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Found 48 result(s)
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PsychArchives is a disciplinary repository for psychological science and neighboring disciplines. Accommodating 20 different digital research object (DRO) types, including articles, preprints, research data, code, supplements, preregistrations, tests and multimedia objects, PsychArchives provides a digital space that integrates all research-related content relevant to psychology. PsychArchives is committed to the FAIR principles, facilitating the findability, accessibility, interoperability and reusability of research and research data.
A service of the Inter-university Consortium for Political and Social Research (ICPSR), openICPSR is a self-publishing repository for social, behavioral, and health sciences research data. openICPSR is particularly well-suited for the deposit of replication data sets for researchers who need to publish their raw data associated with a journal article so that other researchers can replicate their findings.
Arch is an open access repository for the research and scholarly output of Northwestern University. Log in with your NetID to deposit, describe, and organize your research for public access and long-term preservation. We'll use our expertise to help you curate, share, and preserve your work.
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.
UNC Dataverse is an open-source repository software application for archiving, sharing, and accessing research data of all kinds. Each dataverse within the larger repository contains a multitude of datasets, and each dataset contains descriptive metadata and data files. UNC Dataverse is hosted by Odum Institute for Research in Social Science.
The focus of PolMine is on texts published by public institutions in Germany. Corpora of parliamentary protocols are at the heart of the project: Parliamentary proceedings are available for long stretches of time, cover a broad set of public policies and are in the public domain, making them a valuable text resource for political science. The project develops repositories of textual data in a sustainable fashion to suit the research needs of political science. Concerning data, the focus is on converting text issued by public institutions into a sustainable digital format (TEI/XML).
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 Universidad del Rosario Research data repository is an institutional iniciative launched in 2019 to preserve, provide access and promote the use of data resulting from Universidad del Rosario research projects. The Repository aims to consolidate an online, collaborative working space and data-sharing platform to support Universidad del Rosario researchers and their collaborators, and to ensure that research data is available to the community, in order to support further research and contribute to the democratization of knowledge. The Research data repository is the heart of an institutional strategy that seeks to ensure the generation of Findable, Accessible, Interoperable and Reusable (FAIR) data, with the aim of increasing its impact and visibility. This strategy follows the international philosophy of making research data “as open as possible and as closed as necessary”, in order to foster the expansion, valuation, acceleration and reusability of scientific research, but at the same time, safeguard the privacy of the subjects. The platform storage, preserves and facilitates the management of research data from all disciplines, generated by the researchers of all the schools and faculties of the University, that work together to ensure research with the highest standards of quality and scientific integrity, encouraging innovation for the benefit of society.
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Maenduar in Tupi means "to remember". The Maenduar repository, created by LARHUD is an institutional repository (IBICT) dedicated to research data in Digital Humanities and Humanities. The repository encompasses the production of LARHUD members and partners and extends to the public space as a public deposit repository. Researchers, professors, students linked to any institutions will be able to deposit their research data, understanding that Maenduar becomes, from this action, a public, national repository, dedicated to the production of knowledge in the Humanities in the face of the development of digital culture in all areas of the world. social world.
Apollo (previously DSpace@Cambridge) is the University of Cambridge’s Institutional Repository (IR), preserving and providing access to content created by members of the University. The repository stores a range of content and provides different levels of access, but its primary focus is on providing open access to the University’s research publications.
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.
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.