Combining Data Lake and Data Wrangling for Ensuring Data Quality in CRIS

Abstract

Today, researchers should be able to integrate ever-increasing amounts of data into their institutional database, such as Current Research Information Systems (CRIS), regardless of the source, format or size of research information. An effective mechanism should then be employed to ensure faster value creation from data of these organizations, respecting this increasing variety of data, i.e. heterogeneous data. The processing of electronic data plays a central role in modern society. Data in general is an elementary component of operational processes in companies and scientific organizations. They also form the basis for decisions. Poor quality research information may have a negative effect on results and decisions. The quality of research information or trustworthy and reliability of data are crucial. This includes the topic of data lake and data wrangling.