This exercise is best suited to those with an interest in archaeological survey, archaeological data collection, or using mindful observation skills for archaeology and daily life. Users should have a basic understanding of observation and recording methods, such as handwritten, audio, or video recording, but previous experience with archaeology or data collection is not required.
This page provides access to the resource in two ways. The first is through a series of PDFs that represent the completed Data Story. The PDFs include:
The Road Most Traveled is a single-exercise Data Story, so the entirety of the necessary text is within the Observation Guide. The text is also available through the Digital Data Stories code repository on Codeberg. These markdown files represent the source material for the text and primary images within the PDFs, minus additional formatting, and with only a general placement of images. The markdown files may be altered and forked from the Codeberg repository for custom use in different contexts. This code represents our commitment to open science and transparency in our process.
These materials, either through the PDFs or the code, are designed to be used synergistically. However, any piece of this Data Story may be used separately or re-ordered according to the requirements of the individual or to specific educational goals. In addition, this Data Story references Gabbing about Gabii: Going from Notes to Data to Narrative, specifically, the Notes to Data section of that tutorial. The Road Most Traveled resources are available free to use under a Creative Commons Attribution-ShareAlike (CC BY-SA 4.0) license. The resources for Gabbing About Gabii are under a Creative Commons Attribution-ShareAlike (CC BY-SA 2.0) license.
Thank you so much for utilizing our educational resources! This Digital Data Story is currently in an open peer review stage. If you have the time, please consider contributing an open peer review to our ongoing process. This Digital Data Story will move to the published stage after revision based on peer reviewer feedback. Such updates will be noted here, and will be first available through the code repository prior to PDF updating.
First published: November 2023