Large High Resolution Displays for Co-Located Collaborative Intelligence Analysis

Large, high-resolution vertical displays carry the potential to increase the accuracy of collaborative sensemaking, given correctly designed visual analytics tools. From an exploratory user study using a fictional intelligence analysis task, we investigated how users interact with the display to construct spatial schemas and externalize information, as well as how they establish shared and private territories. We investigated the spatial strategies of users partitioned by tool type used (document- or entity-centric). We classified the types of territorial behavior exhibited in terms of how the users interacted with the display (integrated or independent workspaces). Next, we examined how territorial behavior impacted the common ground between the pairs of users. Finally, we recommend design guidelines for building co-located collaborative visual analytics tools specifically for use on large, high-resolution vertical displays

Data analysis and visualization techniques for project tracking: Experiences with the ITLingo-Cloud Platform

Considering the market's competitiveness and the complexity of organizations and projects, analyzing data is crucial to decision support on software development and project management processes. These practices are essential to increase performance, reduce costs and risks of failure, and guarantee the quality of results, keeping the work organized and controlled. ITLingo-Cloud is a multi-organization and multi-workspace collaborative platform to manage and analyze data that can support translating project performance knowledge into improved decision-making. This platform allows users to quickly set up their environment, manage workspaces and technical documentation, and analyze and observe statistics to aid both technical and business decisions. ITLingo-Cloud supports multiple technologies and languages, promotes data synchronization with templates and reusable libraries, as well as automation tasks, namely automatic data extraction, automatic validation, or document automation. The usability of ITLingo-Cloud was recently evaluated with two experiments and discussed with other related approaches.Comment: 19 pages, 5 figure

Harnessing Collaborative Technologies: Helping Funders Work Together Better

This report was produced through a joint research project of the Monitor Institute and the Foundation Center. The research included an extensive literature review on collaboration in philanthropy, detailed analysis of trends from a recent Foundation Center survey of the largest U.S. foundations, interviews with 37 leading philanthropy professionals and technology experts, and a review of over 170 online tools.The report is a story about how new tools are changing the way funders collaborate. It includes three primary sections: an introduction to emerging technologies and the changing context for philanthropic collaboration; an overview of collaborative needs and tools; and recommendations for improving the collaborative technology landscapeA "Key Findings" executive summary serves as a companion piece to this full report

Collaborative behavior, performance and engagement with visual analytics tasks using mobile devices

Interactive visualizations are external tools that can support users’ exploratory activities. Collaboration can bring benefits to the exploration of visual representations or visu‐ alizations. This research investigates the use of co‐located collaborative visualizations in mobile devices, how users working with two different modes of interaction and view (Shared or Non‐Shared) and how being placed at various position arrangements (Corner‐to‐Corner, Face‐to‐Face, and Side‐by‐Side) affect their knowledge acquisition, engagement level, and learning efficiency. A user study is conducted with 60 partici‐ pants divided into 6 groups (2 modes×3 positions) using a tool that we developed to support the exploration of 3D visual structures in a collaborative manner. Our results show that the shared control and view version in the Side‐by‐Side position is the most favorable and can improve task efficiency. In this paper, we present the results and a set of recommendations that are derived from them

Predictive analytics in facilities management: A pilot study for exploring environmental comfort using wireless sensors

Purpose: Advancements in wireless sensor technology and building modelling techniques have enabled facilities managers to understand the environmental performance of the workplace in more depth than ever before. However, it is unclear to what extent this data can be used to predict subjective environmental comfort. Thus, the aim of this study was to pilot test a methodological framework for integrating real-time environmental data with subjective ratings of environmental comfort. Design/Methodology/Approach: An open-plan office was fitted with environmental sensors to measure key indoor environmental quality parameters (carbon dioxide, temperature, humidity, illumination, and sound pressure level). Additionally, building modelling techniques were used to calculate two spatial metrics (‘workspace integration’ and workspace density) for each workspace within the study area. 15 employees were repeatedly sampled across an 11-day study period, providing 78 momentary assessments of environmental comfort. Multilevel models were used to explore the extent to which the objective environmental data predicted subjective environmental comfort. Findings: Higher carbon dioxide levels were associated with more negative ratings of air quality, higher ‘workspace integration’ was associated with higher levels of distractions, and higher workspace density was associated with lower levels of social interactions. Originality/Value: To our knowledge, this is the first field study to directly explore the relationship between physical environment data collected using wireless sensors and subjective ratings of environmental comfort. The study provides proof-of-concept for a methodological framework for the integration of building analytics and human analytics

An introduction to STRIKE : STRuctured Interpretation of the Knowledge Environment

Knowledge forms a critical part of the income generation of the system and the complex environment in which actors participate in the creation of knowledge assets merits robust, eclectic consideration. STRIKE - STRuctured Interpretation of the Knowledge Environment affords an unobtrusive and systematic framework to observe, record, evaluate and articulate concrete and abstract elements of a setting, across internal and external dimensions. Inter-relationships between actor and environment are preserved. STRIKE is supported by underlying techniques to enrich data and enhance the authenticity of its representation. Adoption of photography and videography tools provides illustrative and interpretive benefits and facilitates researcher reflexivity. This structured approach to data analysis and evaluation mitigates criticisms of methodological rigour in observational research and affords standardisation potential, germane for application in a verification or longitudinal capacity. Advancing exploratory validation studies, the method is employed to evaluate the knowledge environments of two enterprises in the UK creative sector. These occupy a critical role in fostering entrepreneurial innovation alongside participant self-efficacy. Access Space in Sheffield and the Bristol Hackspace are committed to open software, open knowledge and open participation; sharing peer learning, creativity and socio-technical aims to address broadly similar community needs. Drawing on Wittgenstein’s Picture Theory of Meaning, the knowledge management perspective is abstracted from the STRIKE assessment. It is argued that the tiered analytical approach which considers a breadth of dimensions enhances representation and interpretation of the knowledge environment and presents a diagnostic and prescriptive capability to actualise change. The paper concludes by evaluating framework effectiveness, findings application and future direction