Bombalytics: Visualization of Competition and Collaboration Strategies of Players in a Bomb Laying Game

Competition and collaboration form complex interaction patterns between the agents and objects involved. Only by understanding these interaction patterns, we can reveal the strategies the participating parties applied. In this paper, we study such competition and collaboration behavior for a computer game. Serving as a testbed for artificial intelligence, the multiplayer bomb laying game Pommerman provides a rich source of advanced behavior of computer agents. We propose a visualization approach that shows an overview of multiple games, with a detailed timeline-based visualization for exploring the specifics of each game. Since an analyst can only fully understand the data when considering the direct and indirect interactions between agents, we suggest various visual encodings of these interactions. Based on feedback from expert users and an application example, we demonstrate that the approach helps identify central competition strategies and provides insights on collaboration.     

On the utility of experiential cross-training for team decision making under time stress

This study investigated the effectiveness of experiential cross-training in a team context for team decision-making under time stress in a simulated naval surveillance task. It was hypothesized that teams whose members explicitly experience all team positions will perform better under time pressure due to a better shared Team Interaction Model (Cannon-Bowers et al. 1993). In addition, it was posited that experiential cross-training would reduce the negative effect of member reconfiguration that can occur in certain military situations. Three groups of teams participated in this study (cross-trained, reconfigured and control). The experiment involved three team training sessions, followed by three time-stressed exercise sessions. During training, one group of teams was cross-trained (CT) by asking each member to perform an entire session at each of the three team positions. Member reconfiguration (where each member was shifted to another's position) was unexpectedly introduced at the first of the exercise sessions for the CT group and for another group (reconfigured) that had not been cross-trained. A third (control) group was neither cross-trained nor reconfigured. During training, the performance of non-CT teams improved more quickly than that of CT teams. During the exercise, the CT group did not achieve the level of performance of the control teams. The immediate effect of team member reconfiguration was to degrade performance significantly for the non-CT teams, but not for the CT teams. The findings are discussed in terms of the multiple mental models' view of team performance (Cannon-Bowers et al. 1993) and the authors discuss the relative utility of crosstraining when overall training time is fixed.     

On the utility of experiential cross-training for team decision-making under time stress

This study investigated the effectiveness of experiential cross-training in a team context for team decision-making under time stress in a simulated naval surveillance task. It was hypothesized that teams whose members explicitly experience all team positions will perform better under time pressure due to a better shared Team Interaction Model (Cannon-Bowers et al. 1993). In addition, it was posited that experiential cross-training would reduce the negative effect of member reconfiguration that can occur in certain military situations. Three groups of teams participated in this study (cross-trained, reconfigured and control). The experiment involved three team training sessions, followed by three time-stressed exercise sessions. During training, one group of teams was cross-trained (CT) by asking each member to perform an entire session at each of the three team positions. Member reconfiguration (where each member was shifted to another's position) was unexpectedly introduced at the first of the exercise sessions for the CT group and for another group (reconfigured) that had not been cross-trained. A third (control) group was neither cross-trained nor reconfigured. During training, the performance of non-CT teams improved more quickly than that of CT teams. During the exercise, the CT group did not achieve the level of performance of the control teams. The immediate effect of team member reconfiguration was to degrade performance significantly for the non-CT teams, but not for CT teams. The findings are discussed in terms of the multiple mental models' view of team performance (Cannon-Bowers et al. 1993) and the authors discuss the relative utility of cross-training when overall training time is fixed.     

Multiple decoupled interaction: An interaction design approach for groupware interaction in co-located virtual environments

Interactive visualizations such as virtual environments and their associated input and interface techniques have traditionally focused on localized single-user interactions and have lacked co-present active collaboration mechanisms where two or more co-located users can share and actively cooperate and interact with the visual simulation. VR facilities such as CAVEs or PowerWalls, among many others, seem to promise such collaboration but due to the special requirements in terms of 3D input and output devices and the physical configuration and layout, they are generally designed to support an active controlling participant—the immersed user—and a passive viewing only audience. In this paper we explore the integration of different technologies, such as small handheld devices and wireless networks with VR/VEs in order to develop a technical and conceptual interaction approach that allows creation of a more ad hoc, interaction rich, multimodal and multi-device environment, where multiple users can access certain interactive capabilities of VE and support co-located collaboration.     

Collaborative Exploration and Sensemaking of Big Environmental Sound Data

Many ecologists are using acoustic monitoring to study animals and the health of ecosystems. Technological advances mean acoustic recording of nature can now be done at a relatively low cost, with minimal disturbance, and over long periods of time. Vast amounts of data are gathered yielding environmental soundscapes which requires new forms of visualization and interpretation of the data. Recently a novel visualization technique has been designed that represents soundscapes using dense visual summaries of acoustic patterns. However, little is known about how this visualization tool can be employed to make sense of soundscapes. Understanding how the technique can be best used and developed requires collaboration between interface, algorithm designers and ecologists. We empirically investigated the practices and needs of ecologists using acoustic monitoring technologies. In particular, we investigated the use of the soundscape visualization tool by teams of ecologists researching endangered species detection, species behaviour, and monitoring of ecological areas using long duration audio recordings. Our findings highlight the opportunities and challenges that ecologists face in making sense of large acoustic datasets through patterns of acoustic events. We reveal the characteristic processes for collaboratively generating situated accounts of natural places from soundscapes using visualization. We also discuss the biases inherent in the approach. Big data from nature has different characteristics from social and informational data sources that comprise much of the World Wide Web. We conclude with design implications for visual interfaces to facilitate collaborative exploration and discovery through soundscapes.     

Lark: Coordinating Co-located Collaboration with Information Visualization

Large multi-touch displays are expanding the possibilities of multiple-coordinated views by allowing multiple people to interact with data in concert or independently. We present Lark, a system that facilitates the coordination of interactions with information visualizations on shared digital workspaces. We focus on supporting this coordination according to four main criteria: scoped interaction, temporal flexibility, spatial flexibility, and changing collaboration styles. These are achieved by integrating a representation of the information visualization pipeline into the shared workspace, thus explicitly indicating coordination points on data, representation, presentation, and view levels. This integrated meta-visualization supports both the awareness of how views are linked and the freedom to work in concert or independently. Lark incorporates these four main criteria into a coherent visualization collaboration interaction environment by providing direct visual and algorithmic support for the coordination of data analysis actions over shared large displays.     

融合全局和近邻协同信息的会话推荐算法

现有基于会话的推荐算法主要通过挖掘单个目标会话的项目转换关系进行推荐,对来自其他不同会话中项目之间的复杂转换信息考虑较少。为此,提出一种融合全局和近邻协同信息的会话推荐算法SFGN-GNN,同时考虑来自全局与近邻会话的协同信息,以充分挖掘用户偏好。通过学习会话表示来表达用户偏好,先按目标会话与近邻会话的成对项目转移关系构建近邻图,依据所有会话中的成对项目转移关系构建全局图,再利用图神经网络获取目标会话节点近邻级和全局级的项目表示,采用融合门融合得到会话级项目表示,并在其中嵌入项目在目标会话中的位置信息和时间信息,然后通过软注意力机制得到最终的会话表示,最后经过softmax函数预测下一个可能交互的项目。在两个数据集上的实验验证了SFGN-GNN算法有效性。     

ChronoCorrelator: Enriching Events with Time Series

Event sequences and time series are widely recorded in many application domains; examples are stock market prices, electronic health records, server operation and performance logs. Common goals for recording are monitoring, root cause analysis and predictive analytics. Current analysis methods generally focus on the exploration of either event sequences or time series. However, deeper insights are gained by combining both. We present a visual analytics approach where users can explore both time series and event data simultaneously, combining visualization, automated methods and human interaction. We enable users to iteratively refine the visualization. Correlations between event sequences and time series can be found by means of an interactive algorithm, which also computes the presence of monotonic effects. We illustrate the effectiveness of our method by applying it to real world and synthetic data sets.     

群组协作社交网络关系的分析及可视化

社交网络的研究应用领域广泛,大多数的研究主要关注于社交网络结构中节点和链接的变化,研究角度较为单一.而群组协作关系在社交网络中较为普遍,为更好地探索群组协作过程中群组级别网络结构的演变,首先将组级任务添加到用于图可视化的任务分类中,针对协作关系网络的特性,设置一个适用于群组协作关系分析的任务分类法,根据此任务分类法设置...     

Social interactions of information systems development teams: a performance perspective

We report results from a longitudinal study of information systems development (ISD) teams. We use data drawn from 60 ISD teams at 22 sites of 15 Fortune 500 organizations to explore variations in performance relative to these teams' social interactions. To do this, we characterize ISD as a form of new product development and focus on team-level social interactions with external stakeholders. Drawing on cluster analysis, we identify five patterns of team-level social interactions and the relationships of these patterns to a suite of objective and subjective measures of ISD performance. Analysis leads us to report three findings. First, data indicate that no one of the five identified patterns maximizes all performance measures. Second, data make clear that the most common approach to ISD is the least effective relative to our suite of performance measures. Third, data from this study show that early indications of ISD project success do not predict actual outcomes. These findings suggest two issues for research and practice. First, these findings indicate that varying patterns of social interactions lead to differences in ISD team performance. Second, the findings illustrate that singular measures of ISD performance are an oversimplification and that multiple measures of ISD performance are unlikely to agree.     

Interaction mining and skill-dependent recommendations for multi-objective team composition

Web-based collaboration and virtual environments supported by various Web 2.0 concepts enable the application of numerous monitoring, mining and analysis tools to study human interactions and team formation processes. The composition of an effective team requires a balance between adequate skill fulfillment and sufficient team connectivity. The underlying interaction structure reflects social behavior and relations of individuals and determines to a large degree how well people can be expected to collaborate. In this paper we address an extended team formation problem that does not only require direct interactions to determine team connectivity but additionally uses implicit recommendations of collaboration partners to support even sparsely connected networks. We provide two heuristics based on Genetic Algorithms and Simulated Annealing for discovering efficient team configurations that yield the best trade-off between skill coverage and team connectivity. Our self-adjusting mechanism aims to discover the best combination of direct interactions and recommendations when deriving connectivity. We evaluate our approach based on multiple configurations of a simulated collaboration network that features close resemblance to real world expert networks. We demonstrate that our algorithm successfully identifies efficient team configurations even when removing up to 40% of experts from various social network configurations.     

Social Presence as a Multi‐Dimensional Group Construct in 3D Virtual Environments

One of the key challenges of distributed teams is the lack of social presence resulting from multiple work locations. Virtual environments (VEs) have been viewed as a collaboration tool for distributed teams that can enhance social presence via shared collaboration space and avatars. We observed, recorded, and analyzed the VE meetings of a globally distributed team. Data were analyzed through quantitative and qualitative content analysis. Our findings show that in the meetings, social presence was a situational phenomenon that constantly varied in strength. Social presence occurred as either a subgroup or group phenomenon, which at times coexisted at both levels. In particular, 2 of the 3 subdimensions of social presence, psychological involvement and behavioral engagement, were observable in team interaction.     

Training for Vigilance: Repeated Sessions with Knowledge of Results

Abstract

Two groups of subjects were run in a visual monitoring test, one with knowledge of results (KR) providing instant feedback of correct responses, commissive errors, and missed signals, and the other with no knowledge of results (NKR). The groups were run for five 48-minute sessions on consecutive days, with a follow-up transfer session five weeks later. Results showed significant differences in detection rates between the groups on all five training sessions, but not on the transfer session. Detection rates increased significantly during the five training sessions for both groups, and at approximately the same rate. Commissive errors were significantly different only in the first two training sessions, with the KR subjects showing more false alarms. Commissive errors did not increase or decrease over time within sessions, or over the five training sessions.     

A multi-level approach of evaluating crew resource management training: a laboratory-based study examining communication skills as a function of team congruence

The article proposes a multi-level approach for evaluating communication skills training (CST) as an important element of crew resource management (CRM) training. Within this methodological framework, the present work examined the effectiveness of CST in matching or mismatching team compositions with regard to hierarchical status and competence. There is little experimental research that evaluated the effectiveness of CRM training at multiple levels (i.e. reaction, learning, behaviour) and in teams composed of members of different status and competence. An experiment with a two (CST: with vs. without) by two (competence/hierarchical status: congruent vs. incongruent) design was carried out. A total of 64 participants were trained for 2.5 h on a simulated process control environment, with the experimental group being given 45 min of training on receptiveness and influencing skills. Prior to the 1-h experimental session, participants were assigned to two-person teams. The results showed overall support for the use of such a multi-level approach of training evaluation. Stronger positive effects of CST were found for subjective measures than for objective performance measures. STATEMENT OF RELEVANCE: This work provides some guidance for the use of a multi-level evaluation of CRM training. It also emphasises the need to collect objective performance data for training evaluation in addition to subjective measures with a view to gain a more accurate picture of the benefits of such training approaches.     

Team formation in social networks based on collective intelligence – an evolutionary approach

The tremendous growth of the social web has inspired research communities to discover social intelligence, which encompasses a wide spectrum of knowledge characterized by human interaction, communication and collaboration, thereby exploiting collective intelligence (CI) to support the successful existence of social communities on the Web. In this work, we address the team formation problem for generalized tasks where a set of experts is to be discovered from an expertise social network that can collaborate effectively to accomplish a given task. The concept of CI that emerges from these collaborations attempts to maximize the potential of the team of experts, rather than only aggregating individual potentials. Because the team formation problem is NP-hard, a genetic algorithm-based approach is applied to optimize computational collective intelligence in web-based social networks. To capture the essence of CI, a novel quantitative measure Collective Intelligence Index (CII) is proposed that takes two factors into account –the “enhanced expertise score” and the “trust-based collaboration score”. This measure relates to the social interactions among experts, reflecting various affiliations that form a network of experts that help to drive creativity by deepening engagements through collaboration and the exchange of ideas and expertise, thereby enriching and enhancing the knowledge base of experts. The presented model also captures the teams’ dynamics by considering trust, which is essential to effective interactions between the experts. The computational experiments are performed on a synthetic dataset that bears close resemblance to real-world expertise networks, and the results clearly establish the effectiveness of our proposed model.     

Interactive, internet delivery of visualization via structured prerendered multiresolution imagery

We present a novel approach for latency-tolerant delivery of visualization and rendering results where client-side frame rate display performance is independent of source dataset size, image size, visualization technique or rendering complexity. Our approach delivers pre-rendered, multiresolution images to a remote user as they navigate through different viewpoints, visualization or rendering parameters. We employ demand-driven tiled, multiresolution image streaming and prefetching to efficiently utilize available bandwidth while providing the maximum resolution user can perceive from a given viewpoint. Since image data is the only input to our system, our approach is generally applicable to all visualization and graphics rendering applications capable of generating image files in an ordered fashion. In our implementation, a normal web server provides on-demand images to a remote custom client application, which uses client-pull to obtain and cache only those images required to fulfill the interaction needs. The main contributions of this work are: (1) an architecture for latency-tolerant, remote delivery of precomputed imagery suitable for use with any visualization or rendering application capable of producing images in an ordered fashion; (2) a performance study showing the impact of diverse network environments and different tunable system parameters on end-to-end system performance in terms of deliverable frames per second.     

面向协同应用的通用协作语言研究

研究和探讨一种能够灵活定制不同协同应用方案的编程语言。对CSCW协同应用中的协作机制和交互特征进行分析，抽象出协同应用中最具共性的基本协作元素，对这些基本元素进行定义和描述。提出将协作问题从计算应用问题中分离出来的方案。对于一个给定的应用，可以构造多种协作方案。使最终用户可选择最符合自己需要的协作方案和交互规则来进行他们之间协同工作，并且还可在协同工作会话过程中改变协作交互规则。     

A multi-level approach of evaluating crew resource management training: a laboratory-based study examining communication skills as a function of team congruence

The article proposes a multi-level approach for evaluating communication skills training (CST) as an important element of crew resource management (CRM) training. Within this methodological framework, the present work examined the effectiveness of CST in matching or mismatching team compositions with regard to hierarchical status and competence. There is little experimental research that evaluated the effectiveness of CRM training at multiple levels (i.e. reaction, learning, behaviour) and in teams composed of members of different status and competence. An experiment with a two (CST: with vs. without) by two (competence/hierarchical status: congruent vs. incongruent) design was carried out. A total of 64 participants were trained for 2.5 h on a simulated process control environment, with the experimental group being given 45 min of training on receptiveness and influencing skills. Prior to the 1-h experimental session, participants were assigned to two-person teams. The results showed overall support for the use of such a multi-level approach of training evaluation. Stronger positive effects of CST were found for subjective measures than for objective performance measures.

Statement of Relevance: This work provides some guidance for the use of a multi-level evaluation of CRM training. It also emphasises the need to collect objective performance data for training evaluation in addition to subjective measures with a view to gain a more accurate picture of the benefits of such training approaches.     

Improving the Effectiveness of Virtual Teams by Adapting Team Processes

Results are presented from a study on virtual teams and whether appropriate early training can positively influence their effectiveness. Sixteen teams that worked together for periods ranging from three months to three years were studied. Team processes that emerged naturally from long-duration teams were formalized and taught to shorter duration teams. These shorter duration teams comprised three different cohorts, each of which received different levels of training. It was found that the adoption of formal procedures and structured processes significantly increased the effectiveness of virtual teams. Tasks that lend themselves to a structured approach were most effectively accomplished during virtual meetings, whereas face-to-face interactions were better for relatively unstructured, discussion intensive tasks. The performance of a virtual team was significantly improved when team processes were adapted to the affordances of the CMC environment. It is shown that this adaptation can occur very rapidly if teams are trained on the technology as well as on work processes that best exploit it.     

Continuous awareness: A visual mobile approach

Facing the challenges of global distribution in software development, Continuous Coordination constitutes a new coordination paradigm that helps break the communication barriers in distributed teams by providing awareness information and integrating heterogeneous tools. Continuous Awareness is an extension of Continuous Coordination emphasizing continuous awareness support across space and time. Traditional desktop-based approaches are insufficient for the requirements of continuous awareness. Team Radar Mobile takes a visual mobile approach to awareness by extending the visualization of awareness information on desktop platforms to mobile platforms. The concept of continuous awareness and its implementation on multiple platforms are discussed. An experiment has evaluated the visual mobile approach to continuous awareness, and found visualization express awareness information more efficiently than the non-visual approach. Our work also provides experience on mobile visualization.