Human-data interaction

We have moved from a world where computing is siloed and specialised, to a world where computing is ubiquitous and everyday. In many, if not most, parts of the world, networked computing is now mundane as both foreground (e.g., smartphones, tablets) and background (e.g., road tra c management, financial systems) technologies. This has permitted, and continues to permit, new gloss on existing interactions (e.g., online banking) as well as distinctively new interactions (e.g., massively scalable distributed real-time mobile gaming). An e ect of this increasing pervasiveness of networked computation in our environments and our lives is that data are also now ubiquitous: in many places, much of society is rapidly becoming “data driven”

Human-Data Interaction in Healthcare

In this paper, we focus on an emerging strand of IT-oriented research, namely Human-Data Interaction (HDI) and how this can be applied to healthcare. HDI regards both how humans create and use data by means of interactive systems, which can both assist and constrain them, as well as to passively collect and proactively generate data. Healthcare provides a challenging arena to test the potential of HDI to provide a new, user-centered perspective on how data work should be supported and assessed, especially in the light of the fact that data are becoming increasingly big and that many tools are now available for the lay people, including doctors and nurses, to interact with health-related data.Comment: 10 pages, 4 Figure

Full Body Interaction beyond Fun: Engaging Museum Visitors in Human-Data Interaction

Engaging museum visitors in data exploration using full-body interaction is still a challenge. In this paper, we explore four strategies for providing entry-points to the interaction: instrumenting the floor; forcing collaboration; implementing multiple body movements to control the same effect; and, visualizing the visitors' silhouette beside the data visualization. We discuss preliminary results of an in-situ study with 56 museum visitors at Discovery Place, and provide design recommendations for crafting engaging Human-Data Interaction experiences

Servitization through human-data interaction : a behavioural approach

Purpose: This paper proposes a new approach to servitization and business models by understanding behavioural aspects of human interactions with technology, specifically, with “smart” devices, connected devices, autonomous systems, and internet of things (IoT) through understanding and interacting with data which these devices and systems generate. Design/methodology/approach: Proposed approach, Behavioural Human Data Interaction Hypothesis (Behavioural HDI Hypothesis), which differs from existing literature, leverages on research in behavioural science, data-driven business models, multi-sided markets, and Human-Data Interaction (HDI). Findings: Behavioural HDI Hypothesis can offer a new approach to future markets for data because it helps to (a) predict consumer choice of product and services; (b) suggest new and improved interaction mechanisms between consumers and their self-generated data; and (c) propose a new approach for building and evaluating business models. Originality/value: To date, very little has been known about whether and how consumers and households accumulate, review and use self-generated data about consumption decisions and how this affects market relationships between consumers and providers of goods and services. This paper shows how Behavioural HDI Hypothesis can make markets for data more efficient through better personalisation and servitization. It also has implications for data collection visibility, data ownership and structure, platform trade-off, security and other ICT-related challenges which negatively affect current business models in the digital economy

Human-Data Interaction: The Human Face of the Data-Driven Society

The increasing generation and collection of personal data has created a complex ecosystem, often collaborative but sometimes combative, around companies and individuals engaging in the use of these data. We propose that the interactions between these agents warrants a new topic of study: Human-Data Interaction (HDI). In this paper we discuss how HDI sits at the intersection of various disciplines, including computer science, statistics, sociology, psychology and behavioural economics. We expose the challenges that HDI raises, organised into three core themes of legibility, agency and negotiability, and we present the HDI agenda to open up a dialogue amongst interested parties in the personal and big data ecosystems

Exploration space of human-data interaction

Data is everywhere. Starting with the invention of writing, representation artifacts brought the data to observable state which led to natural establishment of an interaction form between human and data. In the human-data interaction (HDI) environment, data representations and analytic systems act as an intermediary role. I suggest a new de nition for HDI in which this interaction is conceptualized as a communication model over a set of media. The interaction occurs with the exchange of messages originated from both human and data. Timing and content of the messages are employed to facilitate objective evaluation of properties of analytic system in question. To systematically investigate the complex nature of HDI, my methodology postulates the phenomenon as a high-dimensional space in which data analytic systems could be positioned based on their properties. Evaluation of the properties are performed based on solid de nitions of the dimensions. I de ne ve properties for data analytic systems, namely, responsiveness, communication media level, unit task diversity, closeness factor, and progressiveness level, and demonstrate how these properties could be objectively calculated. I visually explore the HDI space in which data analytic systems reported in my thesis are plotted on a two-dimensional Cartesian system whose axes are responsiveness and communication media level. Visually identi able patterns in this plot, which I call realms, are characterized by quantitative and qualitative analysis of objective, behavioral, and subjective data collected during the user interaction with the corresponding analytic system

Human data interaction through design:An explorative step from theory to practice using design as a vehicle

The increasing use of personal data and AI in everyday technologies has resulted in the amplification of complex and intertwined socio-technical challenges. These, often exemplified by data abuse, breaches, and exploitation, must be alleviated to support sustainable, resilient and human-centred data economies and positive global innovation. Here, we turn towards Human-Data Interaction, an interdisciplinary branch of research, inspired by HCI, that brings together diverse siloed perspectives to present three holistic response principles: data legibility, negotiability and agency. But, the emergent nature of this field calls for refinement of these theoretical tenets to help them translate into practical and tangible responses that are embedded in the technologies we create. We propose this workshop as a foundational step towards this agenda by opening these principles to the CHI community to encourage critique and dialogue about the strengths, weaknesses, value and opportunities of incorporating HDI into the design and evaluation of technology. The outcomes of this workshop, by engaging with HDI through Design, will form the basis for the next stages of research within HDI by contributing to foundational texts within academia and implementing HDI-infused systems within industry