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dc.contributor.authorNavarro Gallinad, Alberten
dc.contributor.authorOrlandi, Fabrizioen
dc.contributor.authorO'Sullivan, Declanen
dc.date.accessioned2021-12-06T16:40:29Z
dc.date.available2021-12-06T16:40:29Z
dc.date.createdDecember 6?8, 2021en
dc.date.issued2021en
dc.date.submitted2021en
dc.identifier.citationAlbert Navarro-Gallinad, Fabrizio Orlandi, Declan O'Sullivan ., Enhancing Rare Disease Research with Semantic Integration of Environmental and Health Data, The 10th International Joint Conference on Knowledge Graphs (IJCKG?21), Thailand, December 6?8, 2021, ACM, 2021en
dc.identifier.otherYen
dc.identifier.urihttp://hdl.handle.net/2262/97660
dc.descriptionPUBLISHEDen
dc.descriptionThailanden
dc.description.abstractKnowledge Graph (KG) approaches are increasingly being used for data integration processes to combine clinical data with other data sources. Health Data Researchers (HDR) could benefit from these technologies since they require additional types of data outside the health sector, like environmental data, to better understand the extrinsic factors that influence health outcomes in rare disease research. However, using and directly navigating the combined data in the KG can be an obstacle for HDRs. To address this problem, the Semantic Environmental and Rare Disease data Integration Frame- work (SERDIF) was designed to hide the complexities for these re- searchers when exploring linked environmental observations with clinical data using a KG approach. The framework was evaluated by HDRs for a case study on Anti-neutrophil cytoplasm antibody (ANCA)-associated vasculitis (AAV) in Ireland, and promising us- ability and effectiveness results were observed. HDRs studying AAV were able to access, explore and export environmental re- lated data to be used as input for their statistical models. SERDIF has the potential to be a solution for HDRs, who require a flexible methodology to integrate environmental data with longitudinal and geospatial diverse clinical data, in their hypothesis validation of environmental factors for rare disease research.
dc.publisherACMen
dc.rightsYen
dc.subjectSemantic Data Integrationen
dc.subjectKnowledge Graphen
dc.subjectUsability Testingen
dc.titleEnhancing Rare Disease Research with Semantic Integration of Environmental and Health Dataen
dc.title.alternativeThe 10th International Joint Conference on Knowledge Graphs (IJCKG?21)en
dc.typeConference Paperen
dc.contributor.sponsorEuropean Union (EU)en
dc.contributor.sponsorEuropean Union (EU)en
dc.contributor.sponsorScience Foundation Ireland (SFI)en
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/anavarroen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/orlandifen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/osulldpsen
dc.identifier.rssinternalid235307en
dc.identifier.doihttps://doi.org/10.1145/3502223.3502226en
dc.relation.ecprojectidinfo:eu-repo/grantAgreement/EC/FP7/713567
dc.relation.ecprojectidinfo:eu-repo/grantAgreement/EC/FP7/813545
dc.rights.ecaccessrightsopenAccess
dc.contributor.sponsorGrantNumber813545en
dc.contributor.sponsorGrantNumber713567en
dc.contributor.sponsorGrantNumber13/RC/2106_Pen
dc.subject.TCDTagEnvironmental Healthen
dc.subject.TCDTagKnowledge Graphsen
dc.subject.TCDTagrare diseasesen


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