Baskent University multidisciplinary healthcare teams have performed periodic patient satisfaction surveys in order to identify strengths and problem areas, formulate the quality improvement objectives and monitor progress towards achieving these objectives. However, patient satisfaction survey results are often highly positive. In these cases, improving care is not easy because measures are not sensitive enough to changes. Therefore a more sensitive measurement tool based on the SERVQUAL scale was developed. The authors believe that patient opinions are extremely important because they provide information that is not necessarily emphasized by managers or health care professionals, resulting in a more complete assessment of past performance and a clearer road map for future action.

The paper demonstrates the use of the SERVQUAL scale in measuring the functional quality of the hospitals assessed.

Ensuring data quality in Linked Open Data is a complex process as it consists of structured information supported by models, ontologies and vocabularies and contains queryable endpoints and links. In this paper, the authors first propose an objective assessment framework for Linked Data quality. The authors build upon previous efforts that have identified potential quality issues but focus only on objective quality indicators that can measured regardless on the underlying use case. Secondly, the authors present an extensible quality measurement tool that helps on one hand data owners to rate the quality of their datasets, and on the other hand data consumers to choose their data sources from a ranked set. The authors evaluate this tool by measuring the quality of the LOD cloud. The results demonstrate that the general state of the datasets needs attention as they mostly have low completeness, provenance, licensing and comprehensibility quality scores.

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