Jonathan Day
email: jonathan.day.2@city.ac.uk

George Buchanan
email: george.buchanan.1@city.ac.uk

Stephann Makri
email: stephann@city.ac.uk

Learning Lessons from Controlled Studies to Investigate Users' Resilience Strategies

Keywords: Resilience Strategies, Workarounds, Cognitive Resilience

This work describes the development and implementation of a controlled study into the way users form and utilise resilience strategies to overcome threats to performance. Despite a carefully considered design, participants demonstrated creative and unanticipated strategies to overcome deliberately 'designed-in' challenges in our task, thus circumventing the errors and responses we had predicted. We discuss the variety of unanticipated resilience strategies we observed during the course of this study, as well as methodological lessons learned as a result. Furthermore, we describe a forthcoming study which seeks to build upon the initial investigation, utilising a revised task paradigm to address and overcome its limitations.

Introduction

A key concern of HCI is the investigation of error:-how and why errors occur, and how they can be prevented in future interactions. An alternative, complimentary perspective however, is the investigation of Resilience Strategies, which constitute positive behavioural adaptations by users to reduce or mitigate threats to performance.

The study of resilience also presents new opportunities to improve systems and interactions, given that historically, it has largely been overlooked [START_REF] Hollnagel | A tale of two safeties[END_REF]. When errors or adverse events occur, the traditional model is to consider the frailties and causal factors that contributed to such, in an attempt to design interventions to reduce the likelihood of future occurrence. However, when resilient interventions pre-empt or neutralise a threat, thus avoiding an adverse event, analysis is seldom deemed necessary.

While the concept of resilience is primarily considered as a property of sociotechnical systems, an emerging reconceptualisation of the term considers 'cognitive resilience' or the resilience strategies of users interacting with systems. Such strategies include creating cues to assist memory, appropriating items, ensuring resource availability, and so fourth. This work addresses these phenomena, exploring how users develop and deploy tactics to mitigate risk, minimise error and improve performance.

Previous Work

As noted, the targeted investigation of users' resilience strategies in HCI is relatively lacking. There are some parallels between this topic and workarounds in a HCI context (e.g. [START_REF] Kobayashi | Work co-ordination, workflow, and workarounds in a medical context[END_REF]), however we draw distinctions based on both coverage and consequence. Resilience includes many prospective, anticipatory interventions, as opposed to the generally responsive nature of workarounds. Moreover, where (particularly in safety critical domains), workarounds are generally deemed to be unconducive to safe practice, resilience is inherently by its definition a positive contributor to outcome.

Furniss et al have however described specific work in this area, and note that existing strategy-specific work largely constitutes anecdotal discussion, with little to frame or situate such accounts. This forms the rationale for their Resilience Markers Framework [START_REF] Furniss | A resilience markers framework for small teams[END_REF]. Furniss et al also offer a categorisation scheme to collate and consider themes across strategies, serving to facilitate discussion and analysis [START_REF] Furniss | Cognitive Resilience: Can we use Twitter to Make Strategies More Tangible?[END_REF].

While such work provides an insightful account of resilience as observed, efforts to empirically elicit examples of resilience or operationalise the concept in order to establish predictive power are seemingly not available to date. We present here an initial step towards achieving these objectives.

A Controlled Study into Cueing Strategies

As an early step toward isolating and investigating resilience strategies in a controlled setting, and owing to the apparent diversity of strategies, we initially opted to limit our scope to focus upon cueing-related strategies. Building on existing work [START_REF] Back | Resilience Markers for Safer Systems and Organisations[END_REF][START_REF] Dix | Designing for Appropriation[END_REF] that suggests users not only utilise, but in some cases develop or appropriate cues to assist prospective memory, we sought to investigate the effectiveness of user-configured cues in reducing placekeeping errors during a challenging and interrupted task.

Study Design & Hypotheses

We designed an independent samples study, with the dependent variable consisting of error rate across three independent variables; IV1: user-configured cues, IV2: systemincorporated cues, and IV3: no cue support. IV2 enabled comparisons against a baseline where cues had been designed into the interface, and IV3 was a control where no cues were intended to be available. Our primary one-tailed hypothesis was that userconfigured cues (IV1) would reduce error rates compared to the absence of cues (IV3). As a secondary, two-tailed hypotheses, we also anticipated a performance different between user configured cues (IV1) and cues hard-coded into the system (IV3).

Task Paradigm

The task composed for the study was modelled on a common, interruption-prone and HCI-relevant task within the medical domain: setting up the delivery of multiple medications. The task involved performing a number of relatively simple calculations (of a [speed = distance / time] nature, but for values: rate, volume and duration) followed by data entry, transcribing data from paper to onscreen form. The different conditions were represented in this interface, with IV1 featuring unpopulated arbitrary checkboxes that users could appropriate as cues, IV2 consisting of automated visual cues of a similar size and nature, and IV3 featuring no such progress-tracking UI elements.

In an attempt to isolate engagement with and effectiveness of these cues, we attempted to 'design out' other implicit cues in the interface. For example, participants were trained to confirm each value immediately upon entering it, which cleared the corresponding field (so values left in fields couldn't be used as a progress tracking cue). We also removed the standard blinking text-field cursor from the interface after a few seconds upon each field being selected, so this wasn't available as a cue.

During the task, participants were interrupted with a paper-based distractor task (checking completed calculations). The points of interruption were predetermined, and as with the design of the onscreen form, increased the threat of place-keeping error. Data capture was via automated logging of input, remote screen monitoring and recording, collection of paper sheets, and brief informal ad-hoc questioning upon completion. Finally, prior to the study proper, a limited pilot with users unfamiliar with the research was undertaken to elicit feedback on the task and instruction.

Findings and Observations

The task performance data did not reveal any relationships between condition (form of cue) and error rate, thus leading to the rejection of the experimental hypotheses. There were however two notable insights provided from this study, one regarding the conduct and resilience of our participants, and one related to setup and task paradigm.

Participants can be highly resilient, even when they're not expected to be.

One key insight was that despite our best efforts to carefully control available cues, participants were very proactive in establishing alternative and additional cueing behaviours and other strategies. This enabled them to maintain performance and manage the threat presented by interruptions. Participants were, to put it simply, far more resilient than we had anticipated, and found novel and innovative ways of coping when critical threats to their cognitive working capacity were presented. In terms of cueing, such strategies included utilising or marking paper sheets as external physical artefacts to track progress (n=13), restructuring the sequence of data entry into the onscreen form (resulting in values serving as implicit visual cues) (n=11), and using unanticipated digital artefacts as visual cues (e.g. the mouse pointer, or placing temporary and arbitrary values in fields; n=3). We also observed other types of potential resilience strategy, including the momentary deferring of experimenter interruptions (n=14), and intentional verbal rehearsal to assist memory (n=6).

Pitching the complexity of the task paradigm is key.

Another unanticipated insight was the significant level of individual variation of task performance between subjects, with total errors per participant ranging from 0 up to 13. This made it unfeasible, given the sample size available (n=29), to establish a baseline level of performance for each of the three groups.

While there is insufficient information to determine why this significant variation in performance occurred, we postulate this was largely a reflection of natural variation in subjects' dexterity with figures. Both the primary and distractor tasks involved calculation, and it was noted that some participants completed such exercises with relative ease using mental arithmetic, while others relied heavily on the provided calculator and appeared to find this aspect of the task more challenging.

Lessons Learned & Revised Study

The study showed that users may be more resilient than we give them credit for. Even in a tightly constrained task, users coped well and deployed unanticipated resilience strategies, a finding which has implications for future work. In our next study we will strive not to exclude potential unforeseen resilience strategies, but will be better equipped to recognise and account for them, and potentially capture more information to enable more targeted and rigorous analysis, providing additional insights.

Another important consideration would be to ensure a stable baseline performance rate could be established in a revised task paradigm, by reducing the level of variance in terms of individual differences. We propose addressing this consideration in three ways: (i) We will avoid the use of a numerical task, and are instead moving towards a paradigm where cognitive load is introduced by workload structuring and interleaving, and subtask sequencing (ii) we will seek to establish and participants' abilities and baseline performance in a screening activity, enabling us to control for variance, and finally (iii) we will employ more stringent and extensive piloting to ensure such a baseline in performance can be established, and will adjust task parameters as necessary to achieve this prior to execution of the study phase.

Acknowledgements

This work was supported by UK EPSRC grant [EP/G059063/1], CHI+MED.


Shah Rukh Humayoun
email: humayoun@cs.uni-kl.de

Achim Ebert
email: ebert@cs.uni-kl.de

Steffen Hess
email: 2steffen.hess@iese.fraunhofer.de

Gerrit Van Der Veer
email: gerrit@acm.org

Workshop on Designing Interaction and Visualization for Mobile Applications (DIViM 2015)

Keywords:

The DIViM 2015 workshop focuses on different issues and limitations regarding designing intuitive interaction and visualization for mobile applications and devices, as well as how to overcome these limits through novel approaches and techniques.

Motivation and Objectives

Current mobile applications (commonly abbreviated as mobile apps or just apps) are in many ways different from the conventional desktop applications due to factors like the usage of multi-touch gesture interaction, the availability of different sizes of devices, new operating systems, mobile access, the change of usage context in different circumstances, and so on. The recent advances in mobile paradigm bring new challenges and open issues in developing intuitive and interactive mobile apps [START_REF] Abolfazli | Review: Rich Mobile Applications: Genesis, taxonomy, and open issues[END_REF]. In this context, designing intuitive interaction and visualization plays an important role for many purposes, e.g., improved user experience and aesthetics. In addition, better interaction modes and suitable visual representations in mobile apps are critical for a successful execution of the users' required tasks [START_REF] Burigat | On the effectiveness of Overview+Detail visualization on mobile devices[END_REF]. However, this requires not only an intensive collaboration between the responsible parties -especially the interaction/UX designers, visualization and HCI experts -but also needs focusing on novel interaction and visualization approaches and techniques targeting this new mobile paradigm.

Inspired by the critical role of interaction design and visualization in the current mobile app development and the organizers' previous experience with the related fields (i.e., interaction designing, visualization, human experience, perception and multimodal input actions, and mobile apps), the workshop aims at creating awareness in the related communities to start focusing on novel methods, approaches, and techniques for utilizing the full power of interaction design and visualization in the current mobile app development at different levels, from showing the relevant information to enhancing user experience.

Workshop Details

Topics and Themes

DIViM 2015 is dedicated to observations, concepts, approaches, techniques, and practices that allow understanding, facilitating, and increasing the awareness of the role of designing and implementing intuitive interactions and visualizations for mobile apps. In this context, topics of interest for paper submissions include, but are not limited to: novel interaction and visualization techniques and methods targeting current mobile apps and devices; frameworks and approaches for designing new interaction techniques and intuitive visualization; novel visual interactive techniques targeting mobile devices; scalability issues; context and usage issues; accessibility and usability issues; interaction and visualization for mobile smart watches; user-centric interaction/visualization; testing/evaluation; tools and environments to support the designing and building of interactive visualization; case studies and best practices.

Target Audience

The workshop targets at researchers and practitioners with a background in interaction design, UX design, visualization, HCI, or mobile app development. The workshop provides a platform for discussing issues and limitations regarding design and implementation of intuitive interaction modes and visualizations for mobile devices as well as how to overcome current limitations and user disaffection through novel approaches and techniques.

Expected Outcomes

The workshop aims at achieving the following outcomes:

• Consolidating research and practices related to interaction design and visualization design in the context of current mobile apps and devices; • Establishing a platform for bringing the interested communities (such as interaction/UX designers, HCI/visualization experts, etc.) closer together to discuss how to make changes in the existing approaches and frameworks, as well as to examine novel methods for designing useful and intuitive interaction and visualization; • Growing the body of knowledge related to interaction and visualization design for the current mobile environment and identifying challenges and future avenues for research relevant to both academia and industry; • Providing a dedicated forum to the relevant communities for exchanging ideas and best practices; thus, foster collaboration between industry and academia.


Bingxin Ni
email: nibingxin1117@gmail.com

Abdullah Al Mahmud
email: aalmahmud@swin.edu.au

David V Keyson
email: d.v.keyson@tudelft.nl

Experiencing a Home Energy Management System: Finding Opportunities for Design

Keywords: Smart home control system, home energy management system, Chinese context, user experience

This paper reports a study, which examines how people experience a Home Energy Management System (HEM). We conducted a probe study with six families in China for two weeks. From our study, we found that people had difficulty in understanding energy data, which were shown as graphs. Families with teenage children showed more interest in using the Home-Energy Management System. Overall, all the participants were fascinated by the remote monitoring and controlling of the appliances offered by the probe. Based on the findings, opportunities for designing HEMs for the target groups are discussed.

Introduction

Home Energy Management Systems (HEMs)/eco-feedback systems are defined as intermediary devices installed at home that can visualize, monitor and/or manage domestic gas and/or electricity consumption [START_REF] Van Dam | Home energy monitors: impact over the medium-term[END_REF]. The end-goals of HEMs are to help homeowners to conserve energy, reduce cost of energy bills and improve comfort [START_REF] Ning | Research: Characteristics of Chinese Urban household energy consumption[END_REF]. It is a fact that residential energy consumption has been increasing each year in China due to the rapid urbanization [START_REF] Van Dam | Home energy monitors: impact over the medium-term[END_REF][START_REF] Fischer | Feedback on household electricity consumption: a tool for saving energy?[END_REF][START_REF] Lamarche | Home Energy Management Products & Trends[END_REF]. There exist a gap between an awareness of energy-conservation and behaviors, because it is difficult for users to link their various activities and develop a coherent, comprehensible, and concise cognitive frame of what energy conservation could mean in one's everyday life [START_REF] Fischer | Feedback on household electricity consumption: a tool for saving energy?[END_REF]. HEMs offer a worthy solution by providing timely feedback of daily energy usage. It is evident that some studies and experiments of implementing HEMS into people's life have been conducted in western countries [START_REF] Van Dam | Home energy monitors: impact over the medium-term[END_REF][START_REF] Petkov | Personalised eco-feedback as a design technique for motivating energy saving behaviour at home[END_REF]. Several Chinese companies have already stepped into this field and have started developing solutions. However, it is not known how HEMs can be applied to existing Chinese families, which arouses great curiosity for further exploration.

Experiencing the Plugwise HEMS package

To discover how people would feel using a home energy management system, user experiments were conducted in Chengdu, China. We used the Plugwise package [7] to assist participants to monitor in-home energy usage and take control of it. The Plugwise package contains four basic components such as one or more Circles, Circle+, USB Stick and Source Home Software. The Circle is plugged in between an appliance and the socket. It measures energy consumption of the connected appliances and can switch it on and off, and send the measured energy consumption data to the Plugwise software via Zigbee wireless network. The Circle+ has the same functionalities as a Circle, but also serves as the network coordinator to control and organize the network. The USB Stick is the connection between the Plugwise Source Home Software, the installed plugs (Circles) and other Plugwise products. After being connected to the USB port of the computer, the Stick receives data from and transmits commands to the installed Plugwise modules. Source Home is the Plugwise software for visualizing energy data and controlling appliances. Ten upper-middle class families responded to volunteer the experiments. However, four families did not install the Plugwise program (three families felt uninterested and bothered to install it, and one family was leaving for a vacation and found no time to experience the Plugwise package). Hence, in total, six families used the Plugwise package for two weeks.

Procedure

On the first day, the Plugwise PC program was installed by the first author. Later on, participants were asked to choose several household appliances to be connected with the Circles to measure electricity consumption (see Fig. 1). After the program was ready and all the hardware were well connected, the interface was shown to the participants with an explanation of each item. Then sensitizing cards were left to participants to fill in. People were asked to first explore the program and then answer a few questions, which would reflect their experience with the Plugwise system. Finally, they needed to fill out the task cards after each time they checked energy usage data. On the day when the Plugwise package was picked up after the study period, the participants completed an evaluation form and participated in short interview sessions. The sensitizing card consists of three parts: 1) collect first time user experience, 2) task card to understand why participant would like to use the probe, what kind of data they are concerned about and what is their emotion, and 3) an evaluation form, to get an overall opinion of the system. The interview data were analysed thematically.

Results

Test participants cared more about high-energy consumption appliances. They always chose what they thought were high energy consuming, such as television, water kettle, laptop and refrigerator. However, they did not choose air conditioners because it was not the right time to use them. They appreciated that it was easy to use the Plugwise hardware but some participants thought it was troublesome to install the plugs for the first time. Furthermore, they felt it was quite like magic that with just a small device, they could track energy consumption of their household products in a simple way. However, since it was only a test for a shorter period, participants did not feel a strong involvement with the system. Families with teenage children showed more interest in HEMs. From the sensitizing booklet, some feedback were received, such as when asked what emotional feeling they might have when they checked energy information on the Plugwise dashboard. Participants reported that it was interesting to receive energy feedback. Participants had questions about energy consumption such as how much electricity it would consume if the computer was on for the whole night? How much electricity it would consume for one light and how much they could save? These detailed information were present however, participants did not know how to switch between different views in the Plugwise dashboard.

The energy feedback data were understandable, but they could not evoke a sense of caring of the participants because the data were found meaningless to them. Two of the participants mentioned that the reasons for causing the changes were not clear to them, which made them feel frustrated after seeing the graphs. Participants were not interested in seeing the numbers and information provided on the interface. They reported that the data in kWh and graphs are generally understandable but quite meaningless to them. "I know what this means, but I need energy forecast. Since I still have to consume this amount even I know its energy usage, I am not sure this system will make a difference on my family." (One person from family #5). "Those data are not hard to understand, but according to my knowledge, I cannot understand why the curve is shaped like this? I want to know the reason caused the changing which I cannot find in the program." (One person from family #1)

Participants were very interested in the turn on/off the appliance function provided by the Plugwise HEM package. Participants were quite surprised by remote control function when it was shown to them and later when they interacted with it. One participant even asked to set a schedule for their television because sometimes they fell asleep and left the TV on for a whole night.

Discussion and Design Implications

For some families, the program could only be installed on a desktop computer, which they used very often. Hence, it was not convenient to check the energy data now and then, which was the limitation of the Plugwise HEMS package. They treated the Plugwise system as a test rather than their own property, so they did not pay much attention and did not truly experience it, either. At this phase, by using the system, it is important to help users to cultivate their awareness of in-home energy management. Making energy more transparent to people proved to be a key insight for changing consumers' attitude and behaviour towards saving energy [START_REF] Darby | The effectiveness of feedback on Energy Consumption. A review for DEFRA of the literature on metering, billing and direct displays[END_REF][START_REF] Petkov | Personalised eco-feedback as a design technique for motivating energy saving behaviour at home[END_REF]. Although it is argued that money is not a good stimulus to rise people's attention in the long run, it is still of great necessity in the early development phase when people start to experience any HEMS. Another remarkable finding was that participants were more attracted to the remote control of household appliances rather than the home energy management system. The reason was that the remote controlling of appliances at home provided them direct advantages when compared with the home energy management system. This also verifies that if users could be offered some benefits, they could pay more attention to HEMS. Besides cost-effectiveness it is an influential aspect to consider when designing HEMs for the target group. From the study, it has been revealed that the target groups are positive to accept the notion of controlling home appliances remotely, which can be considered part of HEMs. Therefore, it is assumed that integrating HEMS with smart home control system could be a good idea for the target group. Another key design issue is the visualization of the energy data, which should be more meaningful to the users and help users to get engaged. Though our study period was quite short and the Plugwise package had several limitations, it was helpful to gather valuable feedback, which provided directions for designing an adapted Home Energy Management System (HEMS) for the target group.

Fig. 1 .

 1 Fig. 1. Circle+ is connected to a television; circles is connected to a desktop and to a refrigerator (left to right)


Gerhard Weber
email: gerhard.weber@tu-dresden.de

Christopher Power
email: christopher.power@cs.york.ac.uk

Helen Petrie
email: helen.petrie@cs.york.ac.uk

Jenny Darzentas
email: jennyd@aegean.gr

Learning Beyond the Classroom: For and About Older and Disabled People

Keywords: Accessibility, MOOC, elearning, older learners, disabled learners

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Overall Concept of the Workshop

A number of studies [START_REF] Power | Virtual Learning Environments: Another Barrier to Blended and E-Learning[END_REF][START_REF] Bohnsack | Accessibility of MOOCs[END_REF] have shown that eLearning platforms can be made accessible, although barriers require specific attention. While typical tasks such as navigation in learning materials, or participation in a forum or a wiki can be made accessible to learners even if they use assistive technologies or augmentations (e.g. subtitling to videos), more advanced tasks such as assessments (e.g. multiple choice quizzes) and the use of specialist notations (e.g. mathematics, chemistry, music) common in education require more advanced accessibility knowledge.

The right to equal access to the educational system has been strengthened by the UN Convention on the Rights of Persons with Disabilities [3] but only at a high level. Developing an action plan suitable for educational institutions at various levels includes both the need to review institutional approaches to identify and strengthen all stakeholders in order to develop more inclusive approaches in classroom teaching and distance education, as well as the provision of education about accessibility in the education system as well as particularly in technology industries. In addition, in an ageing society, life-long access to education is becoming an important issue.

The workshop will identify possibilities for making technology-mediated learning (TML) (learning, blended learning, MOOCs) more accessible and acceptable to disabled and older people. In addition, the workshop will analyse how TML can be used to educate professionals about the needs and wishes of disabled and older people in relation to technology. The accessibility of TML relates both learning design and the learning environment. This includes inclusive approaches to asynchronous/synchronous communication, and the accessibility of microteaching (e.g. in MOOCs). Even if the competence of both teachers and learners can be met, there is still a need to change existing practices related to TML. The workshop will discuss processes to activate all stakeholders related to TML. In particular MOOCs may be a new approach to attract teachers or trainers who encounter a deficit in their practices and who want to become more capable of addressing a wider spectrum of learners.

Organisers

This Workshop is organized on behalf of IFIP WG 13.3 HCI and Disability by: Professor Gerhard Weber, Chair in HCI at Technische Universität Dresden. His research focuses on personalization of multimodal systems for the benefit of people with a disability.

Professor Helen Petrie, Chair in HCI at the University of York, current chair of IFIP WG 13.3. Her research focuses on the design and evaluation of technology for disabled and older people.

Dr Christopher Power is a Lecturer at the University of York. His research aims at creating interactive web systems for all, focusing on disabled and older people.

Dr Jenny Darzentas works at the University of the Aegean. Her research focuses on the design of accessible and usable content.

Expected Outcomes

This workshop will develop a better understanding of the processes needed to raise the accessibility of technology mediated learning for disabled and older learners and the methods and content to introduce accessibility topics into education at all levels.


Junia Anacleto

Sidney Fels
email: ssfels@ece.ubc.ca

Towards a Model of Virtual Proxemics for Wearables

Keywords: Wearables, proxemics, virtual proxemics, control-based spaces 1

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

As wearable technologies promise benefits from invisibly sensing your body's state, providing unobtrusive, attention-free access to your digital world and providing an "always on, always connected" experience [START_REF] Mann | Wearable computing as means for personal empowerment[END_REF], these same features exaggerate the range of consequences due to unauthorized data access. The issue arises from the desire to minimize the amount of attention the wearer pays to the technology leading to a potential loss of control of who can send or access data from the wearer [START_REF] Viseu | Simulation and Augmentation: Issues of Wearable Computers[END_REF]. Attentional and use design categories of wearable technology, presented in ( §2), include not being visible, close to the body, sensory linked and un-monopolizing and controllability. Some of these conflict with each other, greatly impacting actual and perceived levels of data control [START_REF] Viseu | Simulation and Augmentation: Issues of Wearable Computers[END_REF]. As the data becomes more sensitive, due to the types of application areas for wearables, the potential loss of control can lead to a sense of violation if inappropriate access behaviour occurs.

In the physical world, social and cultural protocol and physical proximity provide cues for appropriate behaviours with respect to a person's personal space [START_REF] Hall | Handbook for Proxemic Research[END_REF]. To understand how the physical space around someone defines her/his comfort zones, Hall introduced the theory of proxemics [START_REF] Hall | The hidden dimension[END_REF]. In Hall's theory physical distance from a person provides comfort categories mapped as distance based zones. These zones then provide a sense of socially and culturally associated acceptable distances for different types of people based on familiarity. For example, from 0-45cm is a person's intimate space reserved for people that are intimate with the person. Someone, say a colleague, who comes within this intimate space, may cause feelings of discomfort and violation due to the lack of control available at that distance.

The virtual world does not have a direct equivalent to physical distance, however we argue that the degree of control a person has over data can serve the same function when defining a Virtual Proxemics. Specifically, the less control of data a person has, the closer it is to his/her intimate data space, while the more control they have, the closer to their pubic data space as shown in figure 3. Then, similar to Hall's proxemics, the virtual proxemics determines the comfort level a person has from someone accessing or sending data into their data spaces depending on their relationship with them. So, data in a person's intimate data space can be comfortably sent to or accessed by a person's intimates, but a violation will be felt if it is from more distant relationships. We also argue, that virtual proxemics can be used in the same way that Greenberg [START_REF] Greenberg | Proxemic interactions: The New Ubicomp?[END_REF] uses Hall's proxemics for technology to function when people (or technology) are physically close. That is, the virtual proxemics can provide cues for how a person's data space may be accessed based on the types of human relationships. Thus, virtual proxemics is a model for defining what level of control to provide for a user over their data space, as well as the possibility to automate this control to better allow attention free properties of wearables to be exploited.

In this paper, we describe how virtual proxemics applies to wearables and why the design criteria for wearables emphasize the need for a model based on Hall's proxemics. We begin with Related Work ( §2) discussing wearable technology by describing some of the main factors that have been identified in the literature that impact virtual proxemics. We also present related work on the proxemics theory and how it has been explored in computer science. We present the details of Virtual Proxemics in ( §3). We then present a wearable prototype in ( §4) where we fixed the level of data control and experience two different community relationships with the wearer. We also discuss the observations from the experience in ( §4). Finally we conclude and discuss future work in ( §5).

Related Work

Wearable technologies have emerged as an important direction for the next wave of sensing, fabrication, computing and communication technologies. As the technologies are intended to be worn, key factors related to adoption and effectiveness of the technology have to be addressed. A number of the factors for each of the design character-istics can compromise a wearer's ability to control data flow. We highlight these particular factors as they relate to virtual proxemics.

Related Properties for Wearables

Wearable design characteristics, from hardware to software, from appearance to comfort, from body fitting to garment-technology integration, have been presented by: Mann [START_REF] Mann | Wearable computing as means for personal empowerment[END_REF] who defines attributes for wearables' behavior, Gemperle et al. [START_REF] Gemperle | Design for Wearability[END_REF] who define guidelines for wearability, and Todi and Luyten [START_REF] Todi | Suit up! Enabling eyes-free interactions on jacket buttons[END_REF] who present design goals for wearables.

In particular, Mann describes a general framework for comparing and studying wearable technologies with six necessary attributes for a wearable computer in order to better serve wearers. These attributes are: it (a) must be un-monopolizing of wearer's attention, it (b) must be unrestrictive to the wearer's tasks, it should be (c) observable and (d) controllable by the wearer, it should be (e) attentive to the environment and, it should be (f) communicative to others. His framework is focused on how the wearable technology should behave when worn. However, considering the virtual proxemics perspective, some of the attributes conflict with each other when providing necessary data control in the virtual space, e.g. un-monopolizing wearer's attention and controllable by the wearer. By un-monopolizing the wearer's attention, the user may not be aware of state changes that would require his or her attention; thus, even if the system is controllable, the wearer wouldn't use those controls. Likewise, if the device is controllable, it may require too much attention for the wearer to use effectively. Thus, following these principles may make it more difficult for a wearer to exercise control of their data spaces leading to a higher likelihood that their data space could be violated.

Concerns about aesthetics and interaction are raised based on the design goals presented by Todi and Luyten [START_REF] Todi | Suit up! Enabling eyes-free interactions on jacket buttons[END_REF]. Their first two design goals consider aesthetics problems and the last three consider interaction situations: (1) The wearable device can be integrated into existing clothing, preventing wearers from having to wear additional accessories to achieve the desired interactions; (2) The technology is not readily visible to the naked eye, allowing for inconspicuous interactions and does not compromise the aesthetics of the clothing; (3) Interactive elements should be easily reachable, and allow for eyes-free interactions; (4) Each entity has its own dedicated functions, to avoid mode-switching; and, (5) Individual elements should be linked together to form an automated workflow, what would guide us in our design. The inclination to hide the technology, provide an automated workflow and lack of mode switching may impede actively changing data space access; however, having each entity easily reachable may help the wearer; again providing potential design tradeoffs around data control for the wearer. Todi and Luyten included additional missing goals to support designing wearables, hence, Mann's attributes naturally combine with them. Together, these form a useful set of factors to attend to when developing wearables.

Considering the interaction between the wearer's body and the wearable, issues on wearability are brought forth by Gemperle et al. [START_REF] Gemperle | Design for Wearability[END_REF] as a concern when designing wearable computers. They describe 13 guidelines that cover wearability by discuss-ing: (i) Placement determines where the application should go considering the dynamics of the human body. To guarantee a placement in unobtrusive locations the areas should: be relatively the same size across adults, have low movement/flexibility, and have large surfaces; (ii) Form language defines the shape of the application to ensure a comfortable and stable fit; (iii) Human movement takes into consideration the dynamic structure of the human body and suggests designing around the more active areas or creating spaces on the wearable to allow movement; (iv) Proxemics guideline relates to the human perception of space and dictates that forms should stay within the wearer's intimate space; (v) Sizing takes into consideration the different types of body that could use the wearable application; (vi) Attachment should also consider the different body sizes on top of offering a comfortable form of fixing the application to the body; (vii) Containment remembers the designers about the constraints brought by the components of the wearable application; (viii) Distribution of the application's weight and how it should not hinder the body's movement or balance has to be considered; (ix) Accessibility suggests testing to verify if the physical access to the wearablewearer forms is adequate; (x) Sensory interaction states that the interaction should be kept simple and intuitive;(xi) Thermal issues can arise when placing processing intensive modules close to the body; and (xii) Aesthetic means the wearable should be seen as appropriate by the group of people wearing it; (xiii) Long-term use guideline is about the effect an application may have on the body and mind.

Gemperle et al. [START_REF] Gemperle | Design for Wearability[END_REF] sometimes refer the guidelines as suggestions, states, or definitions, suggesting that some of them have different impact into the design. However, from our perspective all of the guidelines seem relevant enough so that they should be considered for a successful design process for wearables.

Although the discussion of these properties are not stressed in here, they formed the basis for developing the wearable prototype and we are continuously investigating which and how these characteristics impacts the relationship between the wearers and the technology as well as the people they are interacting with, mainly focused on virtual interactions. In this paper, the considered context is the degree of controllability the wearer has and how this impacts his or her feelings of comfort when virtually communicating with a remote group that are either intimate or part of a public related group according to Hall's theory.

Proxemics Theory

The term proxemics is used by Gemperle et al. [START_REF] Gemperle | Design for Wearability[END_REF] to name their guideline iv in which the distance between the wearer and the wearable is determined as the wearable device being placed in contact with the wearer's body, using the concept of intimate space based on Proxemics Theory by Edward Hall [START_REF] Hall | The hidden dimension[END_REF], shown in Fig 1 . Hall's theory includes distance among people, not only between wearer and wearable, and describes a type of nonverbal communication based on distance and level of intimacy considering a body-centric perspective: close to a person is the intimate circle, and away becomes public space. Such terms were coined by Hall to explain the concept of social cohesion, describing how people behave and react in different types of culturally defined personal spaces. According to Hall, proxemics theory was defined as "the study of man's [sic] transactions as he perceives and uses in his intimate, personal, social, and public space in various setting" [START_REF] Hall | Handbook for Proxemic Research[END_REF] mainly related to other people. Although Hall uses the term 'space' to discuss proxemics, we understand that, in fact, his discussions about spaces are more focused on one single dimension of space: a layer of horizontal distance from the central subject at the height would be as tall as the subject.

In Hall, the Intimate space represents the distance for those allowed to touch and be touched by the subject; Personal space is reserved for friends and family; Social space is used for social and work interactions; and, Public space is used for public occasions (e.g.: distance kept from people in a market, plaza or a nightclub). Finally, each of these spaces has variations inside them according to cultural and individual values related to the perception of proximity. These spaces are interpreted and illustrated in figure 1. The image considers 2 axes: distance from the person's body versus degree of intimacy: the bigger the distance, the smaller the degree of intimacy, impacting on our behavior and interaction with others, as people transition from one circle to another. In the work reported here, our model uses the same names from Hall to relate physical space to perceived degree of control as well as the categories of relationship between the wearer and others they encounter. Likewise, we use the same names Hall gives to the level of intimacy between people. We use this mapping to suggest the type of behaviour that the wearable should evoke in the wearer when violations of their data space occur. In our studies, we adapt this Proxemic Theory as a model to represent the concept of Virtual Proxemics for wearables as described in section 3. For this, we interpret the different spaces Hall identified as relating to a person's need for control around their physical space as the distance between other people changes. However, in our adaptation to the virtual data space, we consider the degree of control over a data space to be the correspondence of distance. Thus, we map Intimate space to Intimate Data intimacy Space, Personal space to Personal Data Space and Public space to Public Data Space based on degree of control. In our mapping, the least control over data is considered intimate and the most control over data to be public. Thus, in the same manner as a stranger entering your intimate space is a violation, so would public access to your Intimate Data Space be. However, a close relation, such as a spouse, would have access. Note that we consider data space to be bidirectional where a wearer can be putting data or receiving data into their data spaces.Proxemics in Computer Science Even though proxemic theory is more commonly associated with disciplines other than computer sciences, such as architecture and social sciences, ubiquitous and pervasive computing made such study useful in the context of Human Computer Interaction (HCI). In Virtual Reality (VR), Hall's proxemic theory has been used to study how behaviors that happen in the physical world translate to the virtual world ([2], [START_REF] Wilcox | Personal Space in Virtual Reality[END_REF] and [START_REF] Hasler | Sociocultural Conventions in Avatar-Mediated Nonverbal Communication: A Cross-Cultural Analysis of Virtual Proxemics[END_REF]). Human-Robot Interaction (HRI) has used it to better design how people could interact with robots [START_REF] Takayama | Influences on Proxemic Behaviors in Human-Robot Interaction[END_REF], their acceptance [START_REF] Mumm | Human-Robot Proxemics: Physical and Psychological Distancing in Human-Robot Interaction[END_REF], trust [12] or even robot's behavioral changes to interact with people from different culture to consider social norms [START_REF] Joosse | Lost in Proxemics: Spatial Behavior for Cross-Cultural HRI[END_REF].

Greenberg et al. [START_REF] Greenberg | Proxemic interactions: The New Ubicomp?[END_REF] presented the concept of proxemic interactions for ubiquitous computing systems where they explore how to design systems to respond as a person would, adding four variables, besides distance, to correlate the human proxemics to 'smart' information and communication technology (ICT) proxemics, such as orientation, movement, identity and location. By doing so, they provide their ICT systems some human senses to give awareness about proximity beyond only a front camera to capture the presence of a user or other 'smart' technology.

In the ICT context, there are two main relationships involving interactions to which Greenberg applied Hall's proxemic circles in order to determine the technology's behavior: (A) the interaction between technological devices and user and, (B) the interaction between technological devices and technological devices, as shown in figure 2. However, the similarity in both contexts shows that Greenberg's main point is the proxemical behaviour of ICT related to users (with or without a device mobile mediation).

(A) (B) Fig. 2. Greenberg et al [START_REF] Greenberg | Proxemic interactions: The New Ubicomp?[END_REF] definition for ICT proxemic interaction between (A) located technology and user and (B) located technology and users mediated by a mobile device (from [START_REF] Greenberg | Proxemic interactions: The New Ubicomp?[END_REF]).

In the studies presented here, the proxemic theory and additional variables were combined and used to analyze and better define technology's automatic behavior so that it fits better with the user's expectations based on intimate space. This is particularly evident in Greenberg et al.'s work with proxemic interactions. From the weara-ble computer perspective, we consider Greenberg et al.'s work may also be applicable to how technology should mediate control of a wearer's data spaces to ensure that appropriate access is provided in situations where the wearer's attention, or the design of the garment, makes it difficult for the wearer to do so.

Control of Data Spaces and Wearable-based Interactions

Additional complexities in data control with wearables have been identified by Viseu [START_REF] Viseu | Simulation and Augmentation: Issues of Wearable Computers[END_REF]. She makes the point that wearables, through connection with the digital world, augment the physical world where the wearer is the host for the technology. She identifies that some wearable researchers (i.e. Mann [START_REF] Mann | Wearable computing as means for personal empowerment[END_REF], Gershenfeld [START_REF] Gershenfeld | When things start to think[END_REF], Barfield [START_REF] Barfield | Computational Clothing and Accessories[END_REF] to name a few) believe that technology gives user more control over the environment while others like Lessig [START_REF] Lessig | Code and other laws of cyberspace[END_REF] argue it provides less, since the wearer can end up being controlled by the technology, such as an employee being monitored by an employer. She further makes the observation that this aspect of wearables transcends control and power to the realm of cultural biases. Hall's theory acknowledges how critical this aspect is. In adopting a model based on Hall's theory, we also encapsulate the elements of social protocol and cultural norms about what is appropriate for people to access within a person's data space.

In the literature on wearables, there are examples of virtual proxemics at play to support the view that people do have a sense of different levels of comfort based on different elements of how a wearable data is used. For example, Mann's work on a wearable technology allowing him to block out the world [START_REF] Mann | Wearable computing as means for personal empowerment[END_REF] is a form of complete control of his visual channel. By doing so, he keeps data outside his intimate data space to extent that people would need to pay him to enter it. Augmented reality with a head's up display that doesn't completely block the wearer's view provides filtering on what the wearer sees. Further along the continuum of control are wearables such as Google Glass that do not block the view, however provide opportunities for interpreting what is seen. In these examples, we can see that wearables provide differing levels of control over visual data that can be placed on the continuum of virtual proxemics.

The model of virtual proxemics can also be applied to establish appropriate access control responses by the technology, much as Greenberg et al [START_REF] Greenberg | Proxemic interactions: The New Ubicomp?[END_REF] uses Hall's theory to determine how technology should behave as discussed in the previous subsection. Even though, they are looking more at technology-human and technology-technology interactions rather than human-human mitigation, we believe their thinking extends to human-human interaction. Angelini et al. [START_REF] Angelini | Hugginess: Encouraging Interpersonal Touch through Smart Clothes[END_REF] proposed a combination of wearable technology to mediate sharing user information when two wearers hug. Using the technology to sense proximity, length of hug and history of hugging allowed the system to infer that those two wearers are intimate, thus, allowing access to each person's intimate data space.

A more direct interpretation of Hall's theory applied to control and wearables within a person's intimate space is the Spider Dress [START_REF] Kaplan | Is That a Spider on Your Dress or Are You Happy to See Me? Intel -Innovation Everywhere[END_REF]. The dress senses when someone enters a wearer's personal space combined with the wearer's breathing pattern raising menacing spiderlike arms preventing close contact. If the system were to also know whether an approaching person is an intimate from understanding the breathing pattern related to fear or excitement, it could keep its arms lowered. Ideally, for an attention free wearable, the technology would know how to establish this relationship. In a sense, the virtual proxemics model should provide the wearer a sense of the spider arms over their data space when a non-intimate sends data or wants to read the wearer's data.

Puikkonen et al. [START_REF] Puikkonen | You Can Wear It, But Do They Want to Share It or Stare at It[END_REF] also represent a similar concept with a performative wearable technology to explore inappropriate attention. Though, Puikkonen et al's also expose how the proximity and intimacy of interaction between the wearer and the wearable can lead to the wearer not always being aware of what is happening, leading to a concern over one's right of privacy and a low level of acceptance of certain wearable devices, as shown in [START_REF] Schuster | The revolt against Google 'Glassholes[END_REF] and [START_REF] Zennie | Tech pioneer with augmented-reality glasses bolted to his head traps Paris McDonald's workers 'who tried to rip the device off his face[END_REF].We argue this design characteristic of wearable technology leads to a lack of control of their data space, implying that all interactions with this data space should be treated as a person's intimate data space.

In contrast to collocated interactions between people, wearables also provide a means for communication between remote participants. Work such as Min and Nam [START_REF] Min | Biosignal Sharing for Affective Connectedness[END_REF] used wearable technology 'to bridge the communication gap between people in close relationships who have to live apart'. They collected one of the partner's biosignals and reproduced them to their distant partner using wearable prototypes, so that this partner would feel more connected by physically feeling their partner's heartbeat and breathing rate. Differently from the work of Min and Nam, He and Schiphorst [START_REF] He | Designing a Wearable Social Network[END_REF] explored the concept of mediated communication using wearables and presented a wearable prototype named Patches that allowed for two-way nonverbal communication. In this prototype, the wearer could be poked via a Facebook application by one of his/hers friends and receive the poke on the prototype by simulated feelings of warmth and pressure from one of the patches. In turn, the wearer could return the poke by pressing that patch. When the wearer and observer are physically distant from each other, the wearable becomes the sole channel of communication, effectively mediating the communication between the wearer and observer. In this situation, it may be difficult to know the relationship between the two actors as physical proximity cues are unavailable. Explicit representations are needed, such as using Facebook settings as done in He and Schiphorst [START_REF] He | Designing a Wearable Social Network[END_REF]. However, these mechanisms then require attention from the wearer, conflicting with some of the desired wearable characteristics brought by Mann. We argue in these situations, where a wearer has not specified explicit control, that the data space has to be treated as their intimate data space.

In summary, many of the related wearable technology explorations have touched upon the challenges of how wearable technology provide channels of data to and from the user and that depending upon the control of the data, can lead to feelings of empowerment, disempowerment, comfort, discomfort. In next section, we describe how virtual proxemics is a suitable model for wearers to think about their data spaces and what degrees of control they have. This model also establishes a means to discuss the socio-cultural biases of power and control over people's data spaces in more structure fashion.

Virtual Proxemics

Our model of Virtual Proxemics derives from Hall's theory of physical proxemics. However, we use degree of control as the measure for the different categories of data space in contrast to physical distance for Hall's proxemics (shown in figure 1). In figure 3 we illustrate our mirrored representation of virtual proxemics with data space replacing physical space and the dimension of control replacing distance. As in Hall's proxemics, we envision the virtual proxemics as a continuum with some useful categories that can be identified as related to the type of relationships between people. 1 included for comparison. In virtual proxemics, the higher the degree of control of the data space (i.e. data coming in or out) the lower the level of intimacy in the data space. For example, for data where the wearer has no control of the data, it would be considered in their Intimate data space.

Fig. 3. Representation of virtual proxemics with Hall's physical proxemics from figure

As shown in figure 3, Intimate data space is one where the wearer has little or no control of the data (or doesn't need/want to have). The data may either be directed towards the wearer such as messages, images, voice etc. or coming from the wearer, such as sensor data, annotation, messages etc. For example, a text message appearing in a head's up display coming from someone that isn't filtered or blocked enters a wearer's intimate data space. Or, a heart rate sensor that sends its data to a third party cloud service is in the wearer's Intimate data space. As the amount of control increases over the data, the data space becomes further out to be Personal data space, then Social data space and finally Pubic data space. In the wearer's Public data space he or she has complete control of the data including being able to completely block all incoming or outgoing data. Social space may include filters or other manipulations that mask or block data such augmented reality glasses that filter out advertisements. The Personal data space is where controls provide interpretation of data but does not completely block or filter it such as aggregate data from sensors being sent to a third party.

Virtual proxemics for a wearer's data space serves two potential roles. First, for wearers, by providing this model they may more easily understand the type of exposure they will have to data coming to them or from them allowing them to make better choices about the technology. While wearable technology can be taken off or left in a drawer to block all data, implying that everything is in wearer's Public data space, this does not address the issue of when people want to use a wearable technology. The desire for always on, attention-free, and an invisible form factor imply that manual data controls that do exist may be difficult to attend to or need to be pre-specified and then forgotten about. However, this may compromise wearers' comfort when something unanticipated happen and wearers are not aware or do not want to stop what they are doing to address it. Virtual proxemics categories provide an explicit way to understand any prespecified settings and also communicate when anyone is entering a certain data space so the wearer will know what to do. The second role, much like Greenberg applies Hall's proxemics is that the categories can be used for having the technology automatically managing someone access to wearers' data space and attempting to provide access only to the appropriate data space. Thus, if a cloud service provider attempts to store a wearer's heart rate data, the system could infer that the cloud service provider is a Public member so would not have access to any data in the wearer's Intimate, Personal or Social data spaces, which would include the heart rate data as the wearer was not exerting any data control of that sensing data. Thus, such privacy policy provided by the Virtual Proxemics model would avoid a potential feeling of being violated, what guarantees wearers' empowerment and data control. Alternately, the wearable can evoke an awareness response from the wearer so they have a visceral sensation that a breach is happening.

As to this second role, a number of wearable technology researchers, such as, [START_REF] Cercos | Watch your Steps: Designing a Semi-Public Display to Promote Physical Activity[END_REF], [START_REF] He | Designing a Wearable Social Network[END_REF], [START_REF] Hong | STEPS": Walking on the Music, Moving with Light Breathing[END_REF], and [START_REF] Min | Biosignal Sharing for Affective Connectedness[END_REF], use study participants with known close social relationships. For example, Cercos & Muller [START_REF] Bell | Secure Computer Systems: Mathematical Foundations[END_REF] avoid privacy concerns by having participants who knew each other and worked closely together on a daily basis, i.e. would likely have been in the wearer's Personal or Social circle. Min & Nam [START_REF] Min | Biosignal Sharing for Affective Connectedness[END_REF] provide some insight that the sense of virtual proxemics is understood with their participants, as they noted that some users commented that they would feel considerably different depending on their relationship with the connected partner.

Finally, for this second role, we have not specified access control policies that could be applied to facilitate automatic mechanisms to alert wearers about potential transgressions, much like the spider dress tries to with real proxemics. With respect to confidentiality of data being read by members from different levels of intimacy, access policies such as Bell-Lapadula model [START_REF] Bell | Secure Computer Systems: Mathematical Foundations[END_REF], fit with the intuition for access we propose for virtual proxemics. The approach of "no read up, no write down" is consistent with the notion that if someone from a given comfort circle of the wearer tries to read data from a closer data space the wearer would be made aware of the transgression. Likewise, if data is being written from a close data space to a farther one, the wearer would be notified; but would not be for the other way around. In this way, only potential data confidentiality breaches require attention from the wearer. With respect to integrity of the data, models such as Biba's [START_REF] Biba | Integrity Considerations for Secure Computer Systems[END_REF] could also be applied. In this case, the "no read down, no write up" can be applied to alert the wearer of potential data integrity problems. The Cat in the Map Experience The Cat in the Map is a wearable-based functional prototype designed to provide communication between the wearer and her community when she is out of the community, as shown in figure 4.

(1)

(2) (3) Fig. 4. 'The Cat in the Map' system with the three primary data paths: SMS, photo and GPS.

The system has three main parts: (1) the wearable prototype that collects position data of the wearer and allows her to take pictures; (2) a REST API that creates the bridge between these two parts; and (3) the community shared display showing where the wearer has been, photos taken, messages sent and the send message widget.

The wearable was designed to extend the wearer's senses by allowing her to send her location and photos taken while she walks. The location and photos she takes are presented on a shared display for the remote community. The community could also send real time messages or photo requests to the wearer; the wearer could then choose to do so or not. Together the wearer and community had bidirectional communication so that the community could see what she sees and where she is and send messages and requests.

Our wearable prototype had three main functionalities: taking a picture, collecting GPS data and uploading such information to the servers. These functionalities used the camera module and a push button; GPS module; and, Wi-Fi dongle, respectively; with the Raspberry Pi as the processing unit. In terms of controlling the data chan-remote community wearer nels, the wearer could choose when to take a photo. However, she did not control sending GPS data to the shared display so anyone watching could see where she was. Using the phone, anyone in the remote community could send an SMS to the wearer. These messages would appear on her phone and she could choose to ignore or not after she read it; thus, she was not able to filter messages prior to receiving them, nor could she delete them. Figure 5 shows the hardware built in the wearable. To see the effect of the data control on her feelings with respect to the data spaces created in this prototype, we had one wearer (female graduate student) and two communities in different relationships to her, i.e., co-workers and partner.

In the co-worker condition the wearer walked around a university campus for 4 hours. During this period, she went about her regular activities (e.g. walked around the campus, stayed at the laboratory, had lunch, etc.). The shared display was put in the entrance lobby of her department at the university. Many observers stopped to watch the photos and the path she was taking. She received ten messages: four were requests for photos (e.g. 'Take a picture of my house' -Ant Man), two were comments (e.g. 'Where's the cat now?' -V.), and four were jokes (e.g. 'A neutron walks into a bar […]' -Dr. Sheldon Cooper). The comments and anonymous jokes sometimes had content classified by the wearer as 'insulting', like 'Fresh meat -Hannibal'. These situations made the wearer feel uncomfortable and 'invaded by strangers'. She also commented that she didn't want them to know where she was. This observation suggests that the lack of control of the GPS data appearing on the shared display and the messages coming from the remote community make her uncomfortable. The violation made her feel powerless and 'deeply unmotivated' to continue the interaction, as reported.

In contrast, for the second condition with her partner at the shared display in his home, she used the Cat in the Map for a period of 2 hours. During this period, twelve messages were received such as: comments (e.g. 'Wow, it's huge'), expressions of concern (e.g. Seems windy, did you bring your coat sweetie?) and requests (e.g. '[…] take some pictures of that World of Science place. […]'). Unlike in the co-worker case, the sender identity was known. The wearer reported to have a 'more pleasant experience' on sharing the photos and receiving requests of photos, comments and advice from her partner.

The prototype was designed to have the GPS and messages in the wearer's Intimate data space. Though, the photos were in her Public data space in that she could choose when to take a photo. As expected, her partner, being intimate, did not cause discomfort when he either sent or watched her moving on the shared display. In contrast, co-workers, not being intimates, caused discomfort accessing her Intimate data space. This is consistent with our view of Virtual Proxemics.

Conclusion

We presented a model of Virtual Proxemics derived from Hall's proxemic theory. In Virtual Proxemics the degree of control defines different levels of intimate data spaces from Intimate, Personal, Social and Public in the same way Hall's proxemics defines these for distance from a person. We argue that this model is important for wearable technology design due to the design characteristics of wearables often interfering with the ability for people to control data coming and going from their wearable device. Specifically, attention-free, invisibility, sensory linked, controllability and always-on characteristics in wearable design compromise a wearer's ability to control the data channels. Yet, people understand the social and culturally biased physical space around them as Hall pointed out. Thus, these same understandings can be applied to their data spaces as well. By doing this, it is easier for wearers to understand the complexities of data access policies. This is particularly important once data often associated with wearables is quite sensitive. The other advantage derived from this model is the possibility that technology can be used to infer a wearer's relationship to people that are entering different parts of their data spaces and can provide appropriate protection. We presented an example wearable system where we constructed an Intimate data space to see whether access to it by people in the wearer's Social circle made her uncomfortable, which it did. Likewise, we saw that people in her Intimate space did not make her uncomfortable, thus, suggesting that our approach is promising.

Future work entails exploring the continuum of control and how that relates to the different categories of Virtual Proxemics in the same way that Hall established ranges of distance. As well, if these become established, it will be possible to investigate how technology can use these rules in the same way as Greenberg et al. demonstrated how Hall's proxemics can be used to mitigate human-technology and technologytechnology interactions. Though, as Hall noted, proxemics depends upon social and culturally constructed norms, thus, exploring how virtual proxemics are impacted by social and cultural norms seems appropriate as well.

Fig. 1 .

 1 Fig. 1. Four proxemic circles as defined by Hall [10]. In red: Intimate space; in yellow: Personal Space; in green: Social Space; and, in blue: Public Space. First and second numbers of each space represent the interval for the close state and second and third number, the far state.

Fig. 5 .

 5 Fig. 5. Wearable hardware (1) push button; (2) camera; (3) Raspberry Pi B and Wi-Fi; (4) GPS; (5) LEDs for feedback; (6) battery pouch with two 1500mAh batteries (GPS and Wi-Fi) and a USB charger (Raspberry Pi).

Acknowledgments

We thank BRAVA, BOEING, CAPES, NSERC, DFAIT and PWAIS for their support. We thank Colnago, Gasques and Oliveira for the first steps on this project.