Summary and Setup
Every geospatial project depends on data that is organized, documented, stored safely and checked for errors. This module covers the principles of managing geospatial data during a research project: how spatial data is structured, which formats and coordinate systems to use, how to design a dataset before collecting it, how to organize, version and back up files, and how to judge data quality.
The module is conceptual: it has no programming or software exercises, though it refers to QGIS where that helps. Each episode includes examples and challenges with solutions.
| Episode | What you will learn |
|---|---|
| Introduction to Data Management | The research data lifecycle, why geospatial data needs extra care, and data management plans |
| Geospatial Data Models | Vector and raster data, topology, resolution, and choosing a representation |
| Geospatial File Formats | Shapefile, GeoPackage, GeoJSON, GeoTIFF and others, and which to use when |
| Coordinate Reference Systems | Datums, geographic and projected systems, EPSG codes, and defining versus reprojecting |
| Designing Your Data | Data dictionaries, field types, domains, unique IDs and relationships |
| Organizing, Versioning and Backing Up | Folder structures, file names, portable projects, version control and the 3-2-1 rule |
| Data Quality | Elements of spatial data quality, geometry errors, and quality checks |
Prerequisites
- No prior GIS or programming experience is needed
- Familiarity with spreadsheets and with files and folders on a computer
The companion Data Curation module covers what happens so data can be reused after a project ends: metadata, documentation, preservation, sharing and ethics.
This module is part of Enabling the Geospatial Turn in the Social Sciences, a set of training modules developed at Purdue University with support from the National Science Foundation.
This module is theory only: there is nothing to install and no data to download. You need only a web browser to read the episodes.
Some episodes refer to QGIS, a free and open-source GIS, to show where a setting or tool can be found. If you would like to follow along, you can install it from https://qgis.org (choose the Long Term Release). The other modules in this curriculum (Data Collection, Data Analysis and Data Visualization) include hands-on QGIS and Python exercises.
To practice the challenges, it helps to have:
- a spreadsheet program, for drafting data dictionaries
- a project of your own (or an imagined one) to plan as you go