  This paper presents a framework for assessing data and metadata quality
within Open Data portals. Although a few benchmark frameworks already exist for
this purpose, they are not yet detailed enough in both breadth and depth to
make valid statements about the actual discoverability and accessibility of
publicly available data collections. To address this research gap, we have
designed a quality framework that is able to evaluate data quality in Open Data
portals on dedicated and fine-grained dimensions, such as interoperability,
findability, uniqueness or completeness. Additionally, we propose quality
measures that allow for valid assessments regarding cross-portal findability
and uniqueness of dataset descriptions. We have validated our novel quality
framework for the German Open Data landscape and found out that metadata often
still lacks meaningful descriptions and is not yet extensively connected to the
Semantic Web.
