Pre-Analysis Steps for GIS: Data Cleaning
In this presentation, we will cover the top 5 questions researchers bring to librarians when trying to integrate GIS methods into their data workflows. We will build a baseline building-block knowledge of GIS data and its idiosyncrasies, and talk about some common problems these formats present when you are trying to wrangle GIS data for your project. This presentation will be software agnostic; we will be focusing on the concepts behind GIS data and common data cleaning workflows. We will be demoing these concepts using a number of different software — Google Sheets, OpenRefine, QGIS, R, and Python. You do not need any of this software on your computer to participate in the workshop, it will be a slide-show style format, with time for questions.
Participants will also come away with example code snippets for both Python and R, modeling how to work through common GIS and data cleaning problems. No knowledge of GIS is required. This presentation is designed for those looking to be more intentional about the ways they use GIS data in programmatic environments.
This event was developed in partnership with the Harvard Kennedy School (HKS) Library, and will be held on the HKS campus, in Rubenstein 414.
Registration is required for this event; please find the registration link.