In this paper, we report on findings from an ethnographic study of how people use their calendars for personal information management (PIM). Our participants were faculty, staff and students who were not required to use or contribute to any specific calendaring solution, but chose to do so anyway. The study was conducted in three parts: first, an initial survey provided broad insights into how calendars were used; second, this was followed up with personal interviews of a few participants which were transcribed and content-analyzed; and third, examples of calendar artifacts were collected to inform our analysis. Findings from our study include the use of multiple reminder alarms, the reliance on paper calendars even among regular users of electronic calendars, and wide use of calendars for reporting and life-archival purposes. We conclude the paper with a discussion of what these imply for designers of interactive calendar systems and future work in PIM research.
With the increased use of mobile devices, more and more calendaring tasks are performed off the desktop computer. @cite_8 report on issues faced by mobile workers, their need for access to people and information located remotely, and the planful opportunism they engage in when utilizing their for tasks.
@cite_8
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The rapid and accelerating move towards use of mobile technologies has increasingly provided people and organizations with the ability to work away from the office and on the move. The new ways of working afforded by these technologies are often characterized in terms of access to information and people anytime, anywhere. This article presents a study of mobile workers that highlights different facets of access to remote people and information, and different facets of anytime, anywhere. Four key factors in mobile work are identified: the role of planning, working in "dead time," accessing remote technological and informational resources, and monitoring the activities of remote colleagues. By reflecting on these issues, we can better understand the role of technology and artifacts in mobile work and identify the opportunities for the development of appropriate technological solutions to support mobile workers. Mobile devices are more and more integrated in workflows, especially when interacting with stationary resources like machines in order to improve productivity or usability, but risk unauthorized access or unwanted unattended operation. Systems for location based access control have been developed to restrict the user to be in specific locations in order to proceed in a workflow. However, these approaches do not consider the movement pattern of a user nor do they distinguish the severity of false-positives that might arise from imperfect location measurements which is crucial in certain workflows. In this paper, focusing on mobile users interacting with stationary machines, an approach for workflow policies is presented using three types of location constraints to enforce movement patterns. The evaluation of these constraints is based on a user’s location history which is generated in a tamper-proof environment on his mobile device and describes his geographical trajectory for a given timespan. In this work, we discover the daily location-driven routines that are contained in a massive real-life human dataset collected by mobile phones. Our goal is the discovery and analysis of human routines that characterize both individual and group behaviors in terms of location patterns. We develop an unsupervised methodology based on two differing probabilistic topic models and apply them to the daily life of 97 mobile phone users over a 16-month period to achieve these goals. Topic models are probabilistic generative models for documents that identify the latent structure that underlies a set of words. Routines dominating the entire group's activities, identified with a methodology based on the Latent Dirichlet Allocation topic model, include “going to work late”, “going home early”, “working nonstop” and “having no reception (phone off)” at different times over varying time-intervals. We also detect routines which are characteristic of users, with a methodology based on the Author-Topic model. With the routines discovered, and the two methods of characterizing days and users, we can then perform various tasks. We use the routines discovered to determine behavioral patterns of users and groups of users. For example, we can find individuals that display specific daily routines, such as “going to work early” or “turning off the mobile (or having no reception) in the evenings”. We are also able to characterize daily patterns by determining the topic structure of days in addition to determining whether certain routines occur dominantly on weekends or weekdays. Furthermore, the routines discovered can be used to rank users or find subgroups of users who display certain routines. We can also characterize users based on their entropy. We compare our method to one based on clustering using K-means. Finally, we analyze an individual's routines over time to determine regions with high variations, which may correspond to specific events. A growing class of smartphone applications are tasking applications that run continuously, process data from sensors to determine the user's context (such as location) and activity, and optionally trigger certain actions when the right conditions occur. Many such tasking applications also involve coordination between multiple users or devices. Example tasking applications include location-based reminders, changing the ring-mode of a phone automatically depending on location, notifying when friends are nearby, disabling WiFi in favor of cellular data when moving at more than a certain speed outdoors, automatically tracking and storing movement tracks when driving, and inferring the number of steps walked each day. Today, these applications are non-trivial to develop, although they are often trivial for end users to state. Additionally, simple implementations can consume excessive amounts of energy. This paper proposes Code in the Air (CITA), a system which simplifies the rapid development of tasking applications. It enables non-expert end users to easily express simple tasks on their phone, and more sophisticated developers to write code for complex tasks by writing purely server-side scripts. CITA provides a task execution framework to automatically distribute and coordinate tasks, energy-efficient modules to infer user activities and compose them, and a push communication service for mobile devices that overcomes some shortcomings in existing push services. A mobile device like a smart phone is becoming one of main information processing devices for users these days. Using it, a user not only receives and makes calls, but also performs information tasks. However, a mobile device is still resource constrained, and some applications, especially work related ones, usually demand more resources than a mobile device can afford. To alleviate this, a mobile device should get resources from an external source. One of such sources is cloud computing platforms. Nevertheless an access to these platforms is not always guaranteed to be available and or is too expensive to access them. We envision a way to overcome this issue by creating a virtual cloud computing platform using mobile phones. We argue that due to the pervasiveness of mobile phones and the enhancement in their capabilities this idea is feasible. We show prior evaluation results to support our concept and discuss future developments. Mobile devices are increasingly being relied on for services that go beyond simple connectivity and require more complex processing. Fortunately, a mobile device encounters, possibly intermittently, many entities capable of lending it computational resources. At one extreme is the traditional cloud-computing context where a mobile device is connected to remote cloud resources maintained by a service provider with which it has an established relationship. In this paper we consider the other extreme, where a mobile device's contacts are only with other mobile devices, where both the computation initiator and the remote computational resources are mobile, and where intermittent connectivity among these entities is the norm. We present the design and implementation of a system, Serendipity, that enables a mobile computation initiator to use remote computational resources available in other mobile systems in its environment to speedup computing and conserve energy. We propose a simple but powerful job structure that is suitable for such a system. Serendipity relies on the collaboration among mobile devices for task allocation and task progress monitoring functions. We develop algorithms that are designed to disseminate tasks among mobile devices by accounting for the specific properties of the available connectivity. We also undertake an extensive evaluation of our system, including experience with a prototype, that demonstrates Serendipity's performance. It is well documented that interacting with a mobile phone is associated with poorer performance on concurrently performed tasks because limited attentional resources must be shared between tasks. However, mobile phones generate auditory or tactile notifications to alert users of incoming calls and messages. Although these notifications are generally short in duration, they can prompt task-irrelevant thoughts, or mind wandering, which has been shown to damage task performance. We found that cellular phone notifications alone significantly disrupted performance on an attention-demanding task, even when participants did not directly interact with a mobile device during the task. The magnitude of observed distraction effects was comparable in magnitude to those seen when users actively used a mobile phone, either for voice calls or text messaging. (PsycINFO Database Record Keywords: Driver distraction; Language: en We report on a diary study of the activities of information workers aimed at characterizing how people interleave multiple tasks amidst interruptions. The week-long study revealed the type and complexity of activities performed, the nature of the interruptions experienced, and the difficulty of shifting among numerous tasks. We present key findings from the diary study and discuss implications of the findings. Finally, we describe promising directions in the design of software tools for task management, motivated by the findings. Mobile devices are increasingly the primary way people access information on the Web. More and more users are carrying small computing devices with them wherever they go and can access the Internet regardless of their location. Whereas prior to the wide adoption of mobile devices, a user’s online life and offline life were partitioned by time and location, now there is less of a division. Users can carry their online friends with them and maintain a constant contact in the form of status updates and uploaded pictures and video, in a running social commentary that blurs the distinction between online and offline interactions. This has lead to a proliferation of data that connects a user’s online social network with their offline activities. As a result, the data they create provides a solid link between users, what they are doing offline, and what they are contributing online. The question is how to harness this content. We consider variations of a problem in which data must be delivered to mobile clients en route, as they travel toward their destinations. The data can only be delivered to the mobile clients as they pass within range of wireless base stations. Example scenarios include the delivery of building maps to firefighters responding to multiple alarms. We cast this scenario as a parallel-machine scheduling problem with the little-studied property that jobs may have different release times and deadlines when assigned to different machines. We present new algorithms and also adapt existing algorithms, for both online and offline settings. We evaluate these algorithms on a variety of problem instance types, using both synthetic and real-world data, including several geographical scenarios, and show that our algorithms produce schedules achieving near-optimal throughput. This article is an interview study of calendar use and a cognitive analysis of the interactions between the design of calendars and the task of prospective remembering. The study and analysis are coordinated to present a general critique of current electronic calendar designs and to note opportunities for future designs. The interview data reveal continued use of paper calendars in a highly computerized setting. A key conclusion is that paper calendars support prospective remembering by promoting browsing of existing appointments during subsequent calendar keeping but that this advantage is compromised in current electronic designs. Other aspects of the interviews and the analyses address the representational limitations of both paper and electronic calendars. This research explores a methodology in which design implications of qualitative empirical data are understood and systematized through theoretical analyses of existing artifacts. Desktop notifications are designed to provide awareness of information while a user is attending to a primary task. Unfortunately the awareness can come with the price of disruption to the focal task. We review results of a field study on the use and perceived value of email notifications in the workplace. We recorded users' interactions with software applications for two weeks and studied how notifications or their forced absence influenced users' quest for awareness of new email arrival, as well as the impact of notifications on their overall task focus. Results showed that users view notifications as a mechanism to provide passive awareness rather than a trigger to switch tasks. Turing off notifications cause some users to self interrupt more to explicitly monitor email arrival, while others appear to be able to better focus on their tasks. Users acknowledge notifications as disruptive, yet opt for them because of their perceived value in providing awareness. Scheduling group meetings requires access to participants' calendars, typically located in scattered pockets or desks. Placing participants' calendars on-line and using a rule-based scheduler to find a time slot would alleviate the problem to some extent, but it often is difficult to trust the results, because correct scheduling rules are elusive, varying with the participants and the agenda of a particular meeting. What's needed is a comprehensive scheduling system that summarizes the available information for quick, flexible, and reliable scheduling. We have developed a prototype of a priority-based, graphical scheduling system called Visual Scheduler (VS). A controlled experiment comparing automatic scheduling with VS to manual scheduling demonstrated the former to be faster and less error prone. A field study conducted over six weeks at the UNC-CH Computer Science Department showed VS to be a generally useful system and provided valuable feedback on ways to enhance the functionality of the system to increase its value as a groupwork tool. In particular, users found priority-based time-slots and access to scheduling decision reasoning advantageous. VS has been in use by more than 75 faculty, staff, and graduate students since Fall 1987. Indoor autonomous mobile service robots can overcome their hardware and potential algorithmic limitations by asking humans for help. In this work, we focus on mobile robots that need human assistance at specific spatially-situated locations (e.g., to push buttons in an elevator or to make coffee in the kitchen). We address the problem of what the robot should do when there are no humans present at such help locations. As the robots are mobile, we argue that they should plan to proactively seek help and travel to offices or occupied locations to bring people to the help locations. Such planning involves many trade-offs, including the wait time at the help location before seeking help, and the time and potential interruption to find and displace someone in an office. In order to choose appropriate parameters to represent such decisions, we first conduct a survey to understand potential helpers' travel preferences in terms of distance, interruptibility, and frequency of providing help. We then use these results to contribute a decision-theoretic algorithm to evaluate the possible choices in offices and plan where to proactively seek help. We demonstrate that our algorithm aims to minimize the number of office interruptions as well as task completion time. The increasing mass of information confronting a business or an individual have created a demand for information management applications. Time-based information, in particular, is an important part of many information access tasks. This paper explores how to use 3D graphics and interactive animation to design and implement visualizers that improve access to large masses of time-based information. Two new visualizers have been developed for the Information Visualizer: 1) the Spiral Calendar was designed for rapid access to an individual's daily schedule, and 2) the Time Lattice was designed for analyzing the time relationships among the schedules of groups of people. The Spiral Calendar embodies a new 3D graphics technique for integrating detail and context by placing objects in a 3D spiral. It demonstrates that advanced graphics techniques can enhance routine office information tasks. The Time Lattice is formed by aligning a collection of 2D calendars. 2D translucent shadows provide views and interactive access to the resulting complex 3D object. The paper focuses on how these visualizations were developed. The Spiral Calendar, in particular, has gone through an entire cycle of development, including design, implementation, evaluation, revision and reuse. Our experience should prove useful to others developing user interfaces based on advanced graphics. Desktop operating systems such as Windows and Linux base scheduling decisions on CPU consumption; processes that consume fewer CPU cycles are prioritized, assuming that interactive processes gain from this since they spend most of their time waiting for user input. However, this doesn't work for modern multimedia applications which require significant CPU resources. We therefore suggest a new metric to identify interactive processes by explicitly measuring interactions with the user, and we use it to design and implement a process scheduler. Measurements using a variety of applications indicate that this scheduler is very effective in distinguishing between competing interactive and noninteractive processes. Online labor marketplaces offer the potential to automate tasks too difficult for computers, but don't always provide accurate results. MobileWorks is a crowd platform that departs from the marketplace model to provide robust, high-accuracy results using three new techniques. A dynamic work-routing system identifies expertise in the crowd and ensures that posted work completes within a bounded time with fair wages. A peer-management system helps prevent wrong answers. Last, social interaction techniques let best workers manage and teach other crowd members. This process allows the crowd to collaboratively learn how to solve new tasks. One subclass of human computation applications are those directed at tasks that involve planning (e.g. tour planning) and scheduling (e.g. conference scheduling). Interestingly, work on these systems shows that even primitive forms of automated oversight on the human contributors helps in significantly improving the effectiveness of the humans crowd. In this paper, we argue that the automated oversight used in these systems can be viewed as a primitive automated planner, and that there are several opportunities for more sophisticated automated planning in effectively steering the crowd. Straightforward adaptation of current planning technology is however hampered by the mismatch between the capabilities of human workers and automated planners. We identify and partially address two important challenges that need to be overcome before such adaptation of planning technology can occur: (i) interpreting inputs of the human workers (and the requester) and (ii) steering or critiquing plans produced by the human workers, armed only with incomplete domain and preference models. To these ends, we describe the implementation of AI-MIX, a tour plan generation system that uses automated checks and alerts to improve the quality of plans created by human workers; and present a preliminary evaluation of the effectiveness of steering provided by automated planning. Mobile radio communications raise two major problems. First: a very poor radio link quality. Second: the users' mobility, which requires the management of their position, is resource consuming (especially radio bandwidth). This paper focuses on the second issue and proposes an intelligent method for users locating: the alternative strategy (AS). Our proposal is based on the observation that the mobility behavior of a majority of people can be foretold. If taken into consideration by the system, this characteristic can save signaling messages due to mobility management procedures, leading thus to savings in the system resources. Several versions of the AS are described: a basic version for long term events (i.e., received calls and registrations), and versions with increased memory for short and medium term events. The evaluation of the basic versions was performed using analytic and simulation approaches. It shows that storing the mobility related information brings great savings in system resources when the users have medium or high predictable mobility patterns. More generally speaking, this work points out the fact that the future systems will have to integrate users related information in order: firstly: to provide customized services and secondly: to save system resources. On the other hand, current trends in mobile communications show that adaptive and dynamic system capabilities require that more information to be collected and computed. > This paper examines the hypothesis that information flow, from device to user, is a vital part of skilled activity in human-computer interaction. Two studies are reported. The first study questions users of keyboard-driven word processors about the effects of cursor-movement, finding and word-deletion commands in various contexts. The second study questions users of the Apple Macintosh-based systems, MacWrite and Microsoft Word, about the behaviour of the menu-driven find command. In both studies it is discovered that users often do not know the precise effects of frequently-used actions, such as the final position of the cursor, even though these effects are vital for future planning. It is concluded that even experienced users must acquire the information they need from the device's display during interactions, and that they do not necessarily remember regular details that are available in this way. This conclusion conflicts with those current models of user psychology that assume routine skill relies on complete mental specifications of methods for performing tasks.