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dc.contributor.authorPinheiro, Paulo
dc.contributor.authorSantos, Henrique
dc.contributor.authorLiang, Jason
dc.contributor.authorLiu, Yue
dc.contributor.authorRashid, Sabbir
dc.contributor.authorMcGuinness, Deborah
dc.contributor.authorBax, Marcello
dc.date.accessioned2022-02-18T02:33:59Z
dc.date.available2022-02-18T02:33:59Z
dc.date.issued2018-10-01
dc.identifier.other43
dc.identifier.urihttp://ceur-ws.org/Vol-2180/paper-49.pdf
dc.identifier.urihttps://hdl.handle.net/20.500.13015/4445
dc.description.abstractTo investigate the cause and progression of a phenomenon, such as chronic disease, it is essential to collect a wide variety of data that together explains the complex interplay of different factors, e.g., genetic, lifestyle, environmental and social. Sharing information between studies is therefore of paramount importance. However, data that needs to be analyzed must be appropriately integrated, conceptually aligned, and harmonized. This implies that data collection must be done either in a sufficiently similar or a sufficiently transparent way in order to support meaningful synthesis from different studies. We will demonstrate4,5 how the Human-Aware Data Acquisition (HADatAc) framework integrates and harmonizes data from multiple scientific studies and thus how to use it in interdisciplinary science investigations.
dc.relation.urihttps://tw.rpi.edu/project/hadatac
dc.subjectThe Human-Aware Data Acquisition Infrastructure (HADatAc)
dc.titleHADatAc: A Framework for Scientific Data Integration using Ontologies


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