Open Data and the Status Quo -- A Fine-Grained Evaluation Framework for Open Data Quality and an Analysis of Open Data portals in Germany

TL;DR

This paper introduces a detailed evaluation framework for assessing the quality of open data and metadata in portals, focusing on dimensions like interoperability and findability, validated through an analysis of German Open Data portals.

Contribution

It presents a novel, fine-grained quality assessment framework for open data portals, addressing gaps in existing benchmarks and enabling cross-portal quality comparisons.

Findings

Metadata often lacks meaningful descriptions

Limited connection of datasets to the Semantic Web

Identified quality gaps in German Open Data portals

Abstract

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.