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Found 11 result(s)
With the Program EnviDat we develop a unified and managed access portal for WSL's rich reservoir of environmental monitoring and research data. EnviDat is designed as a portal to publish, connect and search across existing data but is not intended to become a large data centre hosting original data. While sharing of data is centrally facilitated, data management remains decentralised and the know-how and responsibility to curate research data remains with the original data providers.
VertNet is a NSF-funded collaborative project that makes biodiversity data free and available on the web. VertNet is a tool designed to help people discover, capture, and publish biodiversity data. It is also the core of a collaboration between hundreds of biocollections that contribute biodiversity data and work together to improve it. VertNet is an engine for training current and future professionals to use and build upon best practices in data quality, curation, research, and data publishing. Yet, VertNet is still the aggregate of all of the information that it mobilizes. To us, VertNet is all of these things and more.
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Kadi4Mat instance for use at the Karlsruhe Institute of Technology (KIT) and for cooperations, including the Cluster of Competence for Solid-state Batteries (FestBatt), the Battery Competence Cluster Analytics/Quality Assurance (AQua), and more. Kadi4Mat is the Karlsruhe Data Infrastructure for Materials Science, an open source software for managing research data. It is being developed as part of several research projects at the Institute for Applied Materials - Microstructure Modelling and Simulation (IAM-MMS) of the Karlsruhe Institute of Technology (KIT). The goal of this project is to combine the ability to manage and exchange data, the repository , with the possibility to analyze, visualize and transform said data, the electronic lab notebook (ELN). Kadi4Mat supports a close cooperation between experimenters, theorists and simulators, especially in materials science, to enable the acquisition of new knowledge and the development of novel materials. This is made possible by employing a modular and generic architecture, which allows to cover the specific needs of different scientists, each utilizing unique workflows. At the same time, this opens up the possibility of covering other research disciplines as well.
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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BACTIBASE contains calculated or predicted physicochemical properties of bacteriocins produced by both Gram-positive and Gram-negative bacteria. The information in this database is very easy to extract and allows rapid prediction of relationships structure/function and target organisms of these peptides and therefore better exploitation of their biological activity in both the medical and food sectors.
The OpenNeuro project (formerly known as the OpenfMRI project) was established in 2010 to provide a resource for researchers interested in making their neuroimaging data openly available to the research community. It is managed by Russ Poldrack and Chris Gorgolewski of the Center for Reproducible Neuroscience at Stanford University. The project has been developed with funding from the National Science Foundation, National Institute of Drug Abuse, and the Laura and John Arnold Foundation.
RUresearch Data Portal is a subset of RUcore (Rutgers University Community Repository), provides a platform for Rutgers researchers to share their research data and supplementary resources with the global scholarly community. This data portal leverages all the capabilities of RUcore with additional tools and services specific to research data. It provides data in different clusters (research-genre) with excellent search facility; such as experimental data, multivariate data, discrete data, continuous data, time series data, etc. However it facilitates individual research portals that include the Video Mosaic Collaborative (VMC), an NSF-funded collection of mathematics education videos for Teaching and Research. Its' mission is to maintain the significant intellectual property of Rutgers University; thereby intended to provide open access and the greatest possible impact for digital data collections in a responsible manner to promote research and learning.
OpenStreetMap (https://www.openstreetmap.org/export#map=6/51.324/10.426) is built by a community of mappers that contribute and maintain data about roads, trails, cafés, railway stations, and much more, all over the world. Planet.osm is the OpenStreetMap data in one file.
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Adattár stores research data associated with the University of Debrecen, and provides services such as data transfer, storage and sharing. As a result, research data is easily accessible and more visible to the scientific community in each field, following disciplinary standards. Adattár aims to foster best practices of findability and accessibility of research data, and will provide guidance regarding issues of access, privacy, and copyright. Adattár aims to be a widely used, inter-disciplinary, trusted platform for managing, sharing, and archiving research data created by the researchers associated with the university.
The RESID Database of Protein Modifications is a comprehensive collection of annotations and structures for protein modifications including amino-terminal, carboxyl-terminal and peptide chain cross-link post-translational modifications.