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

Design Spaces in Visual Analytics Based on Goals: Analytical Behaviour, Exploratory Investigation, Information Design & Perceptual Tasks

This paper considers a number of perspectives on design spaces in visual analytics and proposes a new set of four design spaces, based on user goals. Three of the user goals are derived from the literature and are categorised under the terms exploratory investigation, perceptual tasks, and information design. The fourth goal is categorised as analytical behaviour; a recently defined term referring to the study of decision-making facilitated by visual analytics. This paper contributes to the literature on decision-making in visual analytics with a survey of real-world applications within the analytical behaviour design space and by providing a new perspective on design spaces. Central to our analysis is the introduction of decision concepts and theories from economics into a visual analytics context. Given the recent interest in decision-making we wanted to understand the emerging topic of analytical behaviour as a design space and found it necessary to look at more than just decision-making to make a valuable contribution. The result is an initial framework suitable for use in the analysis or design of analytical behaviour applications

The Italian version of the Thinking About Life Experiences Questionnaire and its relationship with gender, age, and life events on Facebook

The present study provided a cross-cultural validation of the Thinking About Life Experiences Scale-revised (TALE-R) in an Italian sample of Facebook users (n = 492; female = 378; male = 114; mean age 26.1) to test for replication and universality of the TALE-R three-factor model. Furthermore, it explored the interrelations among gender, age, the scores at the TALE-R and the frequency of posting textual/visual information about individuals' life events on Facebook. Results at exploratory and confirmatory factor analysis gave empirical support to both of a tripartite model for the functions of autobiographical memory (i.e., directive-behavior, social-bonding, and self-continuity) and measurement invariance of this three-factor model across gender and age. Further results at linear correlation and regression analyses showed that directive-behavior and self-continuity functions of autobiographical memory are significantly related to the ways people use Facebook for personal documentation. Age differences more than gender influence this association. Discussion and conclusion reported both theoretical and empirical implications of the findings of the study

Design Spaces in Visual Analytics Based on Goals: Analytical Behaviour, Exploratory Investigation, Information Design & Perceptual Tasks

This paper considers a number of perspectives on design spaces in visual analytics and proposes a new set of four design spaces, based on user goals. Three of the user goals are derived from the literature and are categorised under the terms exploratory investigation, perceptual tasks, and information design. The fourth goal is categorised as analytical behaviour; a recently defined term referring to the study of decision-making facilitated by visual analytics. This paper contributes to the literature on decision-making in visual analytics with a survey of real-world applications within the analytical behaviour design space and by providing a new perspective on design spaces. Central to our analysis is the introduction of decision concepts and theories from economics into a visual analytics context. Given the recent interest in decision-making we wanted to understand the emerging topic of analytical behaviour as a design space and found it necessary to look at more than just decision-making to make a valuable contribution. The result is an initial framework suitable for use in the analysis or design of analytical behaviour applications

Competitive analysis of online reviews using exploratory text mining

Purpose – This paper explores the usefulness of analyzing text-based online reviews using text mining tools and visual analytics for SWOT Analysis, as applied to the hotel industry. These results can be used to develop competitive actions. Design – The text mining/visualization tool, ReviewMap, was used to transform an archive of reviews spanning multiple suppliers into a hierarchy of data of increasing dimensionality. Visual summaries at each level were integrated to propagate selections at one level throughout the rest of the hierarchy. These visual summaries identify features required for competition at a given level and features that currently discriminate amongst competitors. Methodology – The approach was exploratory, the objective of which was to determine if useable competitive intelligence could be found in a typical collection of online reviews for a set of competing hotels. A publically available collection of reviews was subjected to a set of text mining procedures and visual analyses in order to summarize the features and opinions expressed. Originality – Prior analyses of online reviews relied solely upon numeric “star” ratings. This study utilized text mining to uncover information within the written comments and applied the information in a SWOT Analysis of three competing hotels. Findings – In the set of reviews used in this paper, a common measure of analytical power almost doubled when text mining summaries of the written comments were used in combination with numeric ratings. Visual analytics revealed the dominant features for each hotel, the features required of all hotels competing at a given level, and the features that define specific positions within the competitive landscape. This analysis of strengths, weaknesses, opportunities and threats revealed several promising competitive actions for the hotels in the study

Information Seeking in Context: Teachers' Content Selection during Lesson Planning Using the Shoah Foundation's Visual History Archive of Holocaust Survivor Testimony

This study explored the information seeking task of content selection. An integrative conceptual framework used existing models to examine the context and process of information seeking, evaluation, and selection. The conceptual framework incorporated three main elements of the information seeking process: * The information need context, * The information search process, * Relevance criteria. Among teachers' many duties are the creation, implementation, and revision of lesson plans. A subtask of lesson planning is content selection, which occurs when teachers seek outside content, such as readings or audio recordings, to incorporate into lesson plans. Content selection is seen here as a work-task-embedded information seeking process. A qualitative study was implemented within the setting of a week-long professional development workshop, during which eight teachers used a custom software product that combined a lesson-planning module with an information retrieval (IR) system. The IR system provided access to a subset of the Shoah Foundation's Visual History Archive. Data types included interviews, fly-on-the-wall transcripts, transaction logs, relevance judgments, and lesson plans. Analysis combined inductive and deductive techniques, including start codes, constant comparison, emergent themes, and matrix analysis. Findings depict associations among each component of the framework. 1. The information need context consists of five layers (Environment, Role, Person, Task, Information Source), each of which influences information search and relevance. 2. The ISP includes two cognitive-behavioral facets: Conceptualizing and Actualizing. 3. Relevance criteria are the situationally-driven embodiment of contextual elements that apply to information seeking. These findings have theoretical and practical implications for information studies and education. For information studies, this study contributes to understanding of the ISP as contextual, cognitive, and interactive. Information need, while unobservable in its native form, can be depicted in enough detail to supply meaningful requirements for the design of information systems and processes. Content selection is a form of exploratory search, and this study's implications suggest that the "traditional" reference interview should be used as an interaction model during exploratory search. For education, this study extends the discourse about consequences of standards-based education for teacher practice and contributes to models of teacher planning as an iterative, cognitive process

Revamping a Research Library Website from a Content Management Software to an Integrated Library Management Software

An advance in information and communication technology has challenged all the service sectors including libraries and information centres. Providing reliable information services through library websites that is easy and intuitive for the user is a major concern for the entire library professional. This work is a case study on the library website of the Indian Institute of Astrophysics. Formerly the library had Libsys 4.0 as the library automation software and presently it has been migrated to Koha 20.05. The study aims to explore the factors the institute takes into consideration for renovating the website. The new website of IIA Library is a visual example of an integrated library management system where all the spectrums of the library modules are brought down under a single platform designed in Koha. The study design is based on descriptive and exploratory analysis of the former and the later website. The case-study method of the study brings out the possible methods exercised in the process of data correction and migration from LibSys to Koha. For libraries and information centres or other similar institutes planning for a website migration, this case study can provide a point of initiation and culminate the important points required for the revamp

Efficient Point Clustering for Visualization

The visualization of large spatial point data sets constitutes a problem with respect to runtime and quality. A visualization of raw data often leads to occlusion and clutter and thus a loss of information. Furthermore, particularly mobile devices have problems in displaying millions of data items. Often, thinning via sampling is not the optimal choice because users want to see distributional patterns, cardinalities and outliers. In particular for visual analytics, an aggregation of this type of data is very valuable for providing an interactive user experience. This thesis defines the problem of visual point clustering that leads to proportional circle maps. It furthermore introduces a set of quality measures that assess different aspects of resulting circle representations. The Circle Merging Quadtree constitutes a novel and efficient method to produce visual point clusterings via aggregation. It is able to outperform comparable methods in terms of runtime and also by evaluating it with the aforementioned quality measures. Moreover, the introduction of a preprocessing step leads to further substantial performance improvements and a guaranteed stability of the Circle Merging Quadtree. This thesis furthermore addresses the incorporation of miscellaneous attributes into the aggregation. It discusses means to provide statistical values for numerical and textual attributes that are suitable for side-views such as plots and data tables. The incorporation of multiple data sets or data sets that contain class attributes poses another problem for aggregation and visualization. This thesis provides methods for extending the Circle Merging Quadtree to output pie chart maps or maps that contain circle packings. For the latter variant, this thesis provides results of a user study that investigates the methods and the introduced quality criteria. In the context of providing methods for interactive data visualization, this thesis finally presents the VAT System, where VAT stands for visualization, analysis and transformation. This system constitutes an exploratory geographical information system that implements principles of visual analytics for working with spatio-temporal data. This thesis details on the user interface concept for facilitating exploratory analysis and provides the results of two user studies that assess the approach

Computational Modelling of Information Gathering

This thesis describes computational modelling of information gathering behaviour under active inference – a framework for describing Bayes optimal behaviour. Under active inference perception, attention and action all serve for same purpose: minimising variational free energy. Variational free energy is an upper bound on surprise and minimising it maximises an agent’s evidence for its survival. An agent achieves this by acquiring information (resolving uncertainty) about the hidden states of the world and uses the acquired information to act on the outcomes it prefers. In this work I placed special emphasis on the resolution of uncertainty about the states of the world. I first created a visual search task called scene construction task. In this task one needs to accumulate evidence for competing hypotheses (different visual scenes) through sequential sampling of a visual scene and categorising it once there is sufficient evidence. I showed that a computational agent attends to the most salient (epistemically valuable) locations in this task. In the next, this task was performed by healthy humans. Healthy people’s exploration strategies provided evidence for uncertainty driven exploration. I also showed how different exploratory behaviours can be characterised using canonical correlation analysis. In the next study I showed how exploration of a visual scene under different instructions could be explained by appealing to the computational mechanisms that may correspond to attention. This entailed manipulating the precision of task irrelevant cues and their hidden causes as a function of instructions. In the final work, I was interested in characterising impulsive behaviour using a patch leaving paradigm. By varying the parameters of the MDP model, I showed that there could be at least three distinct causes of impulsive behaviour, namely a lower depth of planning, a lower capacity to maintain and process information, and an increased perceived value of immediate rewards

Interactive visual data exploration with subjective feedback : an information-theoretic approach

Visual exploration of high-dimensional real-valued datasets is a fundamental task in exploratory data analysis (EDA). Existing methods use predefined criteria to choose the representation of data. There is a lack of methods that (i) elicit from the user what she has learned from the data and (ii) show patterns that she does not know yet. We construct a theoretical model where identified patterns can be input as knowledge to the system. The knowledge syntax here is intuitive, such as "this set of points forms a cluster", and requires no knowledge of maths. This background knowledge is used to find a Maximum Entropy distribution of the data, after which the system provides the user data projections in which the data and the Maximum Entropy distribution differ the most, hence showing the user aspects of the data that are maximally informative given the user's current knowledge. We provide an open source EDA system with tailored interactive visualizations to demonstrate these concepts. We study the performance of the system and present use cases on both synthetic and real data. We find that the model and the prototype system allow the user to learn information efficiently from various data sources and the system works sufficiently fast in practice. We conclude that the information theoretic approach to exploratory data analysis where patterns observed by a user are formalized as constraints provides a principled, intuitive, and efficient basis for constructing an EDA system