Use case

ChildObesity

Reference	Userreq.ChildObesity
High-level reqs	Techreq.R
Proposed by	Iain Buchan

	Taverna 1.3	Taverna 2.0
Priority

Overview

There has been a dramatic increase in obesity in all age groups, in all parts of the world. The increase accelerated across the 1990s and continues to rise today. It is reported in children as young as two years. The cause(s) of this global epidemic of obesity are largely unknown, and its consequences are difficult to estimate. We have shown that fast-growing children are more susceptible than slow-growing children to the 'obesogenic environment'. The long-term consequences of interactions of growth and the obesity epidemic are unknown. It is therefore very important to present and future public health to run large-scale epidemiological studies of obesity in childhood. Many relevant data were collected as part of routine child health surveillance in the 1990s and additional obesity monitoring data are being collected from children now. In order to analyse these data efficiently, a systematic epidemiological workflow system needs to be developed.

Overall Goals

1) Identify data sources and governance requirements (e.g. data sharing agreements).

2) Deconstruct the epidemiological investigations that have been or are expected to be repeated with data from different localities - reflecting not only upon conventional epidemiological practice but also upon generic scientific method and how the research process can be described as a 'research object'.

3) Specify the meta-data for governance, data quality, statistical and epidemiological analysis.

4) Specify data cleaning/preparation, visualisation and statistical analysis workflows - summarise these in R scripts.

5) Build a workflow system for the analysis of Greater Manchester schools' obesity surveillance data using myGrid services - evaluate this against conventional, less automated alternatives.

Required services

Security; Data; Provenance; R; Mapping

Workflow outline

Verify workflow application and core data requirements with the owner

Upload data

Apply first pass cleaning rules

Notify owner of workflow and abort if data quality below threshold(s)

Standardise height, weight and BMI data for age and sex using the LMS formula and the 1990 British Growth Reference

Apply second pass cleaning (within 5 standard deviations of SDS scores)

Notify owner of workflow and abort if data quality below threshold(s)

Store data quality meta-data

Request meta-data about any non-standard fields that the owner has uploaded

Classify records by the International Obesity Taskforce definitions

Summarise data overall and by sub-groups (e.g. gender) - statistics, charts [optional: and thematic maps / geographical information systems such as CommonGIS^?]

Make standard group comparisons and any owner-specified comparisons

Store statistical process and any critical result summaries into the statistical meta-data

Search for similar workflow runs within the given governance family and summarise the current run against these

Request and store additional interpretation meta-data from the owner

Appendix