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Found 69 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.
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data.public.lu is Luxembourg's central and official platform for data from the public sector, from research institutes and the private sector.
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.
OLAC, the Open Language Archives Community, is an international partnership of institutions and individuals who are creating a worldwide virtual library of language resources by: (i) developing consensus on best current practice for the digital archiving of language resources, and (ii) developing a network of interoperating repositories and services for housing and accessing such resources. The OLAC system has 2016 been integrated with the Linguistic Linked Open Data Cloud.
The CLARIN­/Text+ repository at the Saxon Academy of Sciences and Humanities in Leipzig offers long­term preservation of digital resources, along with their descriptive metadata. The mission of the repository is to ensure the availability and long­term preservation of resources, to preserve knowledge gained in research, to aid the transfer of knowledge into new contexts, and to integrate new methods and resources into university curricula. Among the resources currently available in the Leipzig repository are a set of corpora of the Leipzig Corpora Collection (LCC), based on newspaper, Wikipedia and Web text. Furthermore several REST-based webservices are provided for a variety of different NLP-relevant tasks The repository is part of the CLARIN infrastructure and part of the NFDI consortium Text+. It is operated by the Saxon Academy of Sciences and Humanities in Leipzig.
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.
-----<<<<< The repository is no longer available. This record is out-dated. >>>>>----- GEON is an open collaborative project that is developing cyberinfrastructure for integration of 3 and 4 dimensional earth science data. GEON will develop services for data integration and model integration, and associated model execution and visualization. Mid-Atlantic test bed will focus on tectonothermal, paleogeographic, and biotic history from the late-Proterozoicto mid-Paleozoic. Rockies test bed will focus on integration of data with dynamic models, to better understand deformation history. GEON will develop the most comprehensive regional datasets in test bed areas.
A data repository and social network so that researchers can interact and collaborate, also offers tutorials and datasets for data science learning. "data.world is designed for data and the people who work with data. From professional projects to open data, data.world helps you host and share your data, collaborate with your team, and capture context and conclusions as you work."
Government of Yukon open data provides an easy way to find, access and reuse the government's public datasets. This service brings all of the government's data together in one searchable website. Our datasets are created and managed by different government departments. We cannot guarantee the quality or timeliness of all data. If you have any feedback you can get in touch with the department that produced the dataset. This is a pilot project. We are in the process of adding a quality framework to make it easier for you to access high quality, reliable data.
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Welcome to the National Yang Ming Chiao Tung University Dataverse research data knowledge management website, where you can learn how to obtain, upload, cite and explore research data in the National Yang Ming Chiao Tung University Dataverse.
The Harvard Dataverse Repository is a free data repository open to all researchers from any discipline, both inside and outside of the Harvard community, where you can share, archive, cite, access, and explore research data. Each individual Dataverse collection is a customizable collection of datasets (or a virtual repository) for organizing, managing, and showcasing datasets.
The Energy Data Centre holds information relating to energy research, focused on the UK. It has a research data catalogue, information on publications resulting from the UK Energy Research Centre and the Energy Technologies Institute and energy research related grants.
Kaggle is a platform for predictive modelling and analytics competitions in which statisticians and data miners compete to produce the best models for predicting and describing the datasets uploaded by companies and users. This crowdsourcing approach relies on the fact that there are countless strategies that can be applied to any predictive modelling task and it is impossible to know beforehand which technique or analyst will be most effective.
As one of the cornerstones of the U.S. Geological Survey's (USGS) National Geospatial Program, The National Map is a collaborative effort among the USGS and other Federal, State, and local partners to improve and deliver topographic information for the Nation. It has many uses ranging from recreation to scientific analysis to emergency response. The National Map is easily accessible for display on the Web, as products and services, and as downloadable data. The geographic information available from The National Map includes orthoimagery (aerial photographs), elevation, geographic names, hydrography, boundaries, transportation, structures, and land cover. Other types of geographic information can be added within the viewer or brought in with The National Map data into a Geographic Information System to create specific types of maps or map views.
IEEE DataPort™ is a universally accessible online data repository created, owned, and supported by IEEE, the world’s largest technical professional organization. It enables all researchers and data owners to upload their dataset without cost. IEEE DataPort makes data available in three ways: standard datasets, open access datasets, and data competition datasets. By default, all "standard" datasets that are uploaded are accessible to paid IEEE DataPort subscribers. Data owners have an option to pay a fee to make their dataset “open access”, so it is available to all IEEE DataPort users (no subscription required). The third option is to host a "data competition" and make a dataset accessible for free for a specific duration with instructions for the data competition and how to participate. IEEE DataPort provides workflows for uploading data, searching, and accessing data, and initiating or participating in data competitions. All datasets are stored on Amazon AWS S3, and each dataset uploaded by an individual can be up to 2TB in size. Institutional subscriptions are available to the platform to make it easy for all members of a given institution to utilize the platform and upload 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.
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.
Academic Torrents is a distributed data repository. The academic torrents network is built for researchers, by researchers. Its distributed peer-to-peer library system automatically replicates your datasets on many servers, so you don't have to worry about managing your own servers or file availability. Everyone who has data becomes a mirror for those data so the system is fault-tolerant.
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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.