Toward Slow Data in Archaeology

This is a pdf copy of the PPT slides used in this presentation at the SAA symposium. Digital data play increasingly prominent roles in archaeological research. However, data tend to be considered “raw materials” that fuel scholarship and not as intellectual contributions in their own right. Most attention on “research data management” focuses on “management” where data are considered mainly through the lens of Taylorism (bureaucratic compliance, standards, incentives, and metrics). Research data management largely aims for “Big Data” research opportunities achieved through centralization, economies of scale, and the efficient production of measurable research outcomes. To provoke debate, this paper suggests an alternative model of “Slow Data” that emphasizes thoughtful consideration of data throughout the research process. Our experience with Open Context shows that to be usable by a wider community, data require substantive intellectual investment in modeling and validation. Ideally, researchers should plan for reuse outcomes well before they start data collection. Thus, the intellectual investment underlying data curation must become more integral to the whole practice of archaeology. Rather than simply rewarding high throughput and impact for easily-measured research outputs (papers or even archived datasets), greater recognition for the research process will promote better contextualization of data, leading to meaningful research outcomes from data integration, greater reproducibility, and better ethical practice.