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Found 10 result(s)
The Materials Project produces one of the world's foremost databases of computed information about inorganic, crystalline materials, along with providing powerful web-based apps to help analyze this information to help the design of novel materials. Access is provided free-of-charge with an API available and under a permissive license.
ResearchWorks Archive is the University of Washington’s digital repository (also known as “institutional repository”) for disseminating and preserving scholarly work. ResearchWorks Archive can accept any digital file format or content (examples include numerical datasets, photographs and diagrams, working papers, technical reports, pre-prints and post-prints of published articles).
The Arizona State University (ASU) Research Data Repository provides a platform for ASU-affiliated researchers to share, preserve, cite, and make research data accessible and discoverable. The ASU Research Data Repository provides a permanent digital identifier for research data, which complies with data sharing policies. The repository is powered by the Dataverse open-source application, developed and used by Harvard University. Both the ASU Research Data Repository and the KEEP Institutional Repository are managed by the ASU Library to ensure research produced at Arizona State University is discoverable and accessible to the global community.
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."
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.
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.
A Research Data Repository (RDR) for researchers in India. Any registered researchers of Indian Universities can manage their research data on eSHODHMANTHAN-RDR free of cost. This research data repository is configured to provide free of cost research data management services to existing and forthcoming researchers throughout their research life. eSHODHMANTHAN-RDR is powered by Dataverse project of Harvard University
the Data Hub is a community-run catalogue of useful sets of data on the Internet. You can collect links here to data from around the web for yourself and others to use, or search for data that others have collected. Depending on the type of data (and its conditions of use), the Data Hub may also be able to store a copy of the data or host it in a database, and provide some basic visualisation tools.
In its 10-year tenure, NCED has made major contributions to the growth of Earth-Surface Dynamics (ESD) through direct research in three Integrated Programs (IP) of Streams, Watersheds and Deltas. These contributions include: Establishment of experimental geomorphology and stratigraphy as a major source of insight in ESD, Integration of quantitative methods from engineering, physics, and applied math into ESD, Advances in the coupling of life, especially vegetation, and landscape dynamics, Integration of a variety of novel methods from stochastic hydrology, including nonlocal transport and multifractal spatial signatures, into ESD, Advances in providing the scientific basis for restoring streams, and Integration of subsurface structure and stratigraphic records into understanding present-day delta dynamics. All data created or compiled by NCED-funded scientists is archived here.