SWISH: Scientific Workflow and Integration Software for Health

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SWISH: Scientific Workflow and Integration Software for Health
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Scientific Workflow and Integration Software for Health (SWISH)
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Dr Charmian Bennett and Dr Keith Dear from the Australian National University's Research School of Population Health, talk about SWISH -- open source software that enables easier access and merging of large datasets on population and health.
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i'm dr. sharmion Bennett I'm an epidemiologist at the Australian National University not part of a research team that's looking at the impacts of climate change and human health the Australian national data
service ground has allowed us to develop a scientific workflow system to access and merge large datasets on our environment population and health and we built our workflows using Kepler record our workflow system swish which stands for scientific workflow an integration software for health and it's freely available to other researchers from our website to assist the impacts of climate change on health you need to gather a large amount of data including whether
definitions of extreme weather events population data mortality data including the cause of death and all within a consistent spatial framework and all of these steps have to happen before you actually get to the analysis of the health impacts linked to climate change you can download complete work flows
from our website that will set up your connection to the extreme weather events database in this example the actor get
with it SLA connects to the database to locate daily weather data in this statistical local area of your choice double-click on the string constant box and enter the name of the SLA that you want in this example we're looking at kaylene then click committable the second string constant shows you where the resulting file will be saved in this case on the C Drive in the temp folder when you're done click the Run button in the toolbar and you will see the word executing appear in the bottom left corner when the results window appears scroll down and check that a CSV file with the suburb name has been created this week flow text the doubt will be
obtained in the previous example which calculates how many days had an average temperature of above 35 degrees you can use the search function to locate specific actors to complete this web flow it needs one more input using the string constant actor youth in drag and drop the actor until woot closed space and double-click to edit the parameters in this case our value is 35 degrees then connect this box to the greater than actor using the connector arrows to explore the many swish actors go to the components window and open the folder called my work clothes click the small plus sign to find the green actor icon then drag and drop into your workflow here we are adding a nectar to the workflow to display our results at the end when all of the actors are connected click on the Run button in the toolbar the results are produced in the CSV file which opens here in a text box but can easily be opened in other statistical programs like stata and our
accessing data often requires high level programming expertise using swish can help reduce those barriers to data access by providing a user-friendly drag-and-drop interface swoosh week flows are a single file so it's very easy to share with other researchers this can help us with collaborative research and improve the reproducibility of results in addition swish also packages multiple steps using Stata and are into a single executable flowchart the documents you're working as you go
Keith dear I'm a biostatistician an
epidemiologist at the Australian National University in 2007 2008 the
Garneau Climate Change review team asked a group of us here at insa the national center for epidemiology and population health to look at how health impacts of climate change might pan out in Australia out of 2100 to do this I use
several kinds of data from different sources the demographic breakdown of the Australian population by age sex and location around the country daily records of mortality which are collected within each state and the daily weather records collected by the Bureau of Meteorology
merging these various sources of data into a final data set that I could use for a statistical analysis was complicated I did this initially back in 2007 using scripts in the statistical package data which I wrote specifically for the purpose the final script in
stata that did this operation was quite long several hundred lines of stated code and it took me a lot of time to debug it make sure that I was reasonably confident he was correct and even when I was confident myself it was difficult to communicate it to other potential users of my methods they would essentially have to start again from scratch five years on were now in the process of updating and revising this analysis done back in 2007 2008 and this time I have available to me the swish package of data management tools I can see at least three advantages of using this package over the way I did it back then first of all it's just easier to write the code that means it's easier for me to debug I can spend less time and effort making sure that it's correct and I can have more confidence that it's correct secondly it means that I can modify the analyses I can try out different ways of doing the analysis during the data preparation and the analyses and this means that we can be more sure that we're using optimal efficient methods for the work and finally and I think most importantly it means that the methods can be communicated more easily to others it's intrinsically better documented and it means that we can communicate the methods we used so that others can use them perhaps improve upon them there are five main benefits to
using the switch system to access and merge data sets first of all it improves data access by providing a drag-and-drop interface rather than relying on complex programming you can create executable workflows that integrate both documentation and execution third workflows are easy to share for collaborative research in teaching and training the workflows are also easy to modify an update with new data or to change the spatial scale lastly swish workflows allow you to incorporate existing procedures and analyses and use your preferred statistical packages the switch system is free open source software you can find and download the switch tools and tutorials from our product side and there's some more information about our project at our blog