Open the World with Open Source

Environment

• Climate is What We Expect, Weather (Data) is What We Get Via APIs
  Adam Sparks, Curtin University

  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.

• Read, manipulate and plot gridded data with metR
  Elio Campitelli, Monash University

  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!

• Opening Pacific Data: opportunities and challenges for domain experts and data scientists
  Giulio Valentino Dalla Riva, Pacific Community

  The Pacific Community (SPC) offers open access to high quality, domain-expert curated, regularly updated Pacific data through a variety of access points. In particular, the SPC Pacific Data Hub .stat portal is accessible both through a point-and-click interface and a developer-friendly API (with SDK in R, Python, JS). In this talk I will present the Pacific Data Hub ecosystem, and highlight the opportunities offered by the SPC data portal for both the data user and the developer.