Abstract
Human Data Interaction (HDI) is an emerging field of research that seeks to support end-users in the day-to-day management of their personal digital data. This is a programmatic paper that seeks to elaborate foundational challenges that face HDI from an interactional perspective. It is rooted in and reflects foundational lessons from social studies of science that have had a formative impact on CSCW, and core challenges involved in supporting interaction/collaboration from within the field of CSCW itself. These are drawn upon to elaborate the inherently social and relational character of data and the challenges this poses for the ongoing development of HDI, particularly with respect to the ‘articulation’ of personal data. Our aim in doing this is not to present solutions to the challenges of HDI but to articulate core problems that confront this fledgling field as it moves from nascent concept to find a place in the interactional milieu of everyday life and particular research challenges that accompany it.
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Notes
- 1.
The model also permits a user to operate multiple catalogues, independent of each other, thereby providing a means to control the problems of linking accounts across different sources. Interactions between such catalogues are not considered an explicit feature of the system.
- 2.
HDI construes of the recipient as the processor, which presents a particular request for computation to be carried out to the data source after it has been granted permission. While this hold true, the issue is to enable the user to design permission with respect to just what of the data is available to the processor, and to others within a particular cohort too. Recipient design draws our attention for the need to support human judgement, decision-making and intervention in the course of human data interaction.
- 3.
The requirement is reflected in the Article 29 Data Protection Working Party report on the IoT (14/EN WP 223 2014) and the recommendation that end-users be able to “locally read, edit and modify the data before they are transferred to any data controller … Therefore, device manufacturers should provide a user-friendly interface for users who want to obtain both aggregated data and/or raw data.” The challenge, of course, is bring this about in practice, particularly as personal data sources expand and diversify with the advent of the IoT.
- 4.
All of this, as with so many interactions within the dataware model, trades on reliable identity mechanisms. The general problem of authentication in networked systems has been long studied and several solutions exist: TLS certificates (both server and client) or PGP-based web-of-trust seem feasible initial approaches, though both have weaknesses and would require careful engineering with respect to HDI.
- 5.
Controlling presentation of your meter readings may seem odd, but in a near future world where metering could be done on an appliance or device level, enabling users to control the granularity of energy consumption data (for example) becomes a much more coherent proposition.
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Acknowledgment
The research on which this article is based was funded by RCUK research grants EP/M001636/1 and EP/K003569/1.
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Crabtree, A., Mortier, R. (2015). Human Data Interaction: Historical Lessons from Social Studies and CSCW. In: Boulus-Rødje, N., Ellingsen, G., Bratteteig, T., Aanestad, M., Bjørn, P. (eds) ECSCW 2015: Proceedings of the 14th European Conference on Computer Supported Cooperative Work, 19-23 September 2015, Oslo, Norway. Springer, Cham. https://doi.org/10.1007/978-3-319-20499-4_1
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