Exploring the use of topological data analysis to automatically detect data quality faults.

Data quality problems may occur in various forms in structured and semi-structured data sources. This paper details an unsupervised method of analyzing data quality that is agnostic to the semantics of the data, the format of the encoding, or the internal structure of the dataset. A distance function is used to transform each record of a dataset into an n-dimensional vector of real numbers, which effectively transforms the original data into a high-dimensional point cloud.

OOSTT: a Resource for Analyzing the Organizational Structures of Trauma Centers and Trauma Systems.

Organizational structures of healthcare organizations has increasingly become a focus of medical research. In the CAFÉ project we aim to provide a web-service enabling ontology-driven comparison of the organizational characteristics of trauma centers and trauma systems. Trauma remains one of the biggest challenges to healthcare systems worldwide.