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Data Work: How Energy Advisors and Clients Make IoT Data Accountable
Joel E Fischer1, Andy Crabtree1, James A Colley1
11Mixed Reality Laboratory, School of Computer Science, University of Nottingham, Nottingham, UK.
Computer Supported Cooperative Work : CSCW : an International Journal
|February 7, 2020
Summary
This study examines an interactive sensing system used by UK energy advisors for low-income households. It details how advisors and clients collaborate with data, highlighting the costs and needs for integrating the Internet of Things (IoT) into advisory work.
Area of Science:
- Human-Computer Interaction
- Sociology of Technology
- Energy Policy
Background:
- Energy advisors provide crucial face-to-face advice to low-income households in the UK.
- Interactive sensing systems can potentially enhance the effectiveness of energy advisory services.
- The integration of technology into social work requires understanding collaborative data practices.
Purpose of the Study:
- To investigate the deployment and use of an interactive sensing system by energy advisors.
- To analyze how energy advisors and clients interact with and utilize system-generated data.
- To understand the collaborative 'data work' involved in using IoT systems in advisory contexts.
Main Methods:
- Fieldwork deployment of an interactive sensing system.
- Observational studies of energy advisor-client interactions.
- Qualitative analysis of collaborative data work and system appropriation.
Main Results:
- The interactive sensing system was appropriated into the daily work of energy advisors.
- Collaborative data work, including anticipating, rehearsing, and performing data tasks, was observed between advisors and clients.
- Significant 'overhead costs' were identified in building collaborative action into sensing systems.
Conclusions:
- Integrating the Internet of Things (IoT) into collaborative advisory work necessitates support for discrete workflows and accountability systems.
- The study elaborates on social and collaborative methods of data work crucial for designing and studying collaborative IoT systems.
- Understanding the practicalities of data work is essential for the successful implementation of IoT in social and support services.
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