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<!doctype html>
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<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<link rel="stylesheet" type="text/css" media="screen" href="ourstylesheet.css">
<link rel="icon" type="image/x-icon" href="wombat-icon-web.ico">
<title>WOMBAT: Workshop organised by Monash Business Analytics Team</title>
</head>
<body>
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<div id="header_wrap" class="outer">
<header class="inner">
<img src="wombat-icon-web.png" align="right" width="300">
<h1 id="project_title"> Open the World with Open Source</h1>
<h2 id="project_tagline"> <a href="https://numbats.github.io/WOMBAT2024/"> Workshop Organised by the Monash Business Analytics Team (WOMBAT) </a> </h2>
</header>
</div>
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<div id="main_content_wrap" class="outer">
<section id="main_content" class="inner">
<hr>
<h2> Environment </h2>
<strong>Chair:</strong> Kate Saunders
<br><br>
This session runs from 10:30-12:00 and focuses on tools for working with environmental data. Speakers are:
<br><br>
<ul>
<li> <strong>Climate is What We Expect, Weather (Data) is What We Get Via APIs </strong> <br> <em> Adam Sparks,
Curtin University </em>
<p> No matter where we are, weather shapes our lives. We are all familiar with ordinary everyday weather
concerns, do I need an umbrella when I step out the door today or maybe how cold will it be, will I need to
wear a jacket later? Businesses use it to track long-term patterns and understand historical trends. Major
media organisations use historical weather data to tell stories by visualising the data to show the effects
of climate change to the public. Agricultural researchers use weather data in their analyses to help explain
experimental results or build complex models that simulate farming systems. And governments use the data to
prepare and plan for future disasters or understand seasonal trends to ensure adequate infrastructure is in
place. While the uses are often critical, and the data may be freely or openly available, getting the data
quickly and easily into R can be frustrating. There are 193 members of the World Meteorological Organisation
(WMO), many of which offer some sort of programmatic access to historical weather data or forecasted weather
data via APIs, but some do not, while there are other non-member organisations that do. I'll present the
good, the bad and the ugly of different weather data sources and getting the data wrangled and tamed ready
to go in your R session with what you need to think about for end users of the data when you make a weather
data API client R package to help make our world more understandable.
</p>
<ul>
<li>
<a href="https://coloradosun.com/2024/09/08/patrich-esch-ed-dean-jagers-ranchers-fraud-insurance/">Story from opening slide: “Wrecked rain gauges. Whistleblowers. Million-dollar payouts and manhunts. Then a Colorado crop fraud got really crazy”</a>
</li>
<li>
<a href="https://adamhsparks.codeberg.page/WOMBAT2024/@main/WOMBAT2024.html#/title-slide">Rendered slides</a>
</li>
<li>
<a href="https://codeberg.org/adamhsparks/WOMBAT2024/src/tag/WOMBAT">Slide repository</a>
</li>
<li>
<a href="https://doi.org/10.5281/zenodo.13974911">DOI of slides on Zenodo</a>
</li>
<li>
<a href = "https://adamhsparks.netlify.app/2024/06/02/plotting-perth-month-of-may-high-temperatures-with-weatheroz/">Plotting Perth month of May high temperatures with weatheroz</a>
</li>
</ul>
</li>
<li> <strong> Read, Manipulate and Plot Gridded Data with metR </strong> <br><em> Elio Campitelli, Monash
University </em>
<p> The metR package provides an assortment of tools for wrangling, plotting and analysing meteorological
field data. It has been developed from my own research needs, originally in response to a lack of available
tools. For example, a large number of functions are provided for plotting variations of filled contours,
which preceded the ggplot2 filled contour functions. Because meteorological field data is delivered in
NetCDF there is a function to read this type of file. Utility functions allow conversion between different
different longitude conventions. Principal components is a primary analysis tool, so there are functions for
this, along with various model fitting procedures. There are tools for imputation, finding anomalies and for
model diagnostics. Writing a package tailored to what you, individually need, can be useful for others:
philosophically, if I need it, probably others do too! </p>
</li>
<li> <strong> Open Air Quality directly in R with airpurifyr </strong> <br> <em> Michael Lydeamore, David Wu,
Jayani Lakshika </em>
<p> Air quality and pollution have emerged as critical research areas with implications across various policy
domains, extending beyond traditional climate-focused studies. Despite this growing interest, many projects
still rely on limited, ad-hoc datasets. I will introduce airpurifyr, a new R package designed to facilitate
access to the OpenAQ Web API, a freely available and semi-curated global database of air quality
measurements.
<p> In addition to providing an overview of the airpurifyr package, I will showcase research conducted by our
master's students, who have leveraged the OpenAQ API to enhance their data exploration skills and contribute
to the field of air quality analysis.
<p> By streamlining access to comprehensive air quality data, airpurifyr aims to empower researchers,
policymakers, and students alike, fostering more robust analysis and evidence-based decision-making in the
ongoing pursuit of cleaner, healthier air worldwide. </p>
<ul>
<li><a href = "https://slides.michaellydeamore.com/wombat-airpurifyr-2024">Slides are available on Michael's website</a></li>
<li><a href = "https://github.com/numbats/airpurifyr">airpurifyr package is available on GitHub</a></li>
</ul>
</li>
</ul>
<br><br>
</section>
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