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Found 11 result(s)
The Metropolitan Travel Survey Archive (MTSA) includes travel surveys from numerous public agencies across the United States. The Transportation Secure Data Center has archived these surveys to ensure their continued public availability. The survey data have been converted to a standard file format and cleansed to remove personally identifiable information, including any detailed spatial data regarding individual trips.
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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ISIDORE is a international search engine and a discovery platform for open science allowing the access to digital materials from social sciences and humanities (SSH). Open to all and especially to teachers, researchers, PhD students, and students, it relies on the principles of Web of data and provides access to data in free access (open access). By its vocation, ISIDORE will foster access to open access data produced by research and higher education institutions, laboratories and research teams: digital publication, documentary databases, digitized collections of research libraries, research notebooks and scientific event announcements. ISIDORE collects, enriches and highlights digital data and documents from the Humanities and Social Sciences while providing unified access to them. More information see: https://isidore.science/about
The Scientific Data Repository Hosting Service (SARDC) intends to provide a platform for free access to data created and used in the scope of the research work of national institutions. It is characterized by the availability of a repository platform ( DSpace ) and support for the entire data maintenance component, such as backups, monitoring, updating, security, etc., thus keeping researchers out of the concern of these tasks. Finally, the SARDC service intends to make the data deposited in the repository available through the RCAAP Portal.
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.
The DesignSafe Data Depot Repository (DDR) is the platform for curation and publication of datasets generated in the course of natural hazards research. The DDR is an open access data repository that enables data producers to safely store, share, organize, and describe research data, towards permanent publication, distribution, and impact evaluation. The DDR allows data consumers to discover, search for, access, and reuse published data in an effort to accelerate research discovery. It is a component of the DesignSafe cyberinfrastructure, which represents a comprehensive research environment that provides cloud-based tools to manage, analyze, curate, and publish critical data for research to understand the impacts of natural hazards. DesignSafe is part of the NSF-supported Natural Hazards Engineering Research Infrastructure (NHERI), and aligns with its mission to provide the natural hazards research community with open access, shared-use scholarship, education, and community resources aimed at supporting civil and social infrastructure prior to, during, and following natural disasters. It serves a broad national and international audience of natural hazard researchers (both engineers and social scientists), students, practitioners, policy makers, as well as the general public. It has been in operation since 2016, and also provides access to legacy data dating from about 2005. These legacy data were generated as part of the NSF-supported Network for Earthquake Engineering Simulation (NEES), a predecessor to NHERI. Legacy data and metadata belonging to NEES were transferred to the DDR for continuous preservation and access.
GroupLens is a research lab in the Department of Computer Science and Engineering at the University of Minnesota, Twin Cities specializing in recommender systems, online communities, mobile and ubiquitous technologies, digital libraries, and local geographic information systems.
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The sources of the data sets include data sets donated by researchers, surveys carried out by SRDA, as well as by government department and other academic organizations. Prior to the release of data sets, the confidentiality and sensitivity of every survey data set are evaluated. Standard data management and cleaning procedures are applied to ensure data accuracy and completeness. In addition, metadata and relevant supplement files are also edited and attached.
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.