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Found 85 result(s)
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The INESC TEC data repository showcases datasets produced or used by INESC TEC researchers and their partners. The repository is organized in four groups (institutional clusters). Computer Science, Power and Energy, Network and Intelligent Systems and Power and Energy.
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.
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Discover the data on entrepreneurship projects, innovation plans, digital transformation proposals, consumers, and financial markets. Also, explore research on business, management, and entrepreneurship research development at our Business school.
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SMU Research Data Repository (SMU RDR) is a tool and service for researchers from Singapore Management University (SMU) to store, share and publish their research data. SMU RDR accepts a wide range of research data and outputs generated from research projects.
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The Repository stores in digital format all the academic and scientific documentation (Theses, Articles, Papers) generated by the institution. Its main objectives are to promote open access to the scientific-technological production generated by the Institution. It is organized by collections: Thesis and Final Works, Research, Institutional History and Photographic Archive.
The ColabFit Exchange is an online resource for the discovery, exploration and submission of datasets for data-driven interatomic potential (DDIP) development for materials science and chemistry applications. ColabFit's goal is to increase the Findability, Accessibility, Interoperability, and Reusability (FAIR) of DDIP data by providing convenient access to well-curated and standardized first-principles and experimental datasets. Content on the ColabFit Exchange is open source and freely available.
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.
Sharing and preserving data are central to protecting the integrity of science. DataHub, a Research Computing endeavor, provides tools and services to meet scientific data challenges at Pacific Northwest National Laboratory (PNNL). DataHub helps researchers address the full data life cycle for their institutional projects and provides a path to creating findable, accessible, interoperable, and reusable (FAIR) data products. Although open science data is a crucial focus of DataHub’s core services, we are interested in working with evidence-based data throughout the PNNL research community.
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IIASA DARE is the institutional repository for publishing open research data produced by all researchers affiliated with IIASA - International Institute for Applied Systems Analysis. IIASA has been implemented to help scientists fulfill the requirements from funding bodies and to meet the growing impact of publishing research data. The deposited data will receive a persistent, citable link and it will be openly accessible and stored for the long term.
>>>!!!<<< 2018-01-18: no data nor programs can be found >>>!!!<<< These archives contain public domain programs for calculations in physics and other programs that we suppose about will help during work with computer. Physical constants and experimental or theoretical data as cross sections, rate constants, swarm parameters, etc., that are necessary for physical calculations are stored here, too. Programs are mainly dedicated to computers compatible with PC IBM. If programs do not use graphic units it is possible to use them on other computers, too. It is necessary to reprogram the graphic parts of programs in the other cases.
Savannah hosts the majority of GNU software and some non-GNU software. Savannah's focus is on hosting for free software projects. To ensure that only free software is hosted, Savannah implements very strict hosting policies, including a ban against the use of non-free formats (such as Macromedia Flash).
FLOSSmole is a collaborative collection of free, libre, and open source software (FLOSS) data. FLOSSmole contains nearly 1 TB of data covering the period 2004 until now, about more than 500,000 different open source projects.
<<<!!!<<< 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.
The UA Campus Repository is an institutional repository that facilitates access to the research, creative works, publications and teaching materials of the University by collecting, sharing and archiving content selected and deposited by faculty, researchers, staff and affiliated contributors.
SLAPIS is an integrated Flood Early Warning System that aims to promote decision-making and behavioral changes from reactive to proactive at several levels, from the community to the administration, for the reduction of flood risk in the Communes of the Sirba (main tributary of the Niger River and cause of the main floods in the region)
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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.
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.
The University of Cape Town (UCT) uses Figshare for institutions for their data repository, which was launched in 2017 and is called ZivaHub: Open Data UCT. ZivaHub serves principal investigators at the University of Cape Town who are in need of a repository to store and openly disseminate the data that support their published research findings. The repository service is provided in terms of the UCT Research Data Management Policy. It provides open access to supplementary research data files and links to their respective scholarly publications (e.g. theses, dissertations, papers et al) hosted on other platforms, such as OpenUCT.
The Information Marketplace for Policy and Analysis of Cyber-risk & Trust (IMPACT) program supports global cyber risk research & development by coordinating, enhancing and developing real world data, analytics and information sharing capabilities, tools, models, and methodologies. In order to accelerate solutions around cyber risk issues and infrastructure security, IMPACT makes these data sharing components broadly available as national and international resources to support the three-way partnership among cyber security researchers, technology developers and policymakers in academia, industry and the government.