Patient-generated data, such as data from wearable fitness trackers and smartphone apps, are viewed as a valuable information source towards personalised healthcare. However, studies in specific clinical settings have revealed diverse barriers to their effective use. In this paper, we address the following question: are there barriers prevalent across distinct workflows in clinical settings to using patient-generated data? We conducted a two-part investigation: a literature review of studies identifying such barriers; and interviews with clinical specialists across multiple roles, including emergency care, cardiology, mental health, and general practice. We identify common barriers in a six-stage workflow model of aligning patient and clinician objectives, judging data quality, evaluating data utility, rearranging data into a clinical format, interpreting data, and deciding on a plan or action. This workflow establishes common ground for HCI practitioners and researchers to explore solutions to improving the use of patient-generated data in clinical practices.

Narratives form a key component of multimedia knowledge representation on the Web. However, many existing multimedia narrative systems either ignore the narrative qualities of any media, or focus on the literal depicted content ignoring any subtext. Ignoring narrative subtext can lead to erroneous search results, or automatically remixed content that lacks cohesion. We suggest that subtext can be computationally modeled in terms of Tomashevsky’s hierarchy of themes and motifs. These elements can then be used in a semiotic term expansion algorithm, incorporating knowledge of subtext into search and subsequent narrative generation. We present two experimental applications of this technique. In the first, we use our thematic model in the automatic construction of photo montages from Flickr, comparing it to more traditional term expansion based on co-occurrence, and showing that this improves the perceived relevance of images within the montage. In the second, we use the thematic model in order to automatically identify Flickr images to illustrate short stories, where it dampened the perception of unwanted themes (an effect we describe as reducing thematic noise). Our work is among the first in this space, and shows that thematic subtext can be tackled computationally.

A key area in the research agenda of modelling argumentation is to accurately model argumentation on the social web. In this paper we propose additional extensions to our ontology for argumentation on the social web (which integrates elements of the Argument Interchange Format and the Semantically Interlinked Online Communities project) for the purposes of modelling social and rhetorical tactics used in eristic or irrational arguments. We then present a review of these extensions from a panel of experts in the fields of argumentation modelling, web science, philosophy and open and linked data and discuss the value of modelling social argument, the challenges faced to create usable and accurate models and the completeness, clarity and consistency of our proposed additions.

Applications that operate over streaming data with high-volume and real-time processing requirements are becoming increasingly important. These applications process streaming data in real-time and deliver instantaneous responses to support precise and on-time decisions. In such systems, traceability - the ability to verify and investigate the source of a particular output - in real-time is extremely important. This ability allows raw streaming data to be checked and processing steps to be verified and validated in timely manner. Therefore, it is crucial that stream systems have a mechanism for dynamically tracking provenance - the process that produced result data - at execution time, which we refer to as on-the-fly stream provenance tracking. In this paper, we propose a novel on-the-fly provenance tracking mechanism that enables provenance queries to be performed dynamically without requiring provenance assertions to be stored persistently. We demonstrate how our provenance mechanism works by means of an on-the-fly provenance tracking algorithm. The experimental evaluation shows that our provenance solution does not have a significant effect on the normal processing of stream systems given a 7% overhead. Moreover, our provenance solution offers low-latency processing (0.3 ms per additional component) with reasonable memory consumption.

Non-intrusive appliance load monitoring is the process of disaggregating a household's total electricity consumption into its contributing appliances. In this paper we propose an approach by which individual appliances can be iteratively separated from an aggregate load. Unlike existing approaches, our approach does not require training data to be collected by sub-metering individual appliances, nor does it assume complete knowledge of the appliances present in the household. Instead, we propose an approach in which prior models of general appliance types are tuned to specific appliance instances using only signatures extracted from the aggregate load. The tuned appliance models are then used to estimate each appliance's load, which is subsequently subtracted from the aggregate load. This process is applied iteratively until all appliances for which prior behaviour models are known have been disaggregated. We evaluate the accuracy of our approach using the REDD data set, and show the disaggregation performance when using our training approach is comparable to when sub-metered training data is used. We also present a deployment of our system as a live application and demonstrate the potential for personalised energy saving feedback.

Applications that require continuous processing of high-volume data streams have grown in prevalence and importance. These systems process streaming data in real-time and provide instantaneous response to support precise and ontime decisions. In such systems, it is difficult to know exactly how a particular result is generated or more particularly how to precisely trace stream events that caused a particular result. However, such information is extremely important for validating stream processing results. Therefore, it is crucial that stream processing systems have a mechanism for capturing and querying provenance information - the information pertaining to the process that produced result data - at the level of individual stream events, which we refer to as fine-grained provenance. In this paper, we propose a novel fine-grained provenance solution called Stream Ancestor Function - a reverse mapping function used to express precise dependencies between input and output stream elements. We demonstrate how to utilize stream ancestor functions by means of a stream provenance query and replay execution algorithm. Finally, we evaluate the stream ancestor function in terms of storage consumption for provenance collection and system throughput, demonstrating significant reductions in storage size and reasonable processing overheads.

Behavioural interventions packages of advice and support for behaviour change are one of the most important methodologies and technologies employed by social scientists for understanding and changing behaviour. A typical web-based behavioural intervention study includes the designing, deploying, piloting and trialling of the intervention as well as data analysis. We have developed a research environment named LifeGuide, which covers the full scope of this process, enabling social scientists to carry out intervention studies with minimal technical expertise. In this paper, we present how the LifeGuide can assist and accelerate intervention research, particularly focusing on supporting the running and analysis of trials of web-based behavioural interventions along with the case study of an intervention that has been developed within the LifeGuide.

Located pervasive experiences are often constructed as one off deployments with domain experts acting in a consultancy role to technical specialists who construct the experience. In this paper we will look at how pervasive infrastructures might be constructed that can support domain experts as direct experience authors. We present a case study based around a locative pervasive system supporting school field trips, and describe how aspects of the construction and running of the experience were handed over to the domain experts. Based on our experiences we suggest a number of key principles that we believe make it possible for non-specialists to become pervasive authors: separation of the information layer, use of metaphor, in-situ authoring, robustness, varied location modelling and coarse orchestration

The aim of this article is to produce an alternative view of the adaptive hypermedia (AH) domain from a contextually-aware open hypermedia (OH) perspective. We believe that a wide range of AH techniques can be supported with a small number of OH structures, which can be combined together to create more complex effects, possibly simplifying the development of new AH systems. In this work we reexamine Brusilovsky's taxonomy of AH techniques from a structural OH perspective. We also show that it is possible to identify and model common structures across the taxonomy of adaptive techniques. An agent-based adaptive hypermedia system called HA 3 L is presented, which uses these OH structures to provide a straightforward implementation of a variety of adaptive hypermedia techniques. This enables us to reflect on the structural equivalence of many of the techniques, demonstrates the advantages of the OH approach, and can inform the design of future adaptive hypermedia systems.

A key challenge in co-designing UbiComp is that users may have limited understanding or experience of these technologies. While the value of situated co-design activities for promoting understanding is known, the role of time is less well researched. Here we describe and reflect on a range of co-design activities carried out with the curators of an historic English manor house to create novel visitor tours. We show how an ensemble of situated co-design activities over time led to the unfolding of user understanding around issues of content, technology and user experience, in turn leading to a progressive re-imagining of practice. This points to the importance of time and variety of in-situ activities to help people engage as co-designers in creating novel UbiComp-enabled experiences.

Fieldtrips, traditionally associated with science, history and geography teaching, have long been used to support children’s learning by allowing them to engage with environments first-hand. Recently, ubiquitous computing (UbiComp) has been used to enhance fieldtrips in these educational areas by augmenting environments with a range of instruments, devices and sensors. However, the sorts of interaction design that UbiComp makes possible have the potential not just to enhance the value of educational techniques in known application areas, but also to expand the application of those techniques into new areas of curriculum. We report on a UbiComp-supported fieldtrip to support creative writing, associated with the learning of literacy skills. We discuss how the fieldtrip, designed and run in the grounds of a historic English country house with Year 5 UK schoolchildren, engendered interactions which changed both the processes and products of creative writing, with benefits for both teachers and children.

In this paper we describe an investigation into the requirements for and the use of in-situ authoring in the creation of location based pervasive and UbiComp experiences. We will focus on the co-design process with users that resulted in a novel visitor experience to a historic country estate. This has informed the design of new, in-situ, authoring tools supplemented with tools for retrospective revisiting and reorganization of content. An initial trial of these new tools will be discussed and conclusions drawn as to the appropriateness of such tools. Further enhancements as part of future trials will also be described.

Ubiquitous and mobile technologies provide opportunities for designing novel learning experiences that move out of the classroom. Information can be presented and interacted with in a variety of ways while exploring a physical environment. A key issue this raises is when, where, what and how much? Our research is concerned with the design, delivery and interaction of digital information when learning about ecology outdoors. We present a framework of the different forms of digital augmentation and the different processes by which they can be accessed. Using the framework, we designed an outdoors learning experience, aimed at encouraging students to carry out contextualized scientific enquiry and to reflect on their interactions. Pairs of 11-12 year olds explored a woodland and were presented at certain times with different forms of digital augmentation. Our study showed that this kind of exploration promoted interpretation and reflection at a number of levels of abstraction.