Summary and Schedule
Research data is most valuable when others can find it, understand it, trust it and reuse it, long after the project that created it has ended. This module covers the principles of curating and sharing geospatial data: describing data with metadata and documentation, preserving it for the long term, publishing it in repositories with persistent identifiers and licenses, and protecting the people and places that location data can reveal.
The module is conceptual: it has no programming or software exercises. Each episode includes examples and challenges with solutions.
| Episode | What you will learn |
|---|---|
| Introduction to Data Curation | What curation is, the curation lifecycle, public access policies and the FAIR principles |
| Metadata | Kinds of metadata, essential geospatial elements, and standards such as ISO 19115, DataCite and DDI |
| Documentation | README files, codebooks, provenance, and citing data |
| Preservation | Durable formats, checksums, the OAIS model, trustworthy repositories and very large data |
| Sharing and Publishing Data | Choosing a repository, DOIs, licenses, access levels, and the FAIR and CARE principles |
| Ethics and Sensitive Location Data | Re-identification, aggregation and geomasking, sensitive places, consent and review |
Prerequisites
- No prior GIS or programming experience is needed
- The Data Management module is helpful background, especially its episodes on file formats and organizing data
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.
| Setup Instructions | Download files required for the lesson | |
| Duration: 00h 00m | 1. Introduction to Data Curation |
What is data curation, and how does it differ from data management and
data cleaning? Why does curation matter for research, and for geospatial data in particular? What are the stages of the curation lifecycle? What do funders and federal policies now expect? |
| Duration: 00h 40m | 2. Metadata |
What is metadata, and what kinds are there? What should a metadata record for a geospatial dataset include? Which metadata standards are used for geospatial and social science data? How can I create metadata in QGIS? |
| Duration: 01h 30m | 3. Documentation |
What documentation should accompany a dataset? What goes in a README file? How do I document variables, sources and processing steps? |
| Duration: 02h 15m | 4. Preservation |
Why does digital data need active preservation? Which file formats are safest for the long term? How can I tell whether a file has changed or been corrupted? What makes a repository trustworthy? How are very large datasets stored and moved? |
| Duration: 03h 00m | 5. Sharing and Publishing Data |
Where should I share my research data? What is a DOI, and why does it matter? Which license should I choose for my data? How do the FAIR and CARE principles guide sharing? |
| Duration: 03h 50m | 6. Ethics and Sensitive Location Data |
Why can location data identify people, even without names? How can geospatial data be shared while protecting privacy? What other kinds of location data are sensitive? What ethical and legal obligations apply? |
| Duration: 04h 40m | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.
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 and to explore the repositories and standards they link to.
Optional, for exploring:
- QGIS (https://qgis.org), to look at its metadata editor (Layer Properties > Metadata)
- An ORCID iD (https://orcid.org), free, if you plan to publish data or articles
- Access to your institution’s research repository; at Purdue, PURR (https://purr.purdue.edu/)
To practice the challenges, it helps to have a dataset of your own (or one from another module) to document and plan for sharing.