ADAHEID L. MESTAD
During recovery and transition to the ‘new normal’, the loss of agency for patients and families of patients who go through a major health disruptor such as transplant, cancer, or cardio-vascular disease can be profound. Considering this, how can acute care hospitals help solve for caregivers’ loss of agency? And what does the physicality of such effort in the confines of a hospital building look like? The goal of this case study is to (1) demonstrate how ethnographic thinking and design research can help a medical center understand the needs, values, rituals, and agency of a patients and their families; (2) show socio-spatial solutions that can support the transition to the patient’s and family’s new normal.
The ethnographic study showed that the patients and families who go through a major health disruptor struggle with the loss of agency in various ways. While loss of agency can be obtuse, four themes emerged as contributing factors to the overall sense of loss: (1) loss...
Applied ethnography still struggles with the fundamental challenges of (1) framing research to obtain ‘thick’ data, (2) making sense of data in teams and with clients, and (3) making a convincing case with data in challenging environments. We have observed that borrowing from literary genres can be effective in addressing these challenges. We therefore argue that in an age of data science, it is just as important to draw from the literary arts when gathering, analyzing, and elevating evidence to inspire change in applied ethnographic work. We raise three specific applications of literary genres to distinct project phases, to improve how data is collected and analyzed, and how data travels. In this paper we show: (1) how the screenplay can help solve challenges in research framing, to obtain thicker data; (2) how the novel can help solve challenges in analysis, to turn data into meaningful evidence; (3) how poetry can help solve challenges in the opportunities-development...
imec-SMIT, Vrije Universiteit Brussel
imec-SMIT, Vrije Universiteit Brussel
This paper aims to contribute to the debate on the integration of ethnography and data science by providing a concrete research tool to deploy this integration. We start from our own experiences with user research in a data-rich environment, the smart city, and work towards a research tool that leverages ethnographic praxis with data science opportunities. We discuss the different key components of the system, how they work together and how they allow for human sensemaking....
MILLIE P. ARORA
As algorithms play an increasingly important role in the lives of people and corporations, finding more effective, ethical, and empathetic ways of developing them has become an industry imperative. Ethnography, and the contextual understanding derived from it, has the potential to fundamentally change the way that data science is done. Reciprocally, engaging with data science can help ethnographers focus their efforts, build stronger and more precise insights, and ultimately have greater impact once their work is incorporated into the algorithms that increasingly power our society. In practice, building contextually-informed algorithms requires collaboration between human science and data science teams who are willing to extend their frame of reference beyond their core skill areas. This paper aims to first address the features of ethnography and data science that make collaboration between the two more valuable than the sum of their...
WILLIAM WELSER IV
Case Study—This case-study details how a team of anthropologists and a team of data scientists sought to help a Middle Eastern theme park make use of their big data platform to measure ‘the good customer experience’. Ethnographic research within the theme park revealed that visitors yearned to bond with the other members of their group, as they rarely got the chance during their busy everyday lives back home. However, trying to build a measurement of how the theme park delivered on bonding – through the development of a ‘bonding index’ – turned out to be unfeasible, because the big data platform focused on capturing operational data. The decision to focus on operational data had unintentionally created a path dependency that made the big data setup unfit for answering some of the theme park’s most fundamental questions. This is a problem ReD Associates has observed across clients and to solve it this...