The growing digitization and networking process within our society has a large influence on all aspects of everyday life. Large amounts of data are being produced permanently, and when these are analyzed and interlinked they have the potential to create new knowledge and intelligent solutions for economy and society. Big Data can make important contributions to the technical progress in our societal key sectors and help shape business. What is needed are innovative technologies, strategies and competencies for the beneficial use of Big Data to address societal needs.
BioSchemas relies and extends from schema.org and aims to reuse existing standards and reach consensus among a wide number of life sciences organizations and communities.
Among the many online learning resources that the DCC offers digital curators are high-level briefing papers and legal watch, standards watch and technology watch papers.
Our digital library of resources is free to use and contains everything you need to engage effectively in digital curation and data preservation activities.
CESAER - the Conference of European Schools for Advanced Engineering Education and Research - is a non-profit international association of leading European universities of science and technology and engineering schools/faculties at comprehensive universities and university colleges.
The Coalition for Networked Information (CNI) is dedicated to supporting the transformative promise of digital information technology for the advancement of scholarly communication and the enrichment of intellectual productivity.
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.
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.
A. Goodman, A. Pepe, A. Blocker, C. Borgman, K. Cranmer, M. Crosas, R. Di Stefano, Y. Gil, P. Groth, M. Hedstrom and 5 other author(s). (2014)cite arxiv:1401.2134Comment: Accepted in PLOS Computational Biology. This paper was written collaboratively, on the web, in the open, using Authorea. The living version of this article, which includes sources and history, is available at http://www.authorea.com/3410/.