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.
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.
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.
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.
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 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.
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.
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.
The HydroShare architecture is a stack of storage and computation, web services, and user applications. A content management system, Django+Mezzanine, provides user interface, search, social media functions, and services. iRODS provides content storage. A web browser is the main interface to HydroShare, however a web services applications programming interface (API) supports access through other hydrologic modeling systems, and the architecture separates the interface layer and services layer exposing all functionality through these web services.
N. Micic, D. Neagu, I. Campean, and E. Habib Zadeh. (2017)Every industry has significant data output as a product of their working process, and with the recent advent of big data mining and integrated data warehousing it is the case for a robust methodology for assessing the quality for sustainable and consistent processing. In this paper a review is conducted on Data Quality (DQ) in multiple domains in order to propose connections between their methodologies. This critical review suggests that within the process of DQ assessment of heterogeneous data sets, not often are they treated as separate types of data in need of an alternate data quality assessment framework. We discuss the need for such a directed DQ framework and the opportunities that are foreseen in this research area and propose to address it through degrees of heterogeneity..