This article explores the challenges of designing large-scale computing systems for multiple, diverse user groups. Such computing systems house large, complex datasets, and often provide analytic tools to interpret the data. They are increasingly central to activities in industry, science, and government agencies, and are often associated with “big data,” data warehousing, and/or scientific “cyberinfrastructure”.  A key characteristic of these systems is the diversity and multiplicity of their intended user groups, which may range from various scientific disciplines, to assorted business functions, to government officials and citizen groups. These user groups occupy structurally different positions in local and global political economies, and bring different forms of expertise to the data housed in the computing system. We argue that design anthropologists can contribute to the usefulness of such systems by engaging in collaborative ethnographic research with the targeted user groups, and communicating findings to the designers and developers creating these systems.

Crop rotation is a cultural practice in disease management used to break the disease cycle resulting in a reduction of inoculum. In Ohio, crop rotations have been reduced in diversity, with many farmers shifting to corn-soy rotations from more diverse rotations featuring wheat and forage crops. We investigated the impact of this shift on soil fungal communities under corn by conducting synthetic long-read amplicon sequencing. DNA was extracted from soil sampled during the corn growing season at two locations in Ohio with replicated long-term rotation plots in corn-soybean (CS) and a corn-soybean-winter wheat rotation (CSW) in 2018, 2019, and 2020.18s-ITS amplicons were sequenced using Illumina paired with Loopgenomics™ technology. PERMANOVA analysis revealed that fungal communities were significantly impacted by location, rotation, and time. Shannon and Simpson diversity indices implied fungal species diversity was significantly higher in the CS rotation. Indicator species analysis revealed 20 species indicative of the CSW rotation, including Mortierella , Hymenoschyphus , Ascobolus , and Saitozyma species, and 36 species indicative of the CS rotation, including Fusarium , Neoaschocyta , Zalerion , and Trichoderma species, among others. Indicator species ASV reads for the CSW rotation were not correlated with the decline in corn yield or soil N, C, or active carbon. However, they were positively correlated with soil organic matter.