Major breaches of sensitive company data, as for Facebook's 50 million user accounts in 2018 or Equifax's 143 million user accounts in 2017, are showing the limitations of reactive data security technologies. Companies and government organizations are turning to proactive data security technologies that secure sensitive data at source. However, data security analysts still face two fundamental challenges in data protection decisions: 1) the information overload from the growing number of data repositories and protection techniques to consider; 2) the optimization of protection plans given the current goals and available resources in the organization. In this work, we propose an intelligent user interface for security analysts that recommends what data to protect, visualizes simulated protection impact, and helps build protection plans. In a domain with limited access to expert users and practices, we elicited user requirements from security analysts in industry and modeled data risks based on architectural and conceptual attributes. Our preliminary evaluation suggests that the design improves the understanding and trust of the recommended protections and helps convert risk information in protection plans.

Data analytics is increasingly performed by non-expert analysts (e.g., casual business users). In this context, future analytics tools need easy-to-use techniques to reveal relations between columns of data in a spreadsheet or table. For example, a market analyst, may want to find if industry categories and funding amounts are related: i.e., if some industries receive amounts within distinctive intervals. Traditional filtering and script-based querying poorly support non-expert users in such explorations because they require iterative parameter adjusting and query writing until a meaningful result is found. In this paper, we focus on supporting the analysis of relationships between categorical and numerical columns. We present a novel visualization, Interver, which dynamically reveals insights as the user selects an interval within the relationship. With a concrete scenario, specific analysis tasks, and an informal evaluation, we show how Interver can help non-expert analysts self-serve and answer realistic questions.

In this paper, we propose a mixed-initiative approach to integrate a Q&A site based on a crowd of volunteers with a standard operator-based help desk, ensuring quality of customer service. Q&A sites have emerged as an efficient way to address questions in various domains by leveraging crowd knowledge. However, they lack sufficient reliability to be the sole basis of customer service applications. We built a proof-of-concept mixed-initiative tool that helps a crowd-manager to decide if a question will get a satisfactory and timely answer by the crowd or if it should be redirected to a dedicated operator. A user experiment found that our tool reduced the participants' cognitive load and improved their performance, in terms of their precision and recall. In particular, those with higher performance benefited more than those with lower performance.

Enterprise wikis commonly see low adoption rates, preventing them from reaching the critical mass that is needed to make them valuable. The high interaction costs for contributing content to these wikis is a key factor impeding wiki adoption. Much of the collaboration among knowledge workers continues to occur in email, which causes useful information to stay siloed in personal inboxes. In this demo we present Mail2Wiki, a system that enables easy contribution and initial curation of content from the personal space of email to the shared repository of a wiki.

Corporate wikis are affected by poor adoption rates. The high interaction costs required to organize and maintain information in these wikis are a key factor that limits broader adoption. We present VisualWikiCurator, a wiki extension designed to lower such costs by (a) recommending new content to easily update a wiki page, and (b) extracting structured data from the wiki page while providing new alternative visualizations of the data. The visualizations of extracted semantic data act both as alternative views and as tools to organize the page content. Since no information extraction algorithm is perfect with generic unstructured data, we use a mixed-initiative approach to allow users to refine machine-extracted metadata and easily re-organize the content in wiki pages.

We present a design research project on knowledge sharing and activity awareness in distributed emergency management planning. In three experiments we studied groups using three different prototypes, respectively: a paper-prototype in a collocated work setting, a first software prototype in a distributed setting, and a second, enhanced software prototype in a distributed setting. In this series of studies we tried to better understand the processes of knowledge sharing and activity awareness in complex cooperative work by developing and investigating new tools that can support these processes. We explicate the design rationale behind each prototype and report the results of each experiment investigating it. We discuss how the results from each prototyping phase brought us closer to defining properties of a system that facilitate the sharing and awareness of both content and process knowledge. Our designs enhanced aspects of distributed group performance, in some respects beyond that of comparable face-to-face groups.

This paper presents a research project on the design of a cross-channel information management tool for knowledge workers: we focus on IT services professionals in a large enterprise who work in multiple ad hoc task forces. Through three rounds of investigation, we characterized their work practices and needs, specified their requirements for a cross-channel information management tool, and designed and evaluated a prototype to address these needs. We found that these workers shared the problem of managing information across multiple channels, requiring better support for aggregating, filtering, and organizing this information. We report the requirements elicited and the prototypes built during the design process.

Information overload is a growing threat to the productivity of today's knowledge workers, who need to keep track of multiple streams of information from various sources. RSS feed readers are a popular choice for syndicating information streams, but current tools tend to contribute to the overload problem instead of solving it. We introduce FeedWinnower, an enhanced feed aggregator that helps readers to filter feed items by four facets (topic, people, source, and time), thus facilitating feed triage. The combination of the four facets provides a powerful way for users to slice and dice their personal feeds. In addition, we present a formative evaluation of the prototype conducted with 15 knowledge workers in two different organizations.

Web 2.0 tools are penetrating into organizations after their successful adoption in the consumer domain (e.g., social networking; sharing of photos, videos, tags, or bookmarks; wiki-based editing). Some of these new tools and the collaborative processes that they support on the large scale are often referred to as Collective Intelligence (CI). The workshop brings together leading researchers and designers who are studying or developing CI tools aimed at workers in organizations. The goal is to further articulate the emerging research agenda for this new CSCW area and define new observed forms of CI in organization. Studies of communities, CI tools, and new methods are discussed.

We build on our prior work with computer-supported teams performing a complex decision-making task on maps, where the distinction between content and process common ground is proposed. In this paper we describe a distributed geo-collaboration software prototype. The system design rationale was gleaned from fieldwork, literature on team cognition, and an earlier lab study introducing a reference task with face-to-face teams. We report on a controlled experiment that evaluates this design rationale. Distinct sets of measures show that that the prototype supported both content and process common ground, offsetting the costs imposed by the distributed setting. We interpret the results in relation to prior work on common ground and draw implications for moving beyond current models of sharing and coordination.

Teams of specialized experts, such as emergency management planning teams, while making decisions need to efficiently pool domain-specific knowledge, synthesize relevant information, and keep track of collaborators activities at a low interaction cost. This requires tools that allow monitoring both low-level information (e.g., individual actions and external events) and higher-order activities (e.g., how members contribute to groupwork). This paper presents design of CIVIL, a system prototype developed to support map-based decision-making. We report our empirical evaluation of the effects of visualizations on the decision process and the final product.

We study the development of common ground in an emergency management planning task. Twelve three-person multi-role teams performed the task with a paper prototype in a controlled setting; each team completed three versions of the task. We use converging measures to document the development of common ground in the teams and present an in-depth analysis of the characteristics of the common ground development process. Our findings indicate that in complex collaborative work, process common ground increases, thus diminishing the need for acts like information querying or strategy discussions about how to organize the collaborative activities. However, content common ground is created and tested throughout the three runs; in fact dialogue acts used to clarify this content increase over time. Discussion of the implications of these findings for the theory of common ground and the design of collaborative systems follows.

We studied the process of sharing and managing knowledge (common ground process) in three-member teams performing emergency management planning tasks on shared maps. We built a reference task and a role-based multi-view prototype for studying this process. In this paper we empirically test the claim that common ground increases through joint experience on a task over time. We model the common ground process using a realistic task, a controlled setting, and multiple measures. We present findings from the analysis of questionnaires, communication transcripts, videos, and artifacts.

The workforce is ageing as older workers re-enter the workforce or delay retirement. One consequence is that work groups are increasingly becoming intergenerational. Because group work relies on many collaborative tools (e.g. email, shared calendars), it is essential to understand the special requirements that intergenerational groups have for groupware. Can we design collaborative tools that leverage the differing abilities and contributions of older and younger workers in groups? We focus on how best to support intergenerational groups, offering an analytical framework that combines ideas from the theory of small groups and activity theory. We consider design implications for computer-supported cooperative work (CSCW) and outline design principles for groupware that supports intergenerational groups. Finally, we discuss methodological issues that arise when studying intergenerational cooperative work.

Journal Article Awareness and teamwork in computer-supported collaborations Get access John M. Carroll, John M. Carroll * School of Information Sciences and Technology and Center for Human–Computer Interaction, The Pennsylvania State University, University Park, PA 16802, USA * Corresponding author. Tel.: +1 8148632476; fax: +1 8146353556. E-mail address:[email protected] (J.M. Carroll). Search for other works by this author on: Oxford Academic Google Scholar Mary Beth Rosson, Mary Beth Rosson School of Information Sciences and Technology and Center for Human–Computer Interaction, The Pennsylvania State University, University Park, PA 16802, USA Search for other works by this author on: Oxford Academic Google Scholar Gregorio Convertino, Gregorio Convertino School of Information Sciences and Technology and Center for Human–Computer Interaction, The Pennsylvania State University, University Park, PA 16802, USA Search for other works by this author on: Oxford Academic Google Scholar Craig H. Ganoe Craig H. Ganoe School of Information Sciences and Technology and Center for Human–Computer Interaction, The Pennsylvania State University, University Park, PA 16802, USA Search for other works by this author on: Oxford Academic Google Scholar Interacting with Computers, Volume 18, Issue 1, January 2006, Pages 21–46, https://doi.org/10.1016/j.intcom.2005.05.005 Published: 14 July 2005 Article history Received: 24 April 2005 Accepted: 17 May 2005 Published: 14 July 2005