Enabling the discovery of thematically related research objects with systematic spatializations

It is challenging for scholars to discover thematically related research in a multidisciplinary setting, such as that of a university library. In this work, we use spatialization techniques to convey the relatedness of research themes without requiring scholars to have specific knowledge of disciplinary search terminology. We approach this task conceptually by revisiting existing spatialization techniques and reframing them in terms of core concepts of spatial information, highlighting their different capacities. To apply our design, we spatialize masters and doctoral theses (two kinds of research objects available through a university library repository) using topic modeling to assign a relatively small number of research topics to the objects. We discuss and implement two distinct spaces for exploration: a field view of research topics and a network view of research objects. We find that each space enables distinct visual perceptions and questions about the relatedness of research themes. A field view enables questions about the distribution of research objects in the topic space, while a network view enables questions about connections between research objects or about their centrality. Our work contributes to spatialization theory a systematic choice of spaces informed by core concepts of spatial information. Its application to the design of library discovery tools offers two distinct and intuitive ways to gain insights into the thematic relatedness of research objects, regardless of the disciplinary terms used to describe them

A parent-centered radial layout algorithm for interactive graph visualization and animation

We have developed (1) a graph visualization system that allows users to explore graphs by viewing them as a succession of spanning trees selected interactively, (2) a radial graph layout algorithm, and (3) an animation algorithm that generates meaningful visualizations and smooth transitions between graphs while minimizing edge crossings during transitions and in static layouts. Our system is similar to the radial layout system of Yee et al. (2001), but differs primarily in that each node is positioned on a coordinate system centered on its own parent rather than on a single coordinate system for all nodes. Our system is thus easy to define recursively and lends itself to parallelization. It also guarantees that layouts have many nice properties, such as: it guarantees certain edges never cross during an animation. We compared the layouts and transitions produced by our algorithms to those produced by Yee et al. Results from several experiments indicate that our system produces fewer edge crossings during transitions between graph drawings, and that the transitions more often involve changes in local scaling rather than structure. These findings suggest the system has promise as an interactive graph exploration tool in a variety of settings

The Space Between: The Geography of Social Networks in the Tiber Valley

In displaying archaeological information as points on a map, we lose elements of the social and economic geography of the region we are studying. This paper suggests a methodology for exploring the space between our ‘dots-on-the-map’, based on the rapidly developing ‘science of networks’. It takes as a case study the distribution of sites using stamped brick in the Tiber Valley. It suggests that contradictions between local and global understandings of spatial relationships were exploitable economic opportunities

Node, Node-Link, and Node-Link-Group Diagrams: An Evaluation

Abstract—Effectively showing the relationships between objects in a dataset is one of the main tasks in information visualization. Typically there is a well-defined notion of distance between pairs of objects, and traditional approaches such as principal component analysis or multi-dimensional scaling are used to place the objects as points in 2D space, so that similar objects are close to each other. In another typical setting, the dataset is visualized as a network graph, where related nodes are connected by links. More recently, datasets are also visualized as maps, where in addition to nodes and links, there is an explicit representation of groups and clusters. We consider these three Techniques, characterized by a progressive increase of the amount of encoded information: node diagrams, node-link diagrams and node-link-group diagrams. We assess these three types of diagrams with a controlled experiment that covers nine different tasks falling broadly in three categories: node-based tasks, network-based tasks and group-based tasks. Our findings indicate that adding links, or links and group representations, does not negatively impact performance (time and accuracy) of node-based tasks. Similarly, adding group representations does not negatively impact the performance of network-based tasks. Node-link-group diagrams outperform the others on group-based tasks. These conclusions contradict results in other studies, in similar but subtly different settings. Taken together, however, such results can have significant implications for the design of standard and domain specific visualizations tools. Index Terms—graphs, networks, maps, scatter plots

Making Sense of Document Collections with Map-Based Visualizations

As map-based visualizations of documents become more ubiquitous, there is a greater need for them to support intellectual and creative high-level cognitive activities with collections of non-cartographic materials -- documents. This dissertation concerns the conceptualization of map-based visualizations as tools for sensemaking and collection understanding. As such, map-based visualizations would help people use georeferenced documents to develop understanding, gain insight, discover knowledge, and construct meaning. This dissertation explores the role of graphical representations (such as maps, Kohonen maps, pie charts, and other) and interactions with them for developing map-based visualizations capable of facilitating sensemaking activities such as collection understanding. While graphical representations make document collections more perceptually and cognitively accessible, interactions allow users to adapt representations to users’ contextual needs. By interacting with representations of documents or collections and being able to construct representations of their own, people are better able to make sense of information, comprehend complex structures, and integrate new information into their existing mental models. In sum, representations and interactions may reduce cognitive load and consequently expedite the overall time necessary for completion of sensemaking activities, which typically take much time to accomplish. The dissertation proceeds in three phases. The first phase develops a conceptual framework for translating ontological properties of collections to representations and for supporting visual tasks by means of graphical representations. The second phase concerns the cognitive benefits of interaction. It conceptualizes how interactions can help people during complex sensemaking activities. Although the interactions are explained on the example of a prototype built with Google Maps, they are independent iv of Google Maps and can be applicable to various other technologies. The third phase evaluates the utility, analytical capabilities and usability of the additional representations when users interact with a visualization prototype – VIsual COLlection EXplorer. The findings suggest that additional representations can enhance understanding of map-based visualizations of library collections: specifically, they can allow users to see trends, gaps, and patterns in ontological properties of collections

Networks, Agent-Based Models and the Antonine Itineraries: Implications for Roman Archaeology

This paper presents a way of looking at Roman space from a Roman perspective, and suggests ways in which this point of view might open up new approaches in Roman archaeology. It turns on one conception of Roman space in particular, preserved for us in the Antonine Itineraries. Working from a position that considers the context of the itineraries as movement-through-space, this paper presents an investigation using social network analysis and agent-based simulation to re-animate the itineraries. The itineraries for Iberia, Gaul, Italy, and Britain are considered. The results of the social network analysis suggest structural differences in the way that the itineraries presented space to the reader/traveler. The results of the simulation of information diffusion through these regions following the routes in the itineraries suggest ways that this conception of space affected the cultural and material development of these regions. Suggestions for extending the basic model for more complicated archaeological analyses are presented

Миф и география: география и история в античном мифе

Рассматривается проблема соотношения мифа с географией вообще и исторической географией в частност

Using Course-Subject Co-Occurrence (CSCO) to Reveal the Structure of an Academic Discipline: A Framework to Evaluate Different Inputs of a Domain Map

This article proposes, exemplifies, and validates the use of course-subject co-occurrence (CSCO) data to generate topic maps of an academic discipline. A CSCO event is when two course-subjects are taught in the same academic year by the same teacher. 61,856 CSCO events were extracted from the 2010-11 directory of the American Association of Law Schools and used to visualize the structure of law school education in the United States. Different normalization, ordination (layout), and clustering algorithms were compared and the best performing algorithm of each type was used to generate the final map. Validation studies demonstrate that CSCO produces topic maps that are consistent with expert opinion and four other indicators of the topical similarity of law school course-subjects. This research is the first to use CSCO to produce a visualization of a domain. It is also the first to use an expanded, multi-part gold-standard to evaluate the validity of domain maps and the intermediate steps in their creation. It is suggested that the framework used herein may be adopted for other studies that compare different inputs of a domain map in order to empirically derive the best maps as measured against extrinsic sources of topical similarity (gold standards)

Using Course-Subject Co-Occurrence (CSCO) to Reveal the Structure of an Academic Discipline: A Framework to Evaluate Different Inputs of a Domain Map

This article proposes, exemplifies, and validates the use of course-subject co-occurrence (CSCO) data to generate topic maps of an academic discipline. A CSCO event is when two course-subjects are taught in the same academic year by the same teacher. 61,856 CSCO events were extracted from the 2010-11 directory of the American Association of Law Schools and used to visualize the structure of law school education in the United States. Different normalization, ordination (layout), and clustering algorithms were compared and the best performing algorithm of each type was used to generate the final map. Validation studies demonstrate that CSCO produces topic maps that are consistent with expert opinion and four other indicators of the topical similarity of law school course-subjects. This research is the first to use CSCO to produce a visualization of a domain. It is also the first to use an expanded, multi-part gold-standard to evaluate the validity of domain maps and the intermediate steps in their creation. It is suggested that the framework used herein may be adopted for other studies that compare different inputs of a domain map in order to empirically derive the best maps as measured against extrinsic sources of topical similarity (gold standards)

Doctor of Philosophy

dissertationRecent advancements in mobile devices - such as Global Positioning System (GPS), cellular phones, car navigation system, and radio-frequency identification (RFID) - have greatly influenced the nature and volume of data about individual-based movement in space and time. Due to the prevalence of mobile devices, vast amounts of mobile objects data are being produced and stored in databases, overwhelming the capacity of traditional spatial analytical methods. There is a growing need for discovering unexpected patterns, trends, and relationships that are hidden in the massive mobile objects data. Geographic visualization (GVis) and knowledge discovery in databases (KDD) are two major research fields that are associated with knowledge discovery and construction. Their major research challenges are the integration of GVis and KDD, enhancing the ability to handle large volume mobile objects data, and high interactivity between the computer and users of GVis and KDD tools. This dissertation proposes a visualization toolkit to enable highly interactive visual data exploration for mobile objects datasets. Vector algebraic representation and online analytical processing (OLAP) are utilized for managing and querying the mobile object data to accomplish high interactivity of the visualization tool. In addition, reconstructing trajectories at user-defined levels of temporal granularity with time aggregation methods allows exploration of the individual objects at different levels of movement generality. At a given level of generality, individual paths can be combined into synthetic summary paths based on three similarity measures, namely, locational similarity, directional similarity, and geometric similarity functions. A visualization toolkit based on the space-time cube concept exploits these functionalities to create a user-interactive environment for exploring mobile objects data. Furthermore, the characteristics of visualized trajectories are exported to be utilized for data mining, which leads to the integration of GVis and KDD. Case studies using three movement datasets (personal travel data survey in Lexington, Kentucky, wild chicken movement data in Thailand, and self-tracking data in Utah) demonstrate the potential of the system to extract meaningful patterns from the otherwise difficult to comprehend collections of space-time trajectories