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Found 48 result(s)
>>>>!!!<<< As stated 2017-06-27 The website http://researchcompendia.org is no longer available; repository software is archived on github https://github.com/researchcompendia >>>!!!<<< The ResearchCompendia platform is an attempt to use the web to enhance the reproducibility and verifiability—and thus the reliability—of scientific research. we provide the tools to publish the "actual scholarship" by hosting data, code, and methods in a form that is accessible, trackable, and persistent. Some of our short term goals include: To expand and enhance the platform including adding executability for a greater variety of coding languages and frameworks, and enhancing output presentation. To expand usership and to test the ResearchCompendia model in a number of additional fields, including computational mathematics, statistics, and biostatistics. To pilot integration with existing scholarly platforms, enabling researchers to discover relevant Research Compendia websites when looking at online articles, code repositories, or data archives.
The Deep Blue Data repository is a means for University of Michigan researchers to make their research data openly accessible to anyone in the world, provided they meet collections criteria. Submitted data sets undergo a curation review by librarians to support discovery, understanding, and reuse of the data.
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On this server you'll find 127 items of primary data of the University of Munich. Scientists / students of all faculties of LMU and of institutions that cooperate with the LMU are invited to deposit their research data on this platform.
Research data from University of Pretoria. This data repository facilitates data publishing, sharing and collaboration of academic research, allowing UP to manage and in some cases showcase its data to the wider research community. Previously UPSpace (https://repository.up.ac.za/) was used for both datasets and research outputs. Now UP Research Data Repository is dedicated for datasets.
For datasets big and small; Store your research data online. Quickly and easily upload files of any type and we will host your research data for you. Your experimental research data will have a permanent home on the web that you can refer to.
Open Research Exeter (ORE) is the University of Exeter's repository for all types of research, including research papers, research data and theses. Research in ORE can be viewed and downloaded freely by anyone, anywhere: researchers, students, industry, business and the wider public. ORE's content includes journal articles, conference papers, working papers, reports, book chapters, videos, audio, images, multimedia research project outputs, raw data and analysed data. ORE's content is securely stored, managed and preserved to ensure free, permanent access.
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FDAT is a research data repository hosted by the University of Tübingen, designed to facilitate long-term archiving and publication of research data. Managed by the Information, Communication and Media Center (IKM), it primarily caters to the humanities and social sciences, while welcoming researchers from all scientific disciplines at the university. Committed to high-quality data management, FDAT emphasizes the importance of adhering to the FAIR Data Principles, promoting findability, accessibility, interoperability, and reusability of the research data it contains.
University of Alberta Dataverse is a service provided by the University of Albert Library to help researchers publish, analyze, distribute, and preserve data and datasets. Open for University of Alberta-affiliated researchers to deposit data.
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Science Data Bank is an open generalist data repository developed and maintained by the Chinese Academy of Sciences Computing and Network Information Center (CNIC). It promotes the publication and reuse of scientific data. Researchers and journal publishers can use it to store, manage and share science data.
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University of Warsaw Research Data Repository aims to collect, archive, preserve and make available all types of research data. Storing and making data available is possible for users affiliated with the University of Warsaw, Poland, or those involved in projects carried out in partnership with the University of Warsaw. Browsing and downloading publicly available research data is open to all interested.
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Edmond is the institutional repository of the Max Planck Society for public research data. It enables Max Planck scientists to create citable scientific assets by describing, enriching, sharing, exposing, linking, publishing and archiving research data of all kinds. Further on, all objects within Edmond have a unique identifier and therefore can be clearly referenced in publications or reused in other contexts.
The Brown Digital Repository (BDR) is a place to gather, index, store, preserve, and make available digital assets produced via the scholarly, instructional, research, and administrative activities at Brown.
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The Federated Research Data Repository (FRDR) is a bilingual publishing platform for sharing and preserving Canadian research data. It is a curated, general-purpose repository, custom built for large datasets.
The ASEP Data Repository is an institutional multidisciplinary on-line repository that stores scientific outputs - bibliographic records, full texts and datasets of the institutional authors from The Czech Academy of Sciences. The repository is hosted by Library of the Czech Academy of Sciences. Data that are stored in database are accessible in the on-line catalogue. Each dataset has its own description and metadata according to international standards.
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The AMUReD Institutional Research Data Repository of the Adam Mickiewicz University in Poznan (UAM) collects and provides access to digital versions of research data collected, processed or produced as part of the scientific research or developmental work of UAM employees.The AMUReD Repository is part of the AMU Research Portal, with University Library in Poznan as the operating unit. Depositing data is possible after logging into the AMU Research Portal, according to the attached instructions. The AMUReD repository is open, and research data are made available in three models: open (Open Access), embargo (Embargo) and closed (Restricted Access). The detailed rules of the AMUReD repository are defined in the Regulations. The AMUReD repository complies with the FAIR Principles. Each dataset is given a unique DOI identifier. The AMUReD repository complies with the FAIR Principles. Each dataset is given a unique DOI identifier. The prefix for DOIs is doi:10.60629. It is possible to choose a Creative Commons license for shared datasets.
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Borealis, the Canadian Dataverse Repository, is a bilingual, multidisciplinary, secure, Canadian research data repository, supported by academic libraries and research institutions across Canada. Borealis supports open discovery, management, sharing, and preservation of Canadian research data. Borealis is available to researchers who are affiliated with a participating Canadian university or research organization and their collaborators. Borealis is a shared service provided in partnership with Canadian regional academic library consortia, institutions, research organizations, and the Digital Research Alliance of Canada, with technical infrastructure hosted by Scholars Portal and the University of Toronto Libraries.
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Swedish National Data Service (SND) is a research data infrastructure designed to assist researchers in preserving, maintaining, and disseminating research data in a secure and sustainable manner. The SND Search function makes it easy to find, use, and cite research data from a variety of scientific disciplines. Together with an extensive network of almost 40 Swedish higher education institutions and other research organisations, SND works for increased access to research data, nationally as well as internationally.
The SURF Data Repository is a user-friendly web-based data publication platform that allows researchers to store, annotate and publish research datasets of any size to ensure long-term preservation and availability of their data. The service allows any dataset to be stored, independent of volume, number of files and structure. A published dataset is enriched with complex metadata, unique identifiers are added and the data is preserved for an agreed-upon period of time. The service is domain-agnostic and supports multiple communities with different policy and metadata requirements.
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CINES is the French national long-term preservation service provider for Higher Education and Research: more than 20 institutions (universities, librairies, labs) archive their digital heritage at CINES so that it's preserved over time in a secure, dedicated environment. This includes documents such as PhD theses or publications, digitized ancient/rare books, satellite imagery, 3D/vidéos/image galleries, datasets, etc.
FAIRsharing is a web-based, searchable portal of three interlinked registries, containing both in-house and crowdsourced manually curated descriptions of standards, databases and data policies, combined with an integrated view across all three types of resource. By registering your resource on FAIRsharing, you not only gain credit for your work, but you increase its visibility outside of your direct domain, so reducing the potential for unnecessary reinvention and proliferation of standards and databases.
Here you can find out more about Lancaster’s world-class research activities, view details of publications, outputs and awards and make contact with our researchers.
IDEALS is an institutional repository that collects, disseminates, and provides persistent and reliable access to the research and scholarship of faculty, staff, and students at the University of Illinois at Urbana-Champaign. Faculty, staff, graduate students, and in some cases undergraduate students, can deposit their research and scholarship directly into IDEALS. Departments can use IDEALS to distribute their working papers, technical reports, or other research material. Contact us at https://www.ideals.illinois.edu/feedback for more information.
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A machine learning data repository with interactive visual analytic techniques. This project is the first to combine the notion of a data repository with real-time visual analytics for interactive data mining and exploratory analysis on the web. State-of-the-art statistical techniques are combined with real-time data visualization giving the ability for researchers to seamlessly find, explore, understand, and discover key insights in a large number of public donated data sets. This large comprehensive collection of data is useful for making significant research findings as well as benchmark data sets for a wide variety of applications and domains and includes relational, attributed, heterogeneous, streaming, spatial, and time series data as well as non-relational machine learning data. All data sets are easily downloaded into a standard consistent format. We also have built a multi-level interactive visual analytics engine that allows users to visualize and interactively explore the data in a free-flowing manner.