In learning analytics contexts one of the things we’re interested in is how stakeholders – managers, educators, students, parents, etc. – interact with ‘their’ data at the various levels of granularity. Of course part of that is about how that data is represented and visualised, and the kinds of collaborative sensemaking processes that stakeholders engage in. One of the things I’m also interested in is inviting students into the processes of learning analytics and the space of data representations (per ‘dear learner’).
An area I’ve just come across is ‘Human Data Interaction’ – riffing on human computer interaction to explore specific interactions with data to “support end-users in the day-to-day management of their personal digital data…” with an understanding of data as of an “inherently social and relational character” . Thus, “HDI is a distinctively socio-technical problematic, driven as much by a range of social concerns with the emerging personal data ‘ecosystem’ as it is by technological concerns, to develop digital technologies that support future practices of personal data interaction within it” . In that piece, they highlight the tensions between ‘our’ and ‘my’ data, and issues of data ownership and control. HDI, then, is concerned not only with how people use and create data, but with how they both visualise and understand the data, and how that data is made use of within social relational systems (by data creators and processors).
In that paper they then outline some challenges:
Personal data discovery, including meta-data publication, consumer analytics, discoverability policies, identity mechanisms, and app store models supporting discovery of data processers
Personal data ownership and control, including group management of data sources, negotiation, delegation and transparency/awareness mechanisms, and rights management.
Personal data legibility, including visualisation of what processors would take from data sources and visualisations that help users make sense of data usage, and recipient design to support data editing and data presentation.
Personal data tracking, including real time articulation of data sharing processes (e.g., current status reports and aggregated outputs), and data tracking (e.g., subsequent consumer processing or data transfer).