • ~N after a word specifies the desired edit distance (fuzziness)
  • ~N after a phrase specifies the desired slop amount
  • 1 (current)
Found 10 result(s)
The Alternative Fuels Data Center (AFDC) is a comprehensive clearinghouse of information about advanced transportation technologies. The AFDC offers transportation decision makers unbiased information, data, and tools related to the deployment of alternative fuels and advanced vehicles. The AFDC launched in 1991 in response to the Alternative Motor Fuels Act of 1988 and the Clean Air Act Amendments of 1990. It originally served as a repository for alternative fuel performance data. The AFDC has since evolved to offer a broad array of information resources that support efforts to reduce petroleum use in transportation. The AFDC serves Clean Cities stakeholders, fleets regulated by the Energy Policy Act, businesses, policymakers, government agencies, and the general public.
The CMU Multi-Modal Activity Database (CMU-MMAC) database contains multimodal measures of the human activity of subjects performing the tasks involved in cooking and food preparation. The CMU-MMAC database was collected in Carnegie Mellon's Motion Capture Lab. A kitchen was built and to date twenty-five subjects have been recorded cooking five different recipes: brownies, pizza, sandwich, salad, and scrambled eggs.
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.
Country
GTS AI is an Artificial Intelligence Company that offers excellent services to its clients. We use high definition images and use high quality data to analyze and help in Machine Learning Company . We are a dataset provider and we collect data in regards to artificial intelligence.
An increasing number of Language Resources (LT) in the various fields of Human Language Technology (HLT) are distributed on behalf of ELRA via its operational body ELDA, thanks to the contribution of various players of the HLT community. Our aim is to provide Language Resources, by means of this repository, so as to prevent researchers and developers from investing efforts to rebuild resources which already exist as well as help them identify and access those resources.
<<<!!!<<< All user content from this site has been deleted. Visit SeedMeLab (https://seedmelab.org/) project as a new option for data hosting. >>>!!!>>> SeedMe is a result of a decade of onerous experience in preparing and sharing visualization results from supercomputing simulations with many researchers at different geographic locations using different operating systems. It’s been a labor–intensive process, unsupported by useful tools and procedures for sharing information. SeedMe provides a secure and easy-to-use functionality for efficiently and conveniently sharing results that aims to create transformative impact across many scientific domains.
Country
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.
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.
CLARIN-UK is a consortium of centres of expertise involved in research and resource creation involving digital language data and tools. The consortium includes the national library, and academic departments and university centres in linguistics, languages, literature and computer science.
Country
With the KIT Whole-Body Human Motion Database, we aim to provide a simple way of sharing high-quality motion capture recordings of human whole-body motion. In addition, with the Motion Annotation Tool (https://motion-annotation.humanoids.kit.edu/ ), we aim to collect a comprehensive set of whole-body motions along with natural language descriptions of these motions (https://motion-annotation.humanoids.kit.edu/dataset/).