Search: onr:"swepub:oai:lup.lub.lu.se:5184b347-e10d-4c9a-9f7b-a8ecb5a82d49" > FAIRVASC: A semanti...
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000 | 04395naa a2200361 4500 | |
001 | oai:lup.lub.lu.se:5184b347-e10d-4c9a-9f7b-a8ecb5a82d49 | |
003 | SwePub | |
008 | 220419s2022 | |||||||||||000 ||eng| | |
024 | 7 | a https://lup.lub.lu.se/record/5184b347-e10d-4c9a-9f7b-a8ecb5a82d492 URI |
024 | 7 | a https://doi.org/10.1016/j.compbiomed.2022.1053132 DOI |
040 | a (SwePub)lu | |
041 | a engb eng | |
042 | 9 SwePub | |
072 | 7 | a art2 swepub-publicationtype |
072 | 7 | a ref2 swepub-contenttype |
100 | 1 | a McGlinn, Krisu Trinity College Dublin4 aut |
245 | 1 0 | a FAIRVASC: A semantic web approach to rare disease registry integration |
264 | 1 | b Elsevier BV,c 2022 |
520 | a Rare disease data is often fragmented within multiple heterogeneous siloed regional disease registries, each containing a small number of cases. These data are particularly sensitive, as low subject counts make the identification of patients more likely, meaning registries are not inclined to share subject level data outside their registries. At the same time access to multiple rare disease datasets is important as it will lead to new research opportunities and analysis over larger cohorts. To enable this, two major challenges must therefore be overcome. The first is to integrate data at a semantic level, so that it is possible to query over registries and return results which are comparable. The second is to enable queries which do not take subject level data from the registries. To meet the first challenge, this paper presents the FAIRVASC ontology to manage data related to the rare disease anti-neutrophil cytoplasmic antibody (ANCA) associated vasculitis (AAV), which is based on the harmonisation of terms in seven European data registries. It has been built upon a set of key clinical questions developed by a team of experts in vasculitis selected from the registry sites and makes use of several standard classifications, such as Systematized Nomenclature of Medicine - Clinical Terms (SNOMED-CT) and Orphacode. It also presents the method for adding semantic meaning to AAV data across the registries using the declarative Relational to Resource Description Framework Mapping Language (R2RML). To meet the second challenge a federated querying approach is presented for accessing aggregated and pseudonymized data, and which supports analysis of AAV data in a manner which protects patient privacy. For additional security the federated querying approach is augmented with a method for auditing queries (and the uplift process) using the provenance ontology (PROV-O) to track when queries and changes occur and by whom. The main contribution of this work is the successful application of semantic web technologies and federated queries to provide a novel infrastructure that can readily incorporate additional registries, thus providing access to harmonised data relating to unprecedented numbers of patients with rare disease, while also meeting data privacy and security concerns. | |
650 | 7 | a MEDICIN OCH HÄLSOVETENSKAPx Klinisk medicinx Reumatologi och inflammation0 (SwePub)302102 hsv//swe |
650 | 7 | a MEDICAL AND HEALTH SCIENCESx Clinical Medicinex Rheumatology and Autoimmunity0 (SwePub)302102 hsv//eng |
650 | 7 | a NATURVETENSKAPx Data- och informationsvetenskapx Datavetenskap0 (SwePub)102012 hsv//swe |
650 | 7 | a NATURAL SCIENCESx Computer and Information Sciencesx Computer Sciences0 (SwePub)102012 hsv//eng |
700 | 1 | a Rutherford, Matthewu University of Glasgow4 aut |
700 | 1 | a Gisslander, Karlu Lund University,Lunds universitet,Reumatologi och molekylär skelettbiologi,Sektion III,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Rheumatology,Section III,Department of Clinical Sciences, Lund,Faculty of Medicine4 aut0 (Swepub:lu)ka7822gi |
700 | 1 | a Hederman, Lucyu Trinity College Dublin4 aut |
700 | 1 | a Little, Mark A.u Trinity health kidney centre,Trinity College Dublin4 aut |
700 | 1 | a O'Sullivan, Declanu Trinity College Dublin4 aut |
710 | 2 | a Trinity College Dublinb University of Glasgow4 org |
773 | 0 | t Computers in Biology and Medicined : Elsevier BVg 145q 145x 0010-4825 |
856 | 4 | u http://dx.doi.org/10.1016/j.compbiomed.2022.105313x freey FULLTEXT |
856 | 4 8 | u https://lup.lub.lu.se/record/5184b347-e10d-4c9a-9f7b-a8ecb5a82d49 |
856 | 4 8 | u https://doi.org/10.1016/j.compbiomed.2022.105313 |
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