Reflections on data: the need for context

In the world of ubiquitous computing we can see (or rather we can’t) Big Data generated around us constantly. We can quantify-ourselves by tracking our sleep, calorie-intake, number of steps and even how many coffees we had this week. Sounds like a Black Mirror episode in the making. We can track our utility consumption, how many times we took the metro this month or look back at our personal history via Facebook’s ‘Year in Review’ feature.

Researchers aim to advance, develop and implement technologies to gather, store and analyse the data. But do they focus too much on problem-solving, looking at data in a vacuum and failing to consider the context it’s generated in? Isn’t this an important question to consider when our life is so driven by data? Some researchers raise this issue and apply a more critical approach considering people’s experience of a data-driven life. (e.g. Elsden et al., 2015; Puussaar et al., 2017)

For example, Rooksby et al. (2014) focusing on the area of personal informatics, investigates people’s lived experience and encourages us to look beyond the simplistic view of tracking as only a tool for behaviour change. Some people use tracking in order to document their day-to-day lives as a form of self-expression (ibid.). Elsden et al. (2017) in the context of a wedding, for instance, used Documentary Informatics, utilising the data gathered to create artefacts – coasters mapping the happy couple’s first dance movements. He uses the idea of a documentary style of personal tracking in order to make the data meaningful and longer-lasting.

In one of Taylor et al. (2015)’s projects about data-in-place, data about a street’s environment was collectively gathered by residents themselves due to their concerns regarding the redevelopment plan to be raised to the council. This stressed the importance of residents’ active rather than passive involvement in data gathering (ibid.). In this way, the data-in-place concept introduces the idea of strengthening relations between people, data and places and how people and communities, rather than organisations, can interact with data. Making sense of data in this way materialises data into something meaningful; thereby increasing the data’s value.

Bowyer et al. (2018) try to understand the perspective of families encountering domestic abuse, on how their private data should be handled. They utilise a more relational approach to data, importantly to enable family support workers to see a full picture of each case. The study also brings to light families’ concerns with misinterpretation of their personal data and the broader implications for future civic data-handling systems to reflect the view of families.

So, is it the time, instead of trying to collect as much data as possible, to try to make sense of the data collected? The above examples still raise concerns about ownership of the data created, the difficulty of the equal representation of the views of all stakeholders and the problem of abandonment and sustainability. But maybe these are important identifications of the limitations of the problem-solving approach that is so readily applied to Big Data, especially in certain fields. The studies mentioned show the importance of giving meaning to the data that is so ingrained in our lives, rather than regarding data for data’s sake.

In my view, this is the black mirror we have to be careful not to be transfixed by.

Reference:

[1] Alex Bowyer, Kyle Montague, Stuart Wheater, Ruth McGovern, Raghu Lingam, Madeline Balaam. 2018. Understanding the Family Perspective on the Storage, Sharing and Handling of Family Civic Data. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI ‘18). https://doi.org/10.1145/3173574.3173710

[2] Chris Elsden, Abigail C. Durrant, David Chatting, and David S. Kirk. 2017. Designing Documentary Informatics. In Proceedings of the 2017 Conference on Designing Interactive Systems (DIS ’17), 649–661. https://doi.org/10.1145/3064663.3064714

[3] Chris Elsden, David Kirk, Mark Selby and Chris Speed. 2015. Beyond personal informatics: Designing for experiences with data. In Proceedings of the CHI 2015 Conference on Human Factors in Computer Systems (CHI ‘15).

[4] Aare Puussaar, Adrian Clear, and Peter Wright. 2017. Enhancing Personal Informatics Through Social Sensemaking. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI ‘17), 6936–6942.

[5] John Rooksby, Mattias Rost, Alistair Morrison, and Matthew Chalmers Chalmers. 2014. Personal Tracking As Lived Informatics. In Proceedings of the 32nd Annual ACM Conference on Human Factors in Computing Systems (CHI ’14), 1163–1172. https://doi.org/10.1145/2556288.2557039

[6] Alex S Taylor, Siân Lindley, Tim Regan, et al. 2015. Data-in-Place: Thinking through the Relations Between Data and Community. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2863–2872.

 

 

 


Author: Irina Pavlovskaya

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