SAA 2017 Workshop: Using R for Archaeological Data Analysis, Mapping, and Visualization

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<h1>SAA 2017 Workshop: Using R for Archaeological Data Analysis, Mapping, and Visualization</h1> <p>Presented by: Matthew Harris (AECOM-Burlington, mr.ecos@gmail.com), Ben Marwick (University of Washington, bmarwick@uw.edu)</p> <h2>What is this about?</h2> <p>A revolution in social science, the humanities, and other scientific disciplines is reshaping the way researchers understand, analyze, and present their findings. Features of this revolution include open science, reproducibility, advancement in many analytic and modeling techniques, public presentation (pubarch, sci-comm), and a general data-scientific approach that is built on collaboration and transparency. Applied to the practice of archaeology, be it academic or contract, this approach has the benefit introducing the appeal of our research to a much wider audience, validating our work by making the process open, and giving our work a legacy by proving the data and analysis for others to study and repeat in the future. Additional individual benefits include, better organization of one’s data, documentation of analytical process, ease of archiving, and the ability to confidently duplicate an analysis when new data is collected. </p> <p>The core of this approach is the ability to write computer code to document, automate, and make explicit the methodical process. To that end, the R language for statistical computing is an open-source language widely used by academic researchers and data scientists to achieve these goals. R is a fully functional computer language that has been designed to be an interactive environment for the process of conducting scientific analysis. High quality and cutting edge statistical analysis, mapping, GIS, data visualisation, and communication are possible with the R language. Further, R is supported by a massive and active community of users who contribute to the core code, the available packages, workshops, and endless assistance. </p> <p>This 4-hour workshop seeks to introduce the audience to the capabilities of R, conduct hands-on demonstration of coding basics, introduce project examples, and allow participants to practice on their own data. The mission of this workshop is to teach enough coding basics and provide numerous motivating examples so that attendees are able to take the first steps of coding their own research in R. We will be using the teaching methods of the Data Carpentry curriculum (<a href="http://www.datacarpentry.org/" rel="nofollow">http://www.datacarpentry.org/</a>) and adapting some of their lesson plans for this workshop (Marwick is an accredited Data Carpentry instructor). </p> <h2>Who should attend?</h2> <p>No previous experience with R, coding, or statistics is necessary; just curiosity and a willingness to learn. Enrollment in this workshop is open to anyone including students of all levels, researchers, CRM professionals, and educators. Students are encouraged to register and are offered a reduced rate of $##. </p> <h2>What will you learn?</h2> <p>From this course, you will learn what R is and some of the things you can do with it. You will see numerous examples of what other archaeologists do with R and ideas for how it can be applied to your data and research questions. You will learn the basics of the R language syntax, the conventions of data processing, and the most commonly used packages within the R ecosystem. At a higher level, you will hear the benefits of using code and reproducible methods. Finally, you will also start to build a network of other archaeologists who share your interest in these methods. The specific schedule is as follows:</p> <p>• Getting data into R: We’ll show you how to import common file types, and how you can save time by easily importing thousands of files in an instant <br> • Cleaning data: We’ll look at some very common and powerful programming methods for cleaning data to prepare it for analysis and visualization. <br> • Basic data analysis: We’ll work though some of the most frequently used methods of data analysis, which you can easily adapt to your own purposes. <br> • Visualisation: We’ll show you how to generate several types of plots to explore your data, and how to prepare those plots for publication <br> • Mapping: We’ll explore some of the methods for making maps and doing GIS analysis using R </p> <p>If you have something specific that you really want to know about with R, just send us an email to let us know. We’ll see if we can fit it in! To see an annotated list of many of the things R can do especially for archaeologists, visit <a href="https://github.com/benmarwick/ctv-archaeology/" rel="nofollow">https://github.com/benmarwick/ctv-archaeology/</a></p> <h2>How to prepare?</h2> <p>To participate in this workshop you must bring a laptop with a web browser (e.g. Chrome/Firefox/Internet Explorer) and you must have working copies of the following software:</p> <p>• R – download from <a href="https://cloud.r-project.org/" rel="nofollow">https://cloud.r-project.org/</a> <br> • RStudio – download from <a href="https://www.rstudio.com/products/rstudio/download3/#download" rel="nofollow">https://www.rstudio.com/products/rstudio/download3/#download</a></p> <p>If you installed R on your laptop in the past, it’s important that you get the most up-to-date version from the URL above before coming to this workshop.</p> <p>We’ll provide additional R packages and archaeological datasets during the workshop. </p> <p>If you have any questions or problems with these instructions, don’t hesitate to send us an email. </p> <h2>What to bring?</h2> <p>Bring snacks,questions, and a friend or two. We find that workshops go a lot better if people come in groups, e.g., 4-5 people from one lab, half a dozen from another department or institute, etc., so that they are less inhibited about asking questions, and can support each other afterwards. So while individual sign-ups are welcome, we encourage you to sign-up with a friend. Optionally, you may wish to bring a file of your own data. Ideally this is a simple and well-organised Excel spreadsheet with clearly labelled columns of measurements or counts of artefacts. You will use this to practice the programming methods that we learn in the workshop (unfortunately we probably will not have time during the workshop for very detailed or specialized analyses of your data). We will provide data files for everyone to practice with, so don’t worry if you don’t bring any data of your own. </p> <h2>How to sign up?</h2> <p>Please register your interest via this form: <a href="https://goo.gl/forms/b5pySZqTUrjgl4Aa2" rel="nofollow">https://goo.gl/forms/b5pySZqTUrjgl4Aa2</a></p> <h2>Where/When:</h2> <p>At the 2017 SAA, TBD</p>
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