Unearthing the Infrastructure: Humans and Sensors in Field-Based Scientific Research

Abstract

Abstract. Distributed sensing systems for studying scientific phenomena are critical applications of information technologies. By embedding computational intelligence in the environment of study, sensing systems allow researchers to study phenomena at spatial and temporal scales that were previously impossible to achieve. We present an ethnographic study of field research practices among researchers in the Center for Embedded Networked Sensing (CENS), a National Science Foundation Science & Technology Center devoted to developing wireless sensing systems for scientific and social applications. Using the concepts of boundary objects and trading zones, we trace the processes of collaborative research around sensor technology development and adoption within CENS. Over the 10-year lifespan of CENS, sensor technologies, sensor data, field research methods, and statistical expertise each emerged as boundary objects that were understood differently by the science and technology partners. We illustrate how sensing technologies were incompatible with field-based environmental research until researchers "unearthed" their infrastructures, explicitly reintroducing human skill and expertise into the data collection process and developing new collaborative languages that emphasized building dynamic sensing systems that addressed human needs. In collaborating around a dynamic sensing model, the sensing systems became embedded not in the environment of study, but in the practices of the scientists.

Build It, But Will They Come? A Geoscience Cyberinfrastructure Baseline Analysis

“…Divides between technologists and scientists have been documented in a wide range of geoscience settings (Mayernik, Wallis, & Borgman, 2013;Jackson & Buyuktur, 2014;Finholt and Birnholtz, 2006;Ribes and Finholt, 2008). These divides range from challenges in developing effective collaborative structures and aligning incentives, to difficulties in establishing leadership roles and determining who the relevant "community" actually is for a given cyberinfrastructure initiative.…”

Research data and metadata curation as institutional issues

“…In the development of scientific infrastructure, this often manifests as tensions between technical and scientific researchers. The former group often prioritizes innovation and the use of cutting edge technology, whereas the latter group often prioritizes stability, ease of use, and customizability (Batcheller, 2011;Finholt & Birnholtz, 2006;Mayernik, Wallis, & Borgman, 2013). Material objects can thus carry assumptions and expectations about behavioral patterns from situation to situation, such as from information system designers to users.…”

Knowledge infrastructures in science: data, diversity, and digital libraries

“…Publications are the primary research assets that remain available from CENS. Largely through the efforts of the CENS Data Practices team, which was the predecessor to the Knowledge Infrastructures team, the CENS publication repository was created within the University of California's eScholarship system [20,88,117]. The team also developed a data registry as part of the annual reporting system to NSF.…”