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Found 194 result(s)
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Anyone can use open data from the Maple Ridge Open Data Portal at no cost. Download raw data and share your insights with your community or build new applications that serve specific users
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Our open data portal allows the public to access Pickering's data more easily and encourages collaboration and innovation in the community
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The Whitby GeoHub is a place to discover, explore, search and download apps, maps and location based data about the Town.
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Multidisciplinary research data repository, hosted by DTU, the Danish Technical University.
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The BAW is a research institute for the Federal Ministry of Transport and acts as an advisor to the federal government for issues of waterway engineering. In this role the BAW consumes and produces large volumes of data and information. As part of the implementation of Open Data legislation and in support of Open Data and Open Access principles, the BAW provides access to scientific data together with their metadata. The BAW-Datenrepository was developed as a point of access for hydraulic engineering experts, contractors and customers of the BAW as well as the general public. It is a source for quality-assured information and provides standardised, long-term access to waterway engineering data. The BAW-Datenrepository supports the targeted search for information and data and gives direct access to them. By publishing its scientific data, the BAW promotes transparency in public discourse as well as accountability of public administration enabling the data to create value beyond the BAW.
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MIDAS is a national research data repository. The aim of MIDAS is to collect, process, store and analyse research data and other relevant information in all fields of knowledge, enabling free, easy and convenient access to the data via the Internet. MIDAS provides services for registered and unregistered users: students, listeners, academics, researchers, scientists, research administrators, other actors of the research and studies ecosystem, and all individuals interested in research data. MIDAS consists of the MIDAS portal and MIDAS user account. The MIDAS portal is a public space accessible to anyone interested in discovering and viewing published research Data and their metadata, whereas MIDAS user account is available to registered users only. MIDAS is managed by Vilnius University.
Digital Rocks is a data portal for fast storage and retrieval of images of varied porous micro-structures. It has the purpose of enhancing research resources for modeling/prediction of porous material properties in the fields of Petroleum, Civil and Environmental Engineering as well as Geology. This platform allows managing and preserving available images of porous materials and experiments performed on them, and any accompanying measurements (porosity, capillary pressure, permeability, electrical, NMR and elastic properties, etc.) required for both validation on modeling approaches and the upscaling and building of larger (hydro)geological models. Starting September 2021 we charge fees for publishing larger projects; projects < 2GB remain free: see user agreement https://www.digitalrocksportal.org/user-agreement/
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Macquarie University's Institutional Research Data Repository (RDR) allows researchers to upload, publish, search and download research data. The RDR promotes collaboration, data sharing and discovery amongst researchers globally according to FAIR data principles. The RDR is based on Figshare for Institutions, which has been specifically tailored to suit the needs of the Macquarie University research community.
OLOS is a Swiss-based data management portal tailored for researchers and institutions. Powerful yet easy to use, OLOS works with most tools and formats across all scientific disciplines to help researchers safely manage, publish and preserve their data. The solution was developed as part of a larger project focusing on Data Life Cycle Management (dlcm.ch) that aims to develop various services for research data management. Thanks to its highly modular architecture, OLOS can be adapted both to small institutions that need a "turnkey" solution and to larger ones that can rely on OLOS to complement what they have already implemented. OLOS is compatible with all formats in use in the different scientific disciplines and is based on modern technology that interconnects with researchers' environments (such as Electronic Laboratory Notebooks or Laboratory Information Management Systems).
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ISTA Research Explorer is an online digital repository of multi-disciplinary research datasets as well as publications produced at IST Austria, hosted by the Library. ISTA researchers who have produced research data associated with an existing or forthcoming publication, or which has potential use for other researches, are invited to upload their dataset for sharing and safekeeping. A persistent identifier and suggested citation will be provided.
UltraViolet is part of a suite of repositories at New York University that provide a home for research materials, operated as a partnership of the Division of Libraries and NYU IT's Research and Instruction Technology. UltraViolet provides faculty, students, and researchers within our university community with a place to deposit scholarly materials for open access and long-term preservation. UltraViolet also houses some NYU Libraries collections, including proprietary data collections.
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CRAN is a network of ftp and web servers around the world that store identical, up-to-date, versions of code and documentation for R. R is ‘GNU S’, a freely available language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical techniques: linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering, etc. Please consult the R project homepage for further information.
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DIAS aims at collecting and storing earth observation data; analyzing such data in combination with socio-economic data, and converting data into information useful for crisis management with respect to global-scale environmental disasters, and other threats; and to make this information available within Japan and overseas.
The FigShare service for University of Auckland, New Zealand was launched in January 2015 and allows researchers to store, share and publish research data. It helps the research data to be accessible by storing Metadata alongside datasets. Additionally, every uploaded item recieves a Digital Object identifier (DOI), which allows the data to be cited. If there are any ethical or copyright concerns about publishing a certain dataset, it is possible to publish the metadata associated with the dataset to help discoverability while sharing the data itself via a private channel through manual approval.
<<<!!!<<< 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 University of Amsterdam (UvA) and the Amsterdam University of Applied Sciences (AUAS/HvA) cooperate to connect academic research with the insights and experiences from professional practice, and together the UvA and AUAS offer students a wide range of education pathways.
Provided by the University Libraries, KiltHub is the comprehensive institutional repository and research collaboration platform for research data and scholarly outputs produced by members of Carnegie Mellon University and their collaborators. KiltHub collects, preserves, and provides stable, long-term global open access to a wide range of research data and scholarly outputs created by faculty, staff, and student members of Carnegie Mellon University in the course of their research and teaching.
GigaDB primarily serves as a repository to host data and tools associated with articles published by GigaScience Press; GigaScience and GigaByte (both are online, open-access journals). GigaDB defines a dataset as a group of files (e.g., sequencing data, analyses, imaging files, software programs) that are related to and support a unit-of-work (article or study). GigaDB allows the integration of manuscript publication with supporting data and tools.
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.
ETH Data Archive is ETH Zurich's long-term preservation solution for digital information such as research data, digitised content, archival records, or images. It serves as the backbone of data curation and for most of its content, it is a “dark archive” without public access. In this capacity, the ETH Data Archive also archives the content of ETH Zurich’s Research Collection which is the primary repository for members of the university and the first point of contact for publication of data at ETH Zurich. All data that was produced in the context of research at the ETH Zurich, can be published and archived in the Research Collection. An automated connection to the ETH Data Archive in the background ensures the medium to long-term preservation of all publications and research data. Direct access to the ETH Data Archive is intended only for customers who need to deposit software source code within the framework of ETH transfer Software Registration. Open Source code packages and other content from legacy workflows can be accessed via ETH Library @ swisscovery (https://library.ethz.ch/en/).