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UID:submissions.pasc-conference.org_PASC24_sess152_msa217@linklings.com
SUMMARY:Using Data Journey Modelling to Understand Barriers and Bottleneck
 s in Workflows Using Health and Environment Data
DESCRIPTION:Minisymposium\n\nPauline Karega (University of Manchester)\n\n
 Climate change is a major problem in the world. Changes brought about by t
 he Industrial Revolution resulted in an overall increase in global average
  temperatures, and air quality due to increased greenhouse gas emissions. 
 These changes have directly and indirectly been linked to health. To clear
 ly see the impact that climate change is having on health, we need to comb
 ine health and environment data. Health data exists in a variety of format
 s, including ambulatory data, prescription data, hospital admissions, and 
 environmental data equally exists in several formats, including near real 
 time satellite data, direct measurements of key climate variables from net
 works of weather stations, and more. Data journey modelling predicts place
 s of high cost and risk when existing data needs to move to a new developm
 ent, investigating the movement of data between key stakeholders including
  storage databases, individuals and more. Integrating health and environme
 nt data is crucial for multiple climate impact studies, but data format, a
 ccess, and use in both fields' present different challenges. This study ma
 kes use of the data journey modelling technique to highlight the challenge
 s and overall cost and risk. We display the data journey of integrated hea
 lth and environment data instances.\n\nDomain: Applied Social Sciences and
  Humanities, Engineering, Computational Methods and Applied Mathematics\n\
 nSession Chair: Jim Willenbring (Sandia National Laboratories)
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