  The collection, transfer and integration of research information into
different research Information systems can result in different data errors that
can have a variety of negative effects on data quality. In order to detect
errors at an early stage and treat them efficiently, it is necessary to
determine the clean-up measures and the new techniques of data cleansing for
quality improvement in research institutions. Thereby an adequate and reliable
basis for decision-making using an RIS is provided, and confidence in a given
dataset increased. In this paper, possible measures and the new techniques of
data cleansing for improving and increasing the data quality in research
information systems will be presented and how these are to be applied to the
Research information.
