Augmented reality shows great promise for supporting human-robot collaboration. However, investigating this “in the wild” with participants from industry is mostly uncharted territory. Addressing this, we report on a field study evaluation of ARTHUR, an open-source authoring tool for augmented reality-assisted human-robot collaboration. To facilitate this domain-specific study, we extended ARTHUR with additional design components, improved the authoring experience, and support for collaborative authoring. The study took place at a local company, with 16 participants from three stakeholder groups: robot engineers, UX designers, and operators. The task was to assemble and disassemble a subset of an injection mould together with a collaborative robot, while supported by an AR-interface created in ARTHUR. The study revealed a strong desire of operators to be assisted in their daily tasks by robot(s) that serve as an extra (strong) set of hands, and augmented reality to guide the process and communicate robot intent. Engineers confirmed the feasibility of integrating ARTHUR in future semi-automated workflows and UX designers appreciated the authoring capabilities and proposed further features.

We introduce RoboVisAR, an immersive augmented reality (AR) authoring tool for in-situ robot visualisations. AR robot visualisations, such as the robot's movement path, status, and safety zones, have been shown to benefit human-robot collaboration. However, their creation requires extensive skills in both robotics and AR programming. To address this, RoboVisAR allows users to create custom AR robot visualisations without programming. By recording an example robot behaviour, users can design, combine, and test visualisations in-situ within a mixed reality environment. RoboVisAR currently supports six types of visualisations (Path, Point of Interest, Safety Zone, Robot State, Message, Force/Torque) and four types of conditions for when they are displayed (Robot State, Proximity, Box, Force/Torque). With this tool, users can easily present different visualisations on demand and make them context-aware to avoid visual clutter. An expert user study with three participants suggests that users appreciate the customizability of the visualisations, which could easily be authored in less than ten minutes.

Virtual Reality (VR) technology facilitates effective, flexible, and safe industrial training for novice technicians when on-site training is not feasible. However, previous research has shown that training in VR may be less successful than traditional learning approaches in real-world settings, and haptic interaction may be the key to improving virtual training. In this study, we integrated pseudo-haptic feedback from motion delay with vibrotactile stimulation to enhance the sense of presence, enjoyment, and the perception of physical properties in VR, which may be crucial for achieving faithful simulations. The impact of combined haptic support was assessed in a complex industrial training procedure completing a variety of tasks such as component assembly and cleaning. The results indicate that vibrotactile cues are beneficial for presence and enjoyment, whereas pseudo-haptic illusions effectively enable kinesthetic sensations. Furthermore, multimodal haptic feedback that mixed the two yielded the most advantageous outcomes. Our findings highlight the potential of the pseudo-haptic and vibrotactile fusion in industrial training scenarios, presenting practical implications of the state-of-the-art haptic technologies for virtual learning.

Research on remote assistance in real-world industries is sparse, as most research is conducted in the laboratory under controlled conditions. Consequently, little is known about how users tailor remote assistance technologies at work. Therefore, we developed an augmented reality-based remote assistance prototype called Remote Assist Kit (RAK). RAK is a component-based system, allowing us to study tailoring activities and the usefulness of tailorable remote assistance technologies. We conducted a user evaluation with employees from the plastic manufacturing industry. The employees configured the RAK to solve real-world problems in three collaborative scenarios: (1) troubleshooting a running injection molding machine, (2) tool maintenance, (3) solving a trigonometry problem. Our results show that the tailorability of RAK was perceived as useful, and users were able to successfully tailor RAK to the distinct properties of the scenarios. Specific findings and their implications for the design of tailorable remote assistance technologies are presented. Among other findings, requirements specific to remote assistance in the manufacturing industry were discussed, such as the importance of sharing machine sounds between the local operator and the remote helper. • Users tailor remote assistance to problem scenarios and find it useful. • Movable scene cameras dominated the “injection”-scenario for close-up views. • Awareness of a partner’s tailoring work is crucial for remote assistance. • Sharing machine sounds aids remote troubleshooting of running machines. • Multi-camera setups may enhance awareness at manufacturing machines.

While technologies for human-robot collaboration are rapidly advancing, plenty of aspects still need further investigation, such as ensuring workspace awareness, enabling the operator to reschedule tasks on the fly, and how users prefer to coordinate and collaborate with robots. To address these, we propose an Augmented Reality interface that supports human-robot collaboration in an assembly task by (1) enabling the inspection of planned and ongoing robot processes through dynamic task lists and a path visualization, (2) allowing the operator to also delegate tasks to the robot, and (3) presenting step-by-step assembly instructions. We evaluate our AR interface in comparison to a state-of-the-art tablet interface in a user study, where participants collaborated with a robot arm in a shared workspace to complete an assembly task. Our findings confirm the feasibility and potential of AR-assisted human-robot collaboration, while pointing to some central challenges that require further work.

Determining the correct orientation of objects can be critical to succeed in tasks like assembly and quality assurance. In particular, near-symmetrical objects may require careful inspection of small visual features to disambiguate their orientation. We propose CADTrack, a digital assistant for providing instructions and support for tasks where the object orientation matters but may be hard to disambiguate with the naked eye. Additionally, we present a deep learning pipeline for tracking the orientation of near-symmetrical objects. In contrast to existing approaches, which require labeled datasets involving laborious data acquisition and annotation processes, CADTrack uses a digital model of the object to generate synthetic data and train a convolutional neural network. Furthermore, we extend the architecture of Mask R-CNN with a confidence prediction branch to avoid errors caused by misleading orientation guidance. We evaluate CADTrack in a user study, comparing our tracking-based instructions to other methods to confirm the benefits of our approach in terms of preference and required effort.

Adaptive user interfaces can improve experiences in Extended Reality (XR) applications by adapting interface elements according to the user’s context. Although extensive work explores different adaptation policies, XR creators often struggle with their implementation, which involves laborious manual scripting. The few available tools are underdeveloped for realistic XR settings where it is often necessary to consider conflicting aspects that affect an adaptation. We fill this gap by presenting AUIT, a toolkit that facilitates the design of optimization-based adaptation policies. AUIT allows creators to flexibly combine policies that address common objectives in XR applications, such as element reachability, visibility, and consistency. Instead of using rules or scripts, specifying adaptation policies via adaptation objectives simplifies the design process and enables creative exploration of adaptations. After creators decide which adaptation objectives to use, a multi-objective solver finds appropriate adaptations in real-time. A study showed that AUIT allowed creators of XR applications to quickly and easily create high-quality adaptations.

Workspace awareness is critical for remote assistance with physical tasks, yet it remains difficult to facilitate. For example, if the remote helper is limited to the single viewpoint provided by the worker’s hand-held or head-mounted camera, she lacks the ability to gain an overview of the workspace. This may be addressed by granting the helper view-independence, e.g., through a multi-camera system. However, it can be cumbersome to set up and calibrate multiple cameras, and it can be challenging for the local worker to identify the current viewpoint of the remote helper. We present CueCam, a multi-camera remote assistance system that supports mutual workspace awareness through a flexible ad-hoc camera calibration and various Augmented Reality cues that communicate the helper’s viewpoint and focus. In particular, we propose visual cues presented through a head-mounted Augmented Reality display (Virtual Hand, Color Cue), and sound cues emitted from the cameras’ physical locations (Spatial Sound). Findings from a lab study indicate that all proposed cues effectively support the worker’s awareness of helper’s location and focus, while the Color Cue demonstrated superiority in task performance and preference ratings during a search task.

Arm discomfort is a common issue in Cross Reality applications involving prolonged mid-air interaction. Solving this problem is difficult because of the lack of tools and guidelines for 3D user interface design. Therefore, we propose a method to make existing ergonomic metrics available to creators during design by estimating the interaction cost at each reachable position in the user’s environment. We present XRgonomics, a toolkit to visualize the interaction cost and make it available at runtime, allowing creators to identify UI positions that optimize users’ comfort. Two scenarios show how the toolkit can support 3D UI design and dynamic adaptation of UIs based on spatial constraints. We present results from a walkthrough demonstration, which highlight the potential of XRgonomics to make ergonomics metrics accessible during the design and development of 3D UIs. Finally, we discuss how the toolkit may address design goals beyond ergonomics.

We present a digital assistance approach for applied metrology on near-symmetrical objects. In manufacturing, systematically measuring products for quality assurance is often a manual task, where the primary challenge for the workers lies in accurately identifying positions to measure and correctly documenting these measurements. This paper focuses on a use-case, which involves metrology of small near-symmetrical objects, such as LEGO bricks. We aim to support this task through situated visual measurement guides. Aligning these guides poses a major challenge, since fine grained details, such as embossed logos, serve as the only feature by which to retrieve an object's unique orientation. We present a two-step approach, which consists of (1) locating and orienting the object based on its shape, and then (2) disambiguating the object's rotational symmetry based on small visual features. We apply and compare different deep learning approaches and discuss our guidance system in the context of our use case.

Abstract Analyzing complex data is a non‐linear process that alternates between identifying discrete facts and developing overall assessments and conclusions. In addition, data analysis rarely occurs in solitude; multiple collaborators can be engaged in the same analysis, or intermediate results can be reported to stakeholders. However, current data‐driven communication tools are detached from the analysis process and promote linear stories that forego the hierarchical and branching nature of data analysis, which leads to either too much or too little detail in the final report. We propose a conceptual design for integrated data‐driven reporting that allows for iterative structuring of insights into hierarchies linked to analytic provenance and chosen analysis views. The hierarchies become dynamic and interactive reports where collaborators can review and modify the analysis at a desired level of detail. Our web‐based InsideInsights system provides interaction techniques to annotate states of analytic components, structure annotations, and link them to appropriate presentation views. We demonstrate the generality and usefulness of our system with two use cases and a qualitative expert review.

This paper proposes and evaluates an approach for building models of installed industrial Cyber-Physical Systems using augmented reality on smartphones. It proposes a visual language for annotating devices, containers, flows of liquids and networking connections in augmented reality. Compared to related work, it provides a more lightweight and flexible approach for building 3D models of industrial systems. The models are further used to automatically infer software configuration of controllable industrial products. This addresses a common problem of error-prone and time-consuming configuration of industrial systems in the current practice. The proposed approach is evaluated in a study with 16 domain experts. The study participants are involved in creating a model of an industrial system for water treatment. Their comments show that the approach can enable a less error-prone configuration for more complex systems. Opportunities for improvement in usability and reflections on the potential of the approach are discussed.

Blood sampling is a common and necessary procedure in the treatment and diagnosis of a variety of diseases. However, it often results in painful and stressful experiences for children. Designed together with domain experts, ChillFish is a breath-controlled biofeedback game technology with bespoke airflow sensor that aims to calm children during blood sampling procedures. An experimental pilot study was conducted in which 20 children aged 6-11 were assigned to one of two conditions involving either passive distraction (watching a video) or active distraction using the ChillFish prototype. Medical staff rated ChillFish significantly more useful in facilitating the blood sampling procedure compared to passive distraction. Qualitative feedback from patients, parents, and medical staff identified aspects that impact the acceptance of breath-based active distraction. Our study highlights the potential of non-pharmacological assistive technology tools to reduce fear and pain for children undergoing painful or stressful medical treatment.

Due to substantial research in indoor positioning a vast amount of location technologies and algorithms are available to enable various applications. However, it is challenging knowing which positioning system is optimal, or sufficient, for a specific application---not only when considering development and maintenance costs, but also the potential impact of the positioning system's performance on the respective application's performance.

In sports, if players' physical and technical abilities are mismatched, the competition is often uninteresting for them. With the emergence of exertion games, this could be changing. Player balancing, known from video games, allows players with different skill levels to compete, however, it is unclear how balancing mechanisms should be applied in exertion games, where physical and digital elements are fused. In this paper, we present an exertion game and three approaches for balancing it; a physical, an explicit-digital and an implicit-digital balancing approach. A user study that compares these three approaches is used to investigate the qualities and challenges within each approach and explore how the player experience is affected by them. Based on these findings, we suggest four design strategies for balancing exertion games, so that players will stay engaged in the game and contain the feeling of a fair competition, even if they have mismatched skills.

Little research on assistive technologies for families of children with attention deficit hyperactivity disorder (ADHD) has investigated the long-term impact, after the assistive technology is returned to the researchers. In this paper, we report the outcomes of a follow-up study, conducted four-weeks after a field study of 13 children with ADHD and their families who used an assistive technology designed to help establish and change family practices. We show that some of the positive effects on parent frustration level and conflict level around morning and bedtime routines that we observed in the first phase of the study, continued even after the study period, when the technology was no longer available. We furthermore present insights into family practices in families of children with ADHD and how these could lead to unexpected challenges and implications related to the adoption, use, and outcome of the assistive technology.

Families of children with Attention Deficit Hyperactivity Disorder (ADHD) often report morning and bedtime routines to be stressful and frustrating. Through a design process involving domain professionals and families we designed MOBERO, a smartphone-based system that assists families in establishing healthy morning and bedtime routines with the aim to assist the child in becoming independent and lowering the parents' frustration levels. In a two-week intervention with 13 children with ADHD and their families, MOBERO significantly improved children's independence and reduced parents' frustration levels. Additionally, use of MOBERO was associated with a 16.5% reduction in core ADHD symptoms and an 8.3% improvement in the child's sleep habits, both measured by standardized questionnaires. Our study highlights the potential of assistive technologies to change the everyday practices of families of children with ADHD.

The cooperative, invisible non-clinical work of hospital orderlies is often overlooked. It consists foremost of transferring patients between hospital departments. As the overall efficiency of the hospital is highly dependent on the coordination of the work of orderlies, this study investigates the coordination changes in orderlies' work practices in connection to the implementation of a workflow application at the hospital. By applying a mixed methods approach (both qualitative and quantitative studies), this paper calls for attention to the changes in orderlies' coordination activities while moving from a manual and centralized form to a semi-automatic and decentralized approach after the introduction of the workflow application. We highlight a set of cross-boundary (spatial and organizational) information-sharing breakdowns and the challenges of orderlies in maintaining local and global coordination. We also present design recommendations for future design of coordination tools to support orderlies' work practices.

Indoor Positioning based on WiFi has received extensive focus from research communities, owing its promises of ubiquitous positioning indoors for a variety of applications. The majority of the existing research on WiFi positioning centers around the improvement of positioning accuracy. However, to this end there is missing a unanimous evaluation methodology appropriately reflecting criteria relevant in real-world use. Assessing and advancing the state-of-the-art is often hindered by incomparable evaluation settings, and in many cases a missing rigor in describing evaluation methodology, metrics, and data collection, which is often decoupled from realistic use scenarios and their diversity. This leads to major challenges—and often disappointments—when implementing positioning methods in the hope of the promised accuracies. We believe that this holds especially in large real world environments, as only few extensive experimental evaluations have been reported in such environments. This paper presents a comparative evaluation of several indoor positioning techniques set at a large university hospital spanning 160, 000m2—an environment where several location- and context-aware logistic applications are in daily use. The positioning methods utilize measurements of signal strengths using existing WiFi infrastructure, which eases deployment and maintenance. We identify meaningful key metrics which describe different aspects of the methods' performance. Using these metrics, we furthermore report on experiences with implementing and utilizing indoor positioning solutions in a highly diverse environment, in which building types and materials, as well as building use differ across the complex. Correspondingly, the evaluation data we use is gathered at different building complex parts, days, and daytimes, and both at static locations as well as traveling within the building complex. Our results illustrate and quantify the challenges and breakdowns in transferring performance results from a small controlled setting, such as a small office environment, to a large dynamic building complex.

Using game elements and mechanics in sports training holds great potential for increasing player enjoyment, but also introduces a risk of reducing training relevance. This paper describes a novel training installation for individual handball training, called "The Bouncer", and the design process behind three training games. In order to investigate how game elements can affect the training experience, we conducted a study with 10 experienced amateur handball players, eliciting responses regarding the training relevance of the games. Based on the study and our design insights, we propose three challenges that designers of interactive sports-training games need to consider: 1) Maintaining relevance when translating physical elements into digital representations. 2) Choosing an appropriate level of sensing as game input. 3) Introducing points in training exercises without reducing sport relevance. For the three challenges, we propose strategies to help future designers of training games.

This paper presents the design and development process of an interactive football-training game that aims to improve players' ball-handling skills, and their ability to simultaneously survey the playing field. A small-scale experiment was conducted to test the game, and the results are presented and reflected upon. Based on the experiences gained from the design and development process, as well as examples from the existing field and skill acquisition theory, we present three areas of interest to consider for interactive sport-training game designers: Context Characteristics, Movement Patterns and Perceptual Reaction. From a discussion of these areas, we derive eight design sensitivities that emphasize issues, challenges and opportunities, important for the design, development and analysis of interactive sport-training games in general.

Accurate information about how people commonly travel in a given large-scale building environment and which routes they take for given start and destination points is essential for applications such as indoor navigation, route prediction, and mobile work planning and logistics. In this paper, we propose methods for detecting commonly used routes by robust aggregation, clustering, and merging of indoor position traces. The developed methods overcome three specific challenges for detecting commonly used routes in an indoor setting based on position data: i) a high ratio between path-density and positioning-accuracy, ii) a flat path hierarchy, and iii) providing cost-effective scalability. Through an evaluation based on data collected by staff members at a hospital covering more than 10 hectare over three floors, we show that the proposed methods detect routes that are representative of the commonly used routes between locations. These methods are sufficiently efficient to provide common routes based on real-time data from thousands of devices simultaneously. Furthermore, we show that the methods operate robustly even on basis of noisy and coarse-grained position estimates as provided by large-scale deployable indoor Wi-Fi positioning systems, and with no prior information on building layout.

Existing methods for transportation mode detection (TMD) using mobile sensing make it generally possible to distinguish between walking, cycling, and motorized transport. However, our means of transport evolve and we develop radically new ways of transporting ourselves, thus new TMD sub-classification methods are needed to distinguish these new transport forms. As we transition from fossil-fueled cars to electric vehicles, switch to bikes with electric motors, ride in hybrid buses, or do city sightseeing on Segways, new challenges arise in distinguishing these from a mobile sensing perspective. Distinguishing electric vehicles (EVs) from fossil-fueled vehicles (FFVs) is a challenge, where traditional methods based on features such as GPS speed, or statistics on raw accelerometer data, are insufficient. In this paper, we present methods for distinguishing EVs from FFVs using smartphones with built-in inertial sensors, by reliably identifying idle-engine motor vibrations through features built on frequency analysis. We provide an extensive analysis of the challenges involved in making the EV/FFV distinction, as well as practical tools based on the methods. This includes analyzing the measurable similarities and differences between EVs and FFVs, and developing methods of reliably separating them. The presented tools implement the methods as classifiers built using machine learning. The analysis of our experiments shows that we can achieve an accuracy of 89-95% distinguishing EVs from FFVs, even with on-body phones.

The ability to accurately estimate indoor travel times is crucial for enabling improvements within application areas such as indoor navigation, logistics for mobile workers, and facility management. In this paper, we study the challenges inherent in indoor travel time estimation, and we propose th

The vast availability of mobile phones with built-in movement and location sensors enable the collection of detailed information about human movement even indoors. As mobility is a key element of many processes and activities, an interesting class of information to extract is movement patterns that quantify how humans move, interact and group. In this paper we propose methods for detecting two common pedestrian movement patterns, namely individual following relations and group leadership. The proposed methods for identifying following patterns employ machine learning on features derived using similarity analysis on time lagged sequences of WiFi measurements containing either raw signal strength values or derived locations. To detect leadership we combine the individual following relations into directed graphs and detect leadership within groups by graph link analysis. Methods for detecting these movement patterns open up new possibilities in — amongst others — computational social science, reality mining, marketing research and location-based gaming. We provide evaluation results that show error rates down to 7%, improving over state of the art methods with up to eleven percentage points for following patterns and up to twenty percentage points for leadership patterns. Our method is, contrary to state of the art, also applicable in challenging indoor environments, e.g., multi-story buildings. This implies that even quite small samples allow us to detect information such as how events and campaigns in multistory shopping malls may trigger following in small groups, or which group members typically take the lead when triggered by e.g. commercials, or how rescue or police forces act during training exercises.

The interactive training equipment, TacTower, is aimed at supporting multiple elite athletes, such as handball players in training their micro-tactical skills in close-contact situations. It focuses on psychomotor abilities and trains the skills involved in reading the opponents’ actions and anticipating the outcome while reacting accordingly. The Tac- Tower prototype will be demonstrated live, and here we summarize the main design issues, to give the reader a sense of how the elite sports context stands out from other interaction design domains. There is much potential for interaction design for the elite athletic community, as this domain holds interesting challenges while also inspiring relevant, new forms of interaction design for other domains.

This paper describes the notion of Mobile Urban Drama and how a particular production is implemented to support engaging experiences via location-based mobile phone software. Mobile Urban Drama is a general concept that has been adapted for out-of-school learning projects by introducing support for solving assignments and producing multimedia-based documentation for learning purposes. Media production is seamlessly supported through a context-aware media management system. The Mobile Urban Drama project, "HasleInteractive", is presented. It supports biology, geography and math lessons for 7th to 9th graders in schools. The story is an environmental thriller that takes place partly on the pupils' mobile phones and partly in the real world - in nature, which must be investigated through exercises. The level of pupil engagement is evaluated through interviews with teachers and pupils, as well as an analysis of pupil productivity and produced media materials during the interactive Mobile Urban Drama experience. It is argued how the out-of-school learning features are successfully supported by the system, and we conclude that the level of productivity and engagement is higher than in usual pupil group work.

This paper discusses the application of three spatial multimedia techniques for communication of art in the physical museum space. In contrast to the widespread use of computers in cultural heritage and natural science museums, it is generally a challenge to introduce technology in art museums without disturbing the art works. This has usually been limited to individual audio guides. In our case we strive to achieve holistic and social experiences with seamless transitions between art experience and communication related to the artworks.

This paper describes the eBag infrastructure, which is a generic infrastructure inspired from work with school children who could benefit from a electronic schoolbag for collaborative handling of their digital material. The eBag infrastructure is utilizing the Context-aware HyCon framework and collaborative web services based on WebDAV. A ubiquitous login and logout mechanism has been built based on BlueTooth sensor networks. The eBag infrastructure has been tried out in field tests with school kids. In this paper we discuss experiences and design issues for ubiquitous Web integration in interactive school environments with multiple interactive whiteboards and workstations. This includes proposals for specialized and adaptive XLink structures for organizing school materials as well as issues in login/logout based on proximity of different display surfaces.

WebDAV needs awareness support in order to be a full-fledged collaboration system, This paper introduces AwareDAV, a new WebDAV extension framework enabling shared awareness through event notification. By extending the WebDAV protocol with seven new request-methods and an extensible XML based event subscription scheme, AwareDAV supports fine grained event subscriptions over a range of transport mechanisms and enables a wide range of collaboration scenarios. This paper describes the design of AwareDAV, its API, experiences with its initial implementation, as well as a comparison with Microsoft Exchange and WebDAV-notify.

This demo shows BattleBoard 3D which is an Augmented Reality (AR) based game prototype featuring the use of LEGO for the physical and digital pieces. Design concepts, the physical setting and, user interface for the game is illustrated and described. Based on qualitative studies of children playing the game we illustrate design issues for AR board games.

The Fluid Documents project has developed various research prototypes that show that powerful annotation techniques based on animated typographical changes can help readers utilize annotations more effectively. Our recently-developed Fluid Open Hypermedia prototype supports the authoring and browsing of fluid annotations on third-party Web pages. This prototype is an extension of the Arakne Environment, an open hypermedia application that can augment Web pages with externally stored hypermedia structures. This paper describes how various Web standards, including DOM, CSS, XLink, XPointer, and RDF, can be used and extended to support fluid annotations.

This paper presents a guided tour system for the WWW. It is a module for the Webvise open hypermedia system that implements the ideas of trails and guided tours, originating from the hypertext field. Webvise appears as an open hypermedia helper application to the user and stores the guided tours in an XML format called OHIF separated from the WWW documents included in the tour. The main advantages of the system are: (1) a browser independent format in terms of HTML and PNG-based image maps for reading the guided tours; (2) support for a familiar metaphor, namely, a metro route map; (3) overview maps and route maps with indication of which stations of a tour have been visited; and finally (4) support for arbitrary web pages as stations on the tour. The paper discusses the Webvise Guided Tour System and illustrates its use in a digital library portal. The system is compared to other recent Web-based guided tour systems, and it is argued that Webvise Guided Tour System solves a number of prior system problems.

This paper discusses how to augment the WWW with an open hypermedia service (Webvise) that provides structures such as contexts, links, annotations, and guided tours stored in hypermedia databases external to the Web pages. This includes the ability for users collaboratively to create links from parts of HTML Web pages they do not own and support for creating links to parts of Web pages without writing HTML target tags. The method for locating parts of Web pages can locate parts of pages across frame hierarchies and it is also supports certain repairs of links that breaks due to modified Web pages. Support for providing links to/from parts of non-HTML data, such as sound and movie will be possible via interfaces to plug-ins and Java based media players. The hypermedia structures are stored in a hypermedia database, developed from the Devise Hypermedia framework, and the service is available on the Web via an ordinary URL. The best user interface for creating and manipulating the structures is currently provided for the Microsoft Internet Explorer 4.x browser through COM integration that utilize the Explorers DOM representation of Web-pages. But the structures can also be manipulated and used via special Java applets and a pure proxy server solution is provided for users who only need to browse the structures. A user can create and use the external structures as "transparency" layers on top of arbitrary Web pages, the user can switch between viewing pages with one or more layers (contexts) of structures or without any external structures imposed on them.

This paper discusses an approach for developing dynamically tailorable hypermedia systems in an object-oriented environment. The approach is aimed at making applications developed in compiled languages like Beta and C++ tailorable at run-time. The approach is based on use of: 1) a hypermedia application framework (DEVISE Hyper-media), and 2) an embeddable interpreter for the framework language. A specific hypermedia system is instantiated from the framework with the interpreter embedded in the executable. The specific hypermedia system has a number of “open points” which can be filled via the interpreter at run-time. These open points and the interpreter provide sufficient support to allow tailoring at run-time as well as compile-time. Among the types of tailoring supported are: 1) adding new media-types, 2) alternating editors for supported media-types, and 3) removing a supported media-type. The paper describes the framework and illustrates how the interpreter is integrated. It describes steps involved in tailoring a specific hypermedia system with a new drawing media-type, where graphical objects can be endpoints for links. Since the hypermedia framework uses a persistent object-store, a solution for handling persistent interpreted objects is presented. Finally, the approach is compared with other environments supporting tailoring.

This paper investigates CSCW aspects of large-scale technical projects based on a case study of a specific Danish engineering company and uncovers challenges to CSCW applications in this setting.The company is responsible for management and supervision of one of the worlds largest tunnelhidge construction projects.Our primary aim is to determine requirements on CSCW as they unfold in this concrete setting as opposed to survey and laboratory investigations.The requirements provide feedback to product development both on specific functionality and as a long term vision for CSCW in such settings.The initial qualitative analysis identitled a number of bottlenecks in daily work, where support for cooperation is needed.Examples of bottlenecks are: sharing materials, issuing tasks, and keeping track of task status.Grounded in the analysis, cooperative design workshops based on scenarios of future work situations were established to investigate the potential of different CSCW technologies in this setting.In the workshops, mock-ups and prototypes were used to support end-users in assessing CSCW technologies based on concrete, hands-on experiences.The workshops uncovered several challenges.First, support for sharing materials would require a huge body of diverse materials to be integrated, for example into a hypermedia network.Second, daily work tasks are event driven and plans change too rapidly for people to register them on a computer.Finally, tasks are closely coupled to materials being processed thus a coordination tool should integrate facilities for managing materials.