A. Seeland. Software, (2020)Related to: Selent, B., Kraus, H., Hansen, N., Schembera, B., Seeland, A. & Iglezakis, D. (forthcoming). Management of Research Data in Computational Fluid Dynamics and Thermodynamics. In: Proceedings der E-Science-Tage 2019.
O. Gundersen, und S. Kjensmo. Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), Association for the Advancement of Artificial Intelligence, (2018)
M. Gärtner, U. Hahn, und S. Hermann. Language Technologies for the Challenges of the Digital Age, Seite 284-291. Cham, Springer International Publishing, (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..
D. Dolzycka, K. Biernacka, K. Helbig, und P. Buchholz. Zenodo, (März 2019)Diese Publikation wurde im Rahmen des Verbundprojekts "FDMentor" vom Bundesministerium für Bildung und Forschung gefördert (Förderkennzeichen 16FDM010 und 16FDM011)..
M. Gärtner, U. Hahn, und S. Hermann. Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), Seite 563--570. Paris, France, European Language Resources Association (ELRA), (Mai 2018)
