Mit der voranschreitenden Digitalisierung von Forschung und Lehre steigt die Zahl an Software-Lösungen, die an wissenschaftlichen Einrichtungen entstehen und zur Verarbeitung wissenschaftlicher Daten genutzt werden. Die unter dem Stichwort Open Science geforderte Zugänglichkeit und Nachnutzung von wissenschaftlichen Ergebnissen kann in vielen Fachgebieten nur sichergestellt werden, wenn Forschungsdaten und Programmcode offen zugänglich gemacht werden.
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.
OA2020 is an initiative building on the Berlin Declaration on Open Access to Knowledge in the Sciences and Humanities, which has been embraced by more than 560 signatory institutions.
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O. Gundersen, und S. Kjensmo. Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), Association for the Advancement of Artificial Intelligence, (2018)
N. Micic, D. Neagu, I. Campean, und 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..