Networking Archaeological Data and Communities (NADAC), our Institute for Advanced Topics in the Digital Humanities funded by the National Endowment for the Humanities (NEH), held its second workshop on the topic of Data in the Field.
Building on the lessons of cleaning messy data, February’s workshop focused on the earliest stage of the data lifecycle: data collection in the field. The “field” includes many contexts of data acquisition such as archaeological excavation and survey, lab analyses and sampling, collections cataloging and inventory work, and specialist studies of new or existing collections. NADAC Scholars offered a range of expertise within each of these domains that contributed to the workshop’s goals: 1) understanding how paper and/or digital data collection forms guide the types of data that are collected, and 2) how to create paper and/or digital data collection forms for individual research projects that incorporate attributes of data quality.
With these destinations in mind, workshop faculty Anne Austin and Sarah Kansa charted a course for shipshape data that are interoperable, accessible, and consistent across contexts and specialities. An especially important consideration is that field data are reusable and accessible to both current and future researchers. This target group includes planned and unexpected users of field data, such as specialists asking new questions or applying new methodologies beyond the original intention and scope of a data set.
Navigating these uncharted waters of field data collection is no easy task. With Anne and Sarah at the helm, the workshop drew on case-studies from their collaborative Secret Life of Data (SLO-Data) project to plot the pitfalls and strengths of different approaches to field data collection. These examples provided insights into team training, incorporating specialists and their datasets into project processes, and recommendations for data collection documentation in field manuals. Using these guidelines, Anne and Sarah mapped how to deftly cruise through the murky waters of decentralized, paper records to find the elusive “X” that marks the spot: coherent and accessible datasets. Along with Eric Kansa, they also demonstrated tools like Kobo Toolbox, FAIMS, XLS Form, and Open Data Kit for organizing, accessing, editing, tracking, and archiving field data.
In breakout group activities, participants shared data collection forms and discussed how to adapt a specialist agreement to meet different project needs. They also tackled issues of data quality like how to structure data collection to optimize quality while protecting culturally sensitive information; how to reconcile data collected by different team members who may have competing research questions, methodologies, goals, and priorities; and how to implement reasonable protocols for quality control checks and enforcing data quality compliance.
With these templates and steps mapped out, participants emerged better equipped to steer their projects’ field data collection through the fog of complex standards. These tools can be leveraged to navigate the depths of data quality issues and reach the clear waters of data transparency, accessibility, discoverability, and interoperability. With these navigation charts in hand and time to build a project compass of their own, participants can start to plot a course for smooth data sailing ahead.
