Forensic Ancestry Inference: Data Requirements, Analysis Methods, and Interpretation of Results

2020 ◽  
pp. 225-240
Author(s):  
Ozlem Bulbul ◽  
Kenneth K. Kidd
2012 ◽  
Vol 21 (01) ◽  
pp. 34-43 ◽  
Author(s):  
S. de Lusignan ◽  
P. Krause ◽  
G. Michalakidis ◽  
M. Vicente ◽  
S. Thompson ◽  
...  

SummaryTo perform a requirements analysis of the barriers to conducting research linking of primary care, genetic and cancer data.We extended our initial data-centric approach to include socio-culturalandbusinessrequirements.Wecreatedreferencemodels of core data requirements common to most studies using unified modelling language (UML), dataflow diagrams (DFD) and business process modelling notation (BPMN). We conducted a stakeholder analysis and constructed DFD and UML diagrams for use cases based on simulated research studies. We used research output as a sensitivity analysis.Differences between the reference model and use cases identified study specific data requirements. The stakeholder analysis identified: tensions, changes in specification, some indifference from data providers and enthusiastic informaticians urging inclusion of socio-cultural context. We identified requirements to collect information at three levels: microdata items, which need to be semantically interoperable, meso-the medical record and data extraction, and macro-the health system and socio-cultural issues. BPMN clarified complex business requirements among data providers and vendors; and additional geographical requirements for patients to be represented in both linked datasets. High quality research output was the norm for most repositories.Reference models provide high-level schemata of the core data requirements. However, business requirements’ modelling identifies stakeholder issues and identifies what needs to be addressed to enable participation.


2006 ◽  
Vol 79 (2) ◽  
pp. 273-289 ◽  
Author(s):  
Alistair Sutcliffe ◽  
George Papamargaritis ◽  
Liping Zhao

2013 ◽  
Vol 12 (22) ◽  
pp. 6600-6604
Author(s):  
Liu Jiajia ◽  
Xu Shiwei ◽  
Yu Wen ◽  
Ahmed Abdul-gafa ◽  
Zhu Mengshuai

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