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BioMed Research International
Volume 2017, Article ID 8327980, 13 pages
Research Article

Linked Registries: Connecting Rare Diseases Patient Registries through a Semantic Web Layer

1University of Aveiro, DETI/IEETA, Aveiro, Portugal
2Galician Research and Development Center in Advanced Telecommunications (GRADIANT), Pontevedra, Spain
3National Center for Rare Diseases, Istituto Superiore di Sanità, Rome, Italy
4Leiden University Medical Centre (LUMC), Leiden, Netherlands
5International Centre for Life, Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK
6Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Universitat Pompeu Fabra (UPF), Barcelona, Spain
7Institute of Rare Diseases Research, ISCIII, SpainRDR and CIBERER, Madrid, Spain
8John Walton Muscular Dystrophy Research Centre, Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK
9The European Huntington’s Disease Network, University Hospital of Ulm, Ulm, Germany
10Department of Neurology, University Hospital of Ulm, Ulm, Germany
11Karolinska Institutet, Solna, Sweden
12Institute of Medical Genetics, Charité Universitätsmedizin Berlin, Berlin, Germany

Correspondence should be addressed to Pedro Sernadela;

Received 3 February 2017; Revised 11 June 2017; Accepted 2 October 2017; Published 29 October 2017

Academic Editor: Peyman Björklund

Copyright © 2017 Pedro Sernadela et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Patient registries are an essential tool to increase current knowledge regarding rare diseases. Understanding these data is a vital step to improve patient treatments and to create the most adequate tools for personalized medicine. However, the growing number of disease-specific patient registries brings also new technical challenges. Usually, these systems are developed as closed data silos, with independent formats and models, lacking comprehensive mechanisms to enable data sharing. To tackle these challenges, we developed a Semantic Web based solution that allows connecting distributed and heterogeneous registries, enabling the federation of knowledge between multiple independent environments. This semantic layer creates a holistic view over a set of anonymised registries, supporting semantic data representation, integrated access, and querying. The implemented system gave us the opportunity to answer challenging questions across disperse rare disease patient registries. The interconnection between those registries using Semantic Web technologies benefits our final solution in a way that we can query single or multiple instances according to our needs. The outcome is a unique semantic layer, connecting miscellaneous registries and delivering a lightweight holistic perspective over the wealth of knowledge stemming from linked rare disease patient registries.