Scientific domains vary by the tools and instruments used, the way data are collected and managed, and even how results are analyzed and presented. As advocates of open science practices, it’s important that we understand the common obstacles to scientific workflow across many domains. The COS team visits scientists in their labs and out in the field to discuss and experience their research processes first-hand. We experience the day-to-day of researchers and do our own investigating. We find where data loss occurs, where there are inefficiencies in workflow, and what interferes with reproducibility. These field trips inspire new tools and features for the Open Science Framework to support openness and reproducibility across scientific domains.
Last week, the team visited the Monticello Department of Archaeology to dig a little deeper (bad pun) into the workflow of archaeologists, as well as learn about the Digital Archaeological Archive of Comparative Slavery (DAACS). Derek Wheeler, Research Archaeologist at Monticello, gave us a nice overview of how the Archaeology Department surveys land for artifacts. Shovel test pits, approximately 1 foot square, are dug every 40 feet on center as deep as anyone has dug in the past (i.e., down to undisturbed clay). If artifacts are found, the shovel test pits are dug every 20 feet on center. At Monticello, artifacts are primarily man-made items like nails, bricks or pottery. The first 300 acres surveyed contained 12,000 shovel test pits -- and that’s just 10% of the total planned survey area. That’s a whole lot of holes, and even more data.
Fraser Neiman, Director of Archaeology at Monticello, describes the work being done to excavate on Mulberry Row - the industrial hub of Jefferson’s agricultural industry.
At the Mulberry Row excavation site, Fraser Neiman, Director of Archaeology, explained the meticulous and painstaking process of excavating quadrats, small plots of land isolated for study. Within a quadrat, there exist contexts - stratigraphic units. Any artifacts found within a context are carefully recorded on a context sheet - what the artifact is, its location within the quadrat, along with information about the fill (dirt, clay, etc.) in the context. The fill itself is screened to pull out smaller artifacts the eye may not catch. All of the excavation and data collection at the Mulberry Row Reassessment is conducted following the standards of the Digital Archaeological Archive of Comparative Slavery (DAACS). Standards developed by DAACS help archaeologists in the Chesapeake region to generate, report, and compare data from 20 different sites across the region in a systematic way. Without these standards, archiving and comparing artifacts from different sites would be extremely difficult.
Researchers make careful measurements at the Monticello Mulberry Row excavation site, while recording data on a context sheet.
The artifacts, often sherds, are collected by context and taken to the lab for washing, labeling, analysis and storage. After washing, every sherd within a particular context is labeled with the same number and stored together. All of the data from the context sheets, as well as photos of the quadrants and sherds, are carefully input into DAACS following the standards set out in the DAACS Cataloging Manual. There is an enormous amount of manual labor associated with preparing and curating each artifact. Jillian Galle, Project Manager of DAACS, described the extensive training users must undergo in order to deposit their data in the archive to ensure the standards outlined by the Cataloging Manual are kept. This regimented process ensures the quality and consistency of the data- and thus its utility. The result is a publicly available dataset of the history of Monticello for researchers of all kinds to examine this important site in America’s history.
These sherds have been washed and numbered to denote their context.
Our trip to Monticello Archaeology was eye-opening, as none of us had any practical experience with archaeological research or data. The impressive DAACS protocols and standards represent an important aspect of all scientific research - the ability to accurately capture large amounts of data in a systematic, thoughtful way - and then share it freely with others.