Achieving effective collaboration and trust has been shown to be harder for virtual vs. in-person teams. Related work has confirmed that introductions are a key mechanism to form trust in newly-formed teams. The rise of remote work necessitated by the COVID-19 pandemic highlighted the need for accelerating the development of effective collaboration in virtual teams. In response to this need, based on the research around introductions and trust in team settings, we have developed a novel approach for virtual introductions. This is what we term as asynchronous, semi-guided, professional introductions. Participants pre-record an introduction that uses a set of professionally-focused questions and watch these introductions prior to the meeting. Our study examines the impact of these introductions on virtual teams in three conditions: video, text, and no introduction. In this study, we used the Team Diagnostic Survey post-task completion to assess team effectiveness and interpersonal processes of 28 dyads. Thematic coding was used to collect dyads’ experience and engagement. The introduction conditions demonstrated significantly improved collaboration, effectiveness, and engagement amongst participants. Notably, the video condition was particularly well-received by participants and resulted in higher levels of engagement and effectiveness compared to the text and no introduction conditions. Ultimately, the use of these introductions led to a marked increase in trust and collaboration amongst participants. We reflect on the effects of this finding in the mainstream and propose further research to support newly-formed virtual dyadic teams to increase team effectiveness. This study contributes to the existing literature by introducing a novel asynchronous, semi-guided approach to virtual dyadic team introductions, offering insights crucial for contemporary remote work dynamics.

Abstract Many service providers require permissions to access privacy-sensitive data that are not necessary for their core functionality. To support users’ privacy management, we propose a novel agent-based negotiation framework to negotiate privacy permissions between users and service providers using a new multi-issue alternating-offer protocol based on exchanges of partial and complete offers. Additionally, we introduce a novel approach to learning users’ preferences in negotiation and present two variants of this approach: one variant personalised to each individual user, and one personalised depending on the user’s privacy type. To evaluate them, we perform a user study with participants, using an experimental tool installed on the participants’ mobile devices. We compare the take-it-or-leave-it approach, in which users are required to accept all permissions requested by a service, to negotiation, which respects their preferences. Our results show that users share personal data 2.5 times more often when they are able to negotiate while maintaining the same level of decision regret. Moreover, negotiation can be less mentally demanding than the take-it-or-leave-it approach and it allows users to align their privacy choices with their preferences. Finally, our findings provide insight into users’ data sharing strategies to guide the future of automated and negotiable privacy management mechanisms.

The Internet of Vehicles aims to fundamentally improve transportation by connecting vehicles, drivers, passengers, and service providers together. Several new services such as parking space identification, platooning and intersection control—to name just a few—are expected to improve traffic congestion, reduce pollution, and improve the efficiency, safety and logistics of transportation. Proposed end-user services, however, make extensive use of private information with little consideration for the impact on users and third parties (those individuals whose information is indirectly involved). This article provides the first comprehensive overview of privacy and trust issues in the Internet of Vehicles at the service level. Various concerns over privacy are formalised into four basic categories: personal information privacy, multi-party privacy, trust, and consent to share information. To help analyse services and to facilitate future research, the main relevant end-user services are taxonomised according to voluntary and involuntary information they require and produce. Finally, this work identifies several open research problems and highlights general approaches to address them. These especially relate to measuring the trade-off between privacy and service functionality, automated consent negotiation, trust towards the IoV and its individual services, and identifying and resolving multi-party privacy conflicts.

Peripheral breathing guides – tools designed to influence breathing while completing another primary task – have been proposed to provide physiological benefits during information work. While research has shown that guides can influence breathing rates under ideal conditions, there is little evidence that they can lead to underlying markers of physiological benefit under interrupted work conditions. Further, even if guides are effective during work tasks, it is unclear how personal and workplace factors affect peoples' willingness to adopt them for everyday use. In this paper, we present the results of a comparative, mixed-methods study of five different peripheral breathing guides. Our findings show that peripheral breathing guides are viable and can provide physiological markers of benefit during interrupted work. Further, we show that guides are effective – even when use is intermittent due to workplace distractions. Finally, we contribute guidelines to support the design of breathing guides for everyday information work.

In this work we introduce peripheral awareness as a neurological state for real-time human-computer integration, where the human is assisted by a computer to interact with the world. Changes to the field of view in peripheral awareness have been linked with quality of human performance. This instinctive narrowing of vision that occurs as a threat is perceived has implications in activities that benefit from the user having a wide field of view, such as cycling to navigate the environment. We present "Ena", a novel EEG-eBike system that draws from the user's neural activity to determine when the user is in a state of peripheral awareness to regulate engine support. A study with 20 participants revealed various themes and tactics suggesting that peripheral awareness as a neurological state is viable to align human-machine integration with internal bodily processes. Ena suggests that our work facilitates a safe and enjoyable human-computer integration experience.

Inbodied interaction is an emerging area in HCI that aligns how the body performs internally with our designs to support and optimise human performance. Inbodied Interaction therefore relies on knowledge of our physiology/neurology/kinesiology etc, to blend with HCI methodology. Recent, Inbodied Interaction workshops and summer schools, have been designed to share models of these processes to accelerate access to these areas of specialisation for HCI researchers. As such this one-day-hands-on-studio presents an extension of this work - an Inbodied interaction framework - to (1) make inbodied sciences accessible and (2) usable for HCI practitioners when it comes to crafting experiences, whether for health, performance or play. Our framework also offers a design alternative to cyborging futures that seek to augment human performance, Inbodied Interaction seeks to help discover and optimise human potential. As such, in this studio, we will explore where inbodied interaction fits in the narrative of our future bodies.

Poor indoor air quality (IAQ) can affect health and cognitive performance prior to users becoming aware of the declining air quality. Yet office occupants rarely have access to IAQ information upon which to base their ventilation decisions. This paper details the design and deployment of a situated IAQ display as a probe to explore ventilation and building operation practices when IAQ information is made available. Based on deployments in 11 naturally ventilated offices, we present an analysis of how reflection and sense making around IAQ can inform interactions with buildings. We suggest displays that are locally situated, non-disruptive and visualise the effects of poor IAQ with human analogies may hold potential for engaging office occupants with IAQ. We highlight how ambient displays represent a stepping-stone towards more informed interactions which can improve air quality and cognitive performance, and how IAQ feedback may usefully contribute to alternative HCI research agendas such as Human-Building Interaction.

Mindfulness is a term seen with increasing frequency in HCI literature, and yet the term itself is used almost as variously as the number of papers in which it appears. This diversity makes comparing or evaluating HCI approaches around mindfulness or understanding the design space itself a challenging task. We conducted a structured ACM literature search based on the term mindfulness. Our selection process yielded 38 relevant papers, which we analyzed for their definition, motivation, practice, evaluation and technology use around mindfulness. We identify similarities, divergences and areas of interest for each aspect, resulting in a framework composed of four perspectives and seven lines of research. We highlight challenges and opportunities for future HCI research and design.

Smart thermostats offer impressive scope for adapting to users' thermal comfort preferences and saving energy in shared work environments. Yet human interactions with smart thermostats thus far amount to an assumption from designers that users are willing and able to provide unbiased data at regular intervals; which may be unrealistic. In this paper we highlight the variety of social factors which complicate users' relationships with smart thermostats in shared work environments. These include social dynamics, expectations, and contextually specific factors that influence motivations for interaction with the system. In response we outline our framework towards a Smarter Thermostat: one which better accounts for these messy social inevitabilities, is equipped for a decline in user feedback over time and one which augments rather than attempts to replaces human intelligence- thereby ensuring a smarter thermostat does not create dumber humans.

Behavior modification in health is difficult, as habitual behaviors are extremely well-learned, by definition. This research is focused on building a persuasive system for behavior modification around emotional eating. In this paper, we make strides towards building a just-in-time support system for emotional eating in three user studies. The first two studies involved participants using a custom mobile phone application for tracking emotions, food, and receiving interventions. We found lots of individual differences in emotional eating behaviors and that most participants wanted personalized interventions, rather than a pre-determined intervention. Finally, we also designed a novel, wearable sensor system for detecting emotions using a machine learning approach. This system consisted of physiological sensors which were placed into women's brassieres. We tested the sensing system and found positive results for emotion detection in this mobile, wearable system.

As more applications move from the desktop to touch devices like tablets, designers must wrestle with the costs of porting a design with as little revision of the UI as possible from one device to the other, or of optimizing the interaction per device. We consider the tradeoffs between two versions of a UI for working with data on a touch tablet. One interface is based on using the conventional desktop metaphor (WIMP) with a control panel, push buttons, and checkboxes -- where the mouse click is effectively replaced by a finger tap. The other interface (which we call FLUID) eliminates the control panel and focuses touch actions on the data visualization itself. We describe our design process and evaluation of each interface. We discuss the significantly better task performance and preference for the FLUID interface, in particular how touch design may challenge certain assumptions about the performance benefits of WIMP interfaces that do not hold on touch devices, such as the superiority of gestural vs. control panel based interaction.

The weight scale is perhaps the most ubiquitous health sensor of all and is important to many health and lifestyle decisions, but its fundamental interface--a single numerical estimate of a person's current weight--has remained largely unchanged for 100 years. An opportunity exists to impact public health by re-considering this pervasive interface. Toward that end, we investigated the correspondence between consumers' perceptions of weight data and the realities of weight fluctuation. Through an analysis of online product reviews, a journaling study on weight fluctuations, expert interviews, and a large-scale survey of scale users, we found that consumers' perception of weight scale behavior is often disconnected from scales' capabilities and from clinical relevance, and that accurate understanding of weight fluctuation is associated with greater trust in the scale itself. We propose significant changes to how weight data should be presented and discuss broader implications for the design of other ubiquitous health sensing devices.

Internet advertisers reach millions of customers through practices that real time tracking of users' online activities. The tracking is conducted by third party ad services engaged by the Web sites to facilitate marketing campaigns. Previous research has investigated tracking practices and tracking agencies associated with popular Web sites. Here we investigate the network properties of the third party referral structures that facilitate gathering of user information for the delivery of personalized ads. By considering third party domains associated with the top ten search results for a diverse set of queries, we arrived at the networks of third party domains in four search markets. We show a consistent network structure across markets, with a dominant connected component that, on average, includes 92.8% of network vertices and 99.8% of the connecting edges. There is 99.5% chance that a user will become tracked by all top 10 trackers within 30 clicks on search results. Finally, the third party networks exhibit properties of the small world networks. This implies a high-level global and local efficiency in spreading the user information and delivering targeted ads.

Queries over large scale (petabyte) data bases often mean waiting overnight for a result to come back. Scale costs time. Such time also means that potential avenues of exploration are ignored because the costs are perceived to be too high to run or even propose them. With sampleAction we have explored whether interaction techniques to present query results running over only incremental samples can be presented as sufficiently trustworthy for analysts both to make closer to real time decisions about their queries and to be more exploratory in their questions of the data. Our work with three teams of analysts suggests that we can indeed accelerate and open up the query process with such incremental visualizations.

Millions of recommendations, opinions and experiences are shared across popular microblogging platforms and services each day. Yet much of this content becomes quickly lost in the stream shortly after being posted. This paper looks at the feasibility of identifying useful content in microblog streams so that it might be archived to facilitate wider access and reference. Towards this goal, we present an experiment with a game-with-a-purpose called Twiage that we designed to determine how well the deluge of content in "raw" microblog streams could be turned into filtered and ranked collections using ratings from players. Experiments with Twiage validate the feasibility of applying human-computation to this problem, finding strong agreement about what constitutes the "most useful" content in our test dataset. Second, we compare the effectiveness of various methods of eliciting such ratings, finding that a "choose-best" interface and Elo rating ranking scheme yield the greatest agreement in the fewest rounds. External validation of resulting top-rated twitter content with a domain expert found that while the top Twiage-ranked "tweets" were among the best of the set, there was a tendency for players to also select what we term "weak spam" - e.g., promotional content disguised as articles or reviews, indicating a need for more stringent content filtering.

While previous research studied the high level attributes people consider when they assess the healthiness of food they are familiar with, little work has looked at how people assess arbitrary, potentially unfamiliar, food to decide whether it is a healthy choice. Since there is a growing body of work in Ubicomp around health practices, including systems to support healthy eating, it is important to understand how people apply the knowledge they have to food decisions. In our studies we identified 8 attributes participants use for determining if they think a food is "healthy" or not. Based upon our analysis, we reflect on current system designs and propose four future design opportunities: capturing context of healthy eating, preparation and reflection on healthy eating understanding, sharing understanding and in situ information support.

Mainstream PIM tools capture only a portion of the information that people need to manage. Many information scraps seem to exist that don't make their way into these tools, instead being relegated to sticky notes, text files, and other makeshift storage, or simply being lost. In an effort to understand the role of these information scraps, the underlying needs they reflect, and the way PIM tools must be modified to support those needs, we created List-it, a micronote tool for quick and simple capture of information scraps.

The transition of personal information management (PIM) tools off the desktop to the Web presents an opportunity to augment these tools with capabilities provided by the wealth of real-time information readily available. In this paper, we describe a next-generation personal information assistance engine that lets end-users delegate to it various simple context- and activity-reactive tasks and reminders. Our system, Atomate, treats RSS/ATOM feeds from social networking and life-tracking sites as sensor streams, integrating information from such feeds into a simple unified RDF world model representing people, places and things and their timevarying states and activities. Combined with other information sources on the web, including the user's online calendar, web-based e-mail client, news feeds and messaging services, Atomate can be made to automatically carry out a variety of simple tasks for the user, ranging from context-aware filtering and messaging, to sharing and social coordination actions. Atomate's open architecture and world model easily accommodate new information sources and actions via the addition of feeds and web services. To make routine use of the system easy for non-programmers, Atomate provides a constrained-input natural language interface (CNLI) for behavior specification, and a direct-manipulation interface for inspecting and updating its world model.

Serendipity has a long tradition in the history of science as having played a key role in many significant discoveries. Computer scientists, valuing the role of serendipity in discovery, have attempted to design systems that encourage serendipity. However, that research has focused primarily on only one aspect of serendipity: that of chance encounters. In reality, for serendipity to be valuable chance encounters must be synthesized into insight. In this paper we show, through a formal consideration of serendipity and analysis of how various systems have seized on attributes of interpreting serendipity, that there is a richer space for design to support serendipitous creativity, innovation and discovery than has been tapped to date. We discuss how ideas might be encoded to be shared or discovered by 'association-hunting' agents. We propose considering not only the inventor's role in perceiving serendipity, but also how that inventor's perception may be enhanced to increase the opportunity for serendipity. We explore the role of environment and how we can better enable serendipitous discoveries to find a home more readily and immediately.

This paper describes a longitudinal field experiment in personal note-taking that examines how people capture and use information in short textual notes. Study participants used our tool, a simple browser-based textual note-taking utility, to capture personal information over the course of ten days. We examined the information they kept in notes using the tool, how this information was expressed, and aspects of note creation, editing, deletion, and search. We found that notes were recorded extremely quickly and tersely, combined information of multiple types, and were rarely revised or deleted. The results of the study demonstrate the need for a tool such as ours to support the rapid capture and retrieval of short notes-to-self, and afford insights into how users' actual note-keeping tendencies could be used to better support their needs in future PIM tools.

Scientists, engineers, and educators commonly need to make graphs that quickly illustrate quantitative ideas yet are not based on specific data sets. We call these graphs quantitative concept diagrams (QCDs). Existing charting and illustration programs make it possible to produce such graphs, but they are so time-consuming that users tend to sketch the graphs by hand instead. To reduce the cost of creating QCDs, we developed Graph Sketcher, a quantitative graphing tool that deeply integrates the data plotting capabilities of charting programs with the direct manipulation techniques of illustration programs. We show that our integrated interface substantially reduces the time needed to create QCDs, and we further show that real Graph Sketcher users both enjoy and take advantage of the interface improvements to create QCDs in a wide range of fields.

Abstract When users have poorly defined or complex goals, search interfaces that offer only keyword‐searching facilities provide inadequate support to help them reach their information‐seeking objectives. The emergence of interfaces with more advanced capabilities, such as faceted browsing and result clustering, can go some way toward addressing such problems. The evaluation of these interfaces, however, is challenging because they generally offer diverse and versatile search environments that introduce overwhelming amounts of independent variables to user studies; choosing the interface object as the only independent variable in a study would reveal very little about why one design outperforms another. Nonetheless, if we could effectively compare these interfaces, then we would have a way to determine which was best for a given scenario and begin to learn why. In this article, we present a formative inspection framework for the evaluation of advanced search interfaces through the quantification of the strengths and weaknesses of the interfaces in supporting user tactics and varying user conditions. This framework combines established models of users and their needs and behaviors to achieve this. The framework is applied to evaluate three search interfaces and demonstrates the potential value of this approach to interactive information retrieval evaluation.

We present Inky, a command line for shortcut access to common web tasks.Inky aims to capture the efficiency benefits of typed commands while mitigating their usability problems.Inky commands have little or no new syntax to learn, and the system displays rich visual feedback while the user is typing, including missing parameters and contextual information automatically clipped from the target web site.Inky is an example of a new kind of hybrid between a command line and a GUI interface.We describe the design and implementation of two prototypes of this idea, and report the results of a field study.

Directional faceted browsers, such as the popular column browser iTunes, let a person pick an instance from any column-facet to start their search for music. The expected effect is that any columns to the right are filtered. In keeping with this directional filtering from left to right, however, the unexpected effect is that the columns to the left of the click provide no information about the possible associations to the selected item. In iTunes, this means that any selection in the Album column on the right returns no information about either the Artists (immediate left) or Genres (leftmost) associated with the chosen album.

In this article we investigateinformation scraps—personal information where content has been scribbled on Post-it notes, scrawled on the corners of sheets of paper, stuck in our pockets, sent in email messages to ourselves, and stashed in miscellaneous digital text files. Information scraps encode information ranging from ideas and sketches to notes, reminders, shipment tracking numbers, driving directions, and even poetry. Although information scraps are ubiquitous, we have much still to learn about these loose forms of information practice. Why do we keep information scraps outside of our traditional PIM applications? What role do information scraps play in our overall information practice? How might PIM applications be better designed to accommodate and support information scraps' creation, manipulation and retrieval? We pursued these questions by studying the information scrap practices of 27 knowledge workers at five organizations. Our observations shed light on information scraps' content, form, media, and location. From this data, we elaborate on the typical information scrap lifecycle, and identify common roles that information scraps play: temporary storage, archiving, work-in-progress, reminding, and management of unusual data. These roles suggest a set of unmet design needs in current PIM tools: lightweight entry, unconstrained content, flexible use and adaptability, visibility, and mobility.

This paper introduces bubbling menus, a new design for cascading drop-down menus. Bubbling menus combine the bubble cursor [10] with directional mouse-gesture techniques to facilitate the access of certain items in a menu, such as frequently selected items. Through an extensive iterative design process, we explore bubbling menus in the context of adaptive and customizable user interfaces. Unlike other adaptation and customization techniques such as split menus, bubbling menus do not disrupt the original structure of menus and enable the activation of menus far from a menu bar. Results from two evaluation studies presented in the paper show that bubbling menus provide an effective alternative to accelerate menu selections tasks.

Temporal events, while often discrete, also have interesting relationships within and across times: larger events are often collections of smaller more discrete events (battles within wars; artists' works within a form); events at one point also have correlations with events at other points (a play written in one period is related to its performance over a period of time). Most temporal visualisations, however, only represent discrete data points or single data types along a single timeline: this event started here and ended there; this work was published at this time; this tag was popular for this period. In order to represent richer, faceted attributes of temporal events, we present Continuum. Continuum enables hierarchical relationships in temporal data to be represented and explored; it enables relationships between events across periods to be expressed, and in particular it enables user-determined control over the level of detail of any facet of interest so that the person using the system can determine a focus point, no matter the level of zoom over the temporal space. We present the factors motivating our approach, our evaluation and implementation of this new visualisation which makes it easy for anyone to apply this interface to rich, large-scale datasets with temporal data.

Information cannot be found if it is not recorded. Existing rich graphical application approaches interfere with user input in many ways, forcing complex interactions to enter simple information, requiring complex cognition to decide where the data should be stored, and limiting the kind of information that can be entered to what can fit into specific applications' data models. Freeform text entry suffers from none of these limitations but produces data that is hard to retrieve or visualize. We describe the design and implementation of Jourknow, a system that aims to bridge these two modalities, supporting lightweight text entry and weightless context capture that produces enough structure to support rich interactive presentation and retrieval of the arbitrary information entered.

The issue of improved situation awareness is a key concern for military agencies, promising to deliver strategic advantages in a variety of conflict and non-conflict scenarios. Improved situation awareness can benefit operational effectiveness by facilitating the planning process, improving the quality and timeliness of decisions, and providing better feedback regarding the strategic consequences of military actions. In this paper, we aim to show how a combination of semantic technologies and user interface design initiatives can be used to improve situation awareness in a simulated humanitarian relief scenario. We describe the development of a technical demonstrator system, the AKTiveSA TDS, which integrates a variety of knowledge technologies and visualization components within the context of a unitary application framework. We also describe our approach to scenario development, knowledge acquisition, ontology engineering and system design. Some specific problems encountered during system development are discussed, e.g. the performance overheads associated with rules-based processing, and potential solution strategies for these problems are presented alongside a description of future development activities.

In this paper, we describe our investigation into user tolerance of recognition errors during hand gesture interactions with visual displays. The study is based on our proposed interaction model for investigating gesture based interactions, focusing on three elements: Interaction context, system performance and user goals. This Wizard of Oz experiment investigates how recognition system accuracy rates and task characteristics in both desktop and ubiquitous computing scenarios can influence user tolerance for gesture interactions. Results suggest that interaction context is a greater influence on user tolerance than system performance alone, where recognition error rates can potentially reach 40\\% before users will abandon gestures and use an alternate interaction mode in a ubiquitous computing scenario. Results also suggest that in a desktop scenario, traditional input methods are more appropriate than gestures.

In this paper we consider the types of community networks that are most often codified within the Semantic Web. We propose the recognition of a new structure which fulfils the definition of community used outside the Semantic Web. We argue that the properties inherent in a community allow additional processing to be done with the described relationships existing between entities within the community network. Taking an existing online community as a case study we describe the ontologies and applications that we developed to support this community in the Semantic Web environment and discuss what lessons can be learnt from this exercise and applied in more general settings.

The success of translating an analog or manual practice into a digital interactive system may depend on how well that translation captures not only the functional what and how aspects of the practice, but the why of the process as well. Addressing these attributes is particularly challenging when there is a gap in expertise between the design team and the domain to be modeled. In this paper, we describe Making Tea, a design method foregrounding the use of analogy to bridge the gap between design team knowledge and domain expertise. Making Tea complements more traditional user-centered design approaches such as ethnography and task analysis. In this paper, we situate our work with respect to other related design methods such as Cultural Probes and Artifact Walkthroughs. We describe the process by which we develop, validate and use analogy in order to maximize expert contact time in observation, interviews, design reviews and evaluation. We contextualize the method in a discussion of its use in a project we ran to replace a paper-based synthetic chemistry lab book with an interactive system for use in a pervasive lab environment.

The UK e-Science programme is relying on the evolution of the paper lab book into a pervasive data gathering lab system. To date take up of existing commercial or research lab book replacement systems has not been great. In this paper, we reconsider both the role of the lab book in the experimental cycle, as well as its affective and experiential properties as an artefact, in order to design an e-Science lab book that will be acceptable to the scientists who will use it. To this end we combined and extended existing design analysis models in order to assess the artefact functionally and experientially. We present the approach we developed, the prototype we designed based on our analysis, and the results of the formative study we performed of the artefact in real use. We show that our design elicitation method strongly contributed to the success of our prototype's take up.

We present radial scroll, an interface widget to support scrolling particularly on either small or large scale touch displays. Instead of dragging a elevator in a scroll bar, or using repetitive key presses to page up or down, users gesture anywhere on the document surface such that clockwise gestures advance the document; counter clockwise gestures reverse the document. We describe our prototype implementation and discuss the results of an initial user study.

We present a Semantic Web application that we callCS AKTive Space. The application exploits a wide range of semantically heterogeneousand distributed content relating to Computer Science research in theUK. This content is gathered on a continuous basis using a variety of methods including harvesting and scraping as well as adopting a range models for content acquisition. The content currently comprises aroundten million RDF triples and we have developed storage, retrieval andmaintenance methods to support its management. The content is mediated through an ontology constructed for the application domainand incorporates components from other published ontologies. CS AKTive Spacesupports the exploration of patterns and implications inherent in the content and exploits a variety of visualisations and multi dimensional representations. Knowledge services supported in the applicationinclude investigating communities of practice: who is working, researching or publishing with whom. This work illustrates a number ofsubstantial challenges for the Semantic Web. These include problems of referential integrity, tractable inference and interaction support. Wereview our approaches to these issues and discuss relevant related work.

Hunter Gatherer is an interface that lets Web users carry out three main tasks: (1) collect components from within Web pages; (2) represent those components in a collection; (3) edit those component collections. Our research shows that while the practice of making collections of content from within Web pages is common, it is not frequent, due in large part to poor interaction support in existing tools. We engaged with users in task analysis as well as iterative design reviews in order to understand the interaction issues that are part of within-Web-page collection making and to design an interaction that would support that process.We report here on that design development, as well as on the evaluations of the tool that evolved from that process, and the future work stemming from these results, in which our critical question is: what happens to users perceptions and expectations of web-based information (their web-based information management practices) when they can treat this information as harvestable, recontextualizable data, rather than as fixed pages?