SHEILA PONTIS, Sense Information Design & Princeton University
Ethnographic analysis is the examination of raw data with an interpretative lens to identify themes, connections and patterns. How can you make this process more accessible to support data socialization and encourage collaboration from all members of an organization or team? In this tutorial you will learn and practice information design principles and visual frameworks to support research data analysis, translate findings into tangible forms and share learnings with more clarity.
This hands-on tutorial will help ethnographic and design researchers analyze and synthesize field research data in a structured and visual way. Tutorial participants will create visuals that keep the power of the text, its meanings and emotions, without oversimplifying or misrepresenting the data. The tutorial will cover:
Information design principles for supporting ethnographic research
Six ways of seeing and showing for analyzing data and visualizing insights...
This case study examines how one Artificial Intelligence (AI) security software team made the decision to abandon a core feature of the product – an interactive Knowledge Graph visualization deemed by prospective buyers as “cool,” “impressive,” and “complex” – in favor of one that its users – security analysts – found easier to use and interpret. Guided by the results of ethnographic and user research, the QRadar Advisor with Watson team created a new knowledge graph (KG) visualization more aligned with how security analysts actually investigate potential security threats than evocative of AI and “the way that the internet works.” This new feature will be released in Q1 2020 by IBM and has been adopted as a component in IBM’s open-source design system. In addition, it is currently being reviewed by IBM as a patent application submission. The commitment of IBM and the team to replace a foundational AI component with one that better aligns to the mental models and practices of its...
by MAKALÉ FABER CULLEN
“We don’t fail because we are not intelligent or erudite enough; we fail because we don’t present our stakeholders with engaging material that will improve their ideas. We choose the medium which makes us comfortable, not the one our stakeholders would prefer.”
— Sam Ladner, Practical Ethnography (159)
Our work as ethnographers, as social scientists, is rich, experiential, relational, multi-dimensional and full-sensory. As often as we can, we immerse ourselves in communities and in landscapes and then—we heighten all our senses, turn down our ego and try to understand the context. Nothing is as important as context.
We document and analyze these contexts and the individuals and objects within them, refining them for a new context of service design or product development that is itself a whole new ecosystem of relationships, ethics, finances, goals, timescapes. Businesses and organizations have distinct customs, rituals, and standards for creating "evidence-that-counts."
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...
University of Illinois at Chicao
A simple understanding of the principles of good information and visualization design can help in the presentation, comprehension, and socialization of your research insights and recommendations. ‘Simple’ means a point of view that the aesthetics of your deliverables should never say “look at me” but rather support content by saying “look at this.”
This tutorial will give you a foundational understanding of good design techniques for creating clear and impactful research stimulus and reporting. The session is tailored for researchers with little or no design experience looking to improve their visual design skills, create impact by communicating visually, and build empathy with your designers and design teams.
Using examples and case studies from professional practice as inspiration, this course will expose participants to a variety of topics, all relevant to their professional practice:
Emphasizing the user voice in storytelling
by MABEL CHAN, Salesforce
The Salesforce Platform empowers customers to build applications that are highly customized to their particular business operations and data. As platform researchers, we help create the tools that enable customers, including Salesforce administrators, to build these applications. Last year, the platform research team at Salesforce embarked on a project to update our existing UX personas. We had inherited two sets of persona work that described Platform users, but neither was actually being used to guide product-related decisions. One of the projects, the results of a skill segmentation survey, was regarded as accurate and credible, but was reported through dense tables of data and few stakeholders read or referenced it. The other was a more traditional set of personas that was easy to consume, but lacked specificity and was perceived as too superficial to be useful in decision-making. While this original persona work was based in research, it sat underutilized by researchers, designers, and product managers...