Starting in January 2016 and funded for three years by the German Research Foundation (DFG), project CONQUAIRE – Continuous Quality Control for Research Data to Ensure Reproducibility will focus on reproducibility and quality control during the research process in an institutional setting.
The Cross-Domain Interoperability Framework (CDIF) is a set of guidelines and practice for using domain-agnostic standards to support the interoperability and reusability of FAIR data, especially across domain and institutional boundaries. It is being developed in response to the need for agreements on the use of standards in FAIR
CyVerse is funded by the National Science Foundation’s Directorate for Biological Sciences. We are a dynamic virtual organization led by the University of Arizona to fulfill a broad mission that spans our partner institutions: Texas Advanced Computing Center, Cold Spring Harbor Laboratory, and the University of North Carolina at Wilmington. CyVerse provides life scientists with powerful computational infrastructure to handle huge datasets and complex analyses, thus enabling data-driven discovery. Our extensible platforms provide data storage, bioinformatics tools, image analyses, cloud services, APIs, and more.
The full-featured DKRZ long term archiving service LTA WDCC (World Data Centre for Climate) offers long term archiving for datasets relevant for climate and Earth System research.
Why is it so important to cite data? Books and journal articles have long benefited from an infrastructure that makes them easy to cite, a key element in the process of research and academic discourse. We believe that you should cite data in just the same way that you can cite other sources of information, such as articles and books.
We want to help make data more accessible and more useful; our purpose is to develop and support methods to locate, identify and cite data and other research objects.
This document specifies a method of organising file-based data with associated metadata, known as DataCrate in both human and machine readable formats, based on the schema.org linked-data vocabularly, supplemented with terms from the SPAR ontologies and [PCDM] where schema.org does not have coverage. The motivation for this work comes from the research domain.
A DataCrate is a dataset a set of files contained in a single directory. There are two ways of organizing a DataCrate.
For working data or data that does not need to be distributed with checksums, a Working DataCrate is a plain-old directory containing payload data files, with two metadata files at the root; one for humans and one for machines.
For distribution, or archiving; where integrity is important, a Bagged DataCrate is a BagIt bag conforming to the DataCrate BagIt profile with the payload files in the /data directory. A Bagged DataCrate has a clear separation between metadata and payload, and can be integrity-checked using the checksums in the BagIt manifest.
Data Observation Network for Earth (DataONE) is the foundation of new innovative environmental science through a distributed framework and sustainable cyberinfrastructure that meets the needs of science and society for open, persistent, robust, and secure access to well-described and easily discovered Earth observational data.
The 'German Network for Bioinformatics Infrastructure – de.NBI' is a national, academic and non-profit infrastructure supported by the Federal Ministry of Education and Research providing bioinformatics services to users in life sciences research and biomedicine in Germany and Europe. The partners organize training events, courses and summer schools on tools, standards and compute services provided by de.NBI to assist researchers to more effectively exploit their data.