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Found 12 result(s)

The Perovskite Database Project

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The Perovskite Database Project aims at making all perovskite device data, both past and future, available in a form adherent to the FAIR data principles, i.e. findable, accessible, interoperable, and reusable.

NIST Data Discovery

NIST PDR

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Data products developed and distributed by the National Institute of Standards and Technology span multiple disciplines of research and are widely used in research and development programs by industry and academia. NIST's publicly available data sets showcase its committment to providing accurate, well-curated measurements of physical properties, exemplified by the Standard Reference Data program, as well as its committment to advancing basic research. In accordance with U.S. Government Open Data Policy and the NIST Plan for providing public access to the results of federally funded research data, NIST maintains a publicly accessible listing of available data, the NIST Public Dataset List (json). Additionally, these data are assigned a Digital Object Identifier (DOI) to increase the discovery and access to research output; these DOIs are registered with DataCite and provide globally unique persistent identifiers. The NIST Science Data Portal provides a user-friendly discovery and exploration tool for publically available datasets at NIST. This portal is designed and developed with data.gov Project Open Data standards and principles. The portal software is hosted in the usnistgov github repository.

Materials Cloud Archive

Materials Cloud

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FAIR & long-term storage of research data from computational materials science, or from experimental materials science that is of relevance to simulations. Complementary tools available to explore the full provenance of the calculations and to perform simulations or data analytics in the cloud.

Pacific Northwest National Laboratory DataHub: Scientific Data Repository

PNNL2

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Sharing and preserving data are central to protecting the integrity of science. DataHub, a Research Computing endeavor, provides tools and services to meet scientific data challenges at Pacific Northwest National Laboratory (PNNL). DataHub helps researchers address the full data life cycle for their institutional projects and provides a path to creating findable, accessible, interoperable, and reusable (FAIR) data products. Although open science data is a crucial focus of DataHub’s core services, we are interested in working with evidence-based data throughout the PNNL research community.

ColabFit Exchange

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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.

NoMaD Repository & Archive

Novel Materials Discovery

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The NOMAD Repository and Archive stands for open access of scientific materials data. It enables the confirmatory analysis of materials data, their reuse, and repurposing. All data is available in their raw format as produced by the underlying code (Repository) and in a common, machine-processable, and well-defined data format (Archive).

RODARE

Rossendorf Data Repository

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Rodare is the institutional research data repository at HZDR (Helmholtz-Zentrum Dresden-Rossendorf). Rodare allows HZDR researchers to upload their research software and data and enrich those with metadata to make them findable, accessible, interoperable and retrievable (FAIR). By publishing all associated research software and data via Rodare research reproducibility can be improved. Uploads receive a Digital Object Identfier (DOI) and can be harvested via a OAI-PMH interface.

NanoCommons Knowledge Base

NanoSolveIT Knowledge Base

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The NanoTox Knowlege Base provides access to Nanomaterials, their physico-chemical characterisations, toxicological assays and environmental data as well as computational model based descriptors.

ACEnano

Analytical and Characterisation Excellence in nanomaterial risk assessment

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The ACEnano Knowledge Infrastructure facilitates access and sharing of methodology applied in nanosafety, starting with nanomaterials characterisation protocols developed or optimised within the ACEnano project.

QsarDB

QSAR Data Base

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QSAR DataBank (QsarDB) is repository for (Quantitative) Structure-Activity Relationships ((Q)SAR) data and models. It also provides open domain-specific digital data exchange standards and associated tools that enable research groups, project teams and institutions to share and represent predictive in silico models.

CU Scholar

University of Colorado Boulder's institutional repository

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CU Scholar is an open access institutional repository supporting the research and teaching mission of the University of Colorado Boulder. It is intended to serve as a platform for preserving the research activities of members of the CU Boulder community and for providing public access to that research. CU Scholar is maintained by the University Libraries.

Kadi4Mat

Kadi4Mat instance KIT+

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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.