Experiences with starfield visualizations for analysis of library collections

This paper presents a qualitative and formative study of the uses of a starfield-based visualization interface for analysis of library collections. The evaluation process has produced feedback that suggests ways to significantly improve starfield interfaces and the interaction process to improve their learnability and usability. The study also gave us clear indication of additional potential uses of starfield visualizations that can be exploited by further functionality and interface development. We report on resulting implications for the design and use of starfield visualizations that will impact their graphical interface features, their use for managing data quality and their potential for various forms of visual data mining. Although the current implementation and analysis focuses on the collection of a physical library, the most important contributions of our work will be in digital libraries, in which volume, complexity and dynamism of collections are increasing dramatically and tools are needed for visualization and analysis

A tool for metadata analysis

We describe a Web-based metadata quality tool that provides statistical descriptions and visualisations of Dublin Core metadata harvested via the OAI protocol. The lightweight nature of development allows it to be used to gather contextualized requirements and some initial user feedback is discussed

Metadata Quality for Digital Libraries

The quality of metadata in a digital library is an important factor in ensuring access for end-users. Several studies have tried to define quality frameworks and assess metadata but there is little user feedback about these in the literature. As collections grow in size maintaining quality through manual methods becomes increasingly difficult for repository managers. This research presents the design and implementation of a web-based metadata analysis tool for digital repositories. The tool is built as an extension to the Greenstone3 digital library software. We present examples of the tool in use on real-world data and provide feedback from repository managers. The evidence from our studies shows that automated quality analysis tools are useful and valued service for digital libraries

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

Characterizing and Evaluating Users' Information Seeking Behavior in Social Tagging Systems

Social tagging systems in the Web 2.0 era present an innovative information seeking environment succeeding the library and traditional Web. The primary goals of this study were to, in this particular context: (1) identify the general information seeking strategies adopted by users and determine their effectiveness; (2) reveals the characteristics of the users who prefer different strategies; and (3) identify the specific traits of users' information seeking paths and understand factors shaping them. A representative social tagging system, Douban (http://www.douban.com/) was chosen as the research setting in order to generate empirical findings.Based on the mixed methods research design, this study consists of a quantitative phase and a qualitative phase. The former firstly involved a clickstream data analysis of 20 million clickstream records requested from Douban at the footprint, movement, and track levels. Limited to studying physical behavior, it was complemented by an online survey which captured Douban users' background information from various aspects. In the subsequent qualitative phase, a focus group gathered a number of experienced Douban users to help interpret the quantitative results.Major findings of this study show that: (1) the general strategies include encountering, browsing by resource, browsing by tag, browsing by user/group, searching, and monitoring by user/group; (2) while browsing by resource is the most popular strategy, browsing by tag is the most effective one; (3) users preferring different strategies do not have significantly different characteristics; and (4) on users' information seeking paths these exist two resource viewing patterns - continuous and sporadic, and two resource collecting patterns - lagged and instant, and they can be attributed to user, task, and system factors.A model was developed to illustrate the strategic and tactic layers of users' information seeking behavior in social tagging systems. It offers a deep insight into the behavioral changes brought about by this new environment as compared to the Web in general. This model can serve as the theoretical base for designing user-oriented information seeking interfaces for social tagging systems so that the general strategies and specific tactics will be accommodated efficiently

Topic-Relevance Map: Visualization for Improving Search Result Comprehension

Peer reviewe

Scholarly chronographics: can a timeline be useful in historiography?

Our paper is concerned with the visualisation of historical events and artefacts in the context of time. It arises from a project bringing together expertise in visualisation, historiography and software engineering. The work is the result of an extended enquiry over several years which has included investigation of the prior history of such chronographics and their grounding in the temporal ontology of the Enlightenment. Timelines - visual, spatial presentations of chronology - are generally regarded as being too simple, perhaps too childish, to be worthy of academic attention, yet such chronographics should be capable of supporting sophisticated thinking about history and historiography, especially if they take full advantage of the capabilities of digital technologies. They should enable even professional academic historians to 'make sense' of history in new ways, allowing them insights they would not otherwise have achieved. In our paper we highlight key findings from the history of such representations, principally from the eighteenth and nineteenth centuries, and show how, in a project to develop new digital chronographics for collections of cultural objects and events, we have explored new implementations of the important ideas we have extracted about timewise presentation and interaction. This includes the representation of uncertainty, of relations between events, and the epistemology of time as a 'space' for history. We present developed examples, in particular a chronographic presentation of a large database of works by a single author, a composer, and discuss the extent to which our ambitions for chronographics have been realised in practice. Keywords: timeline, chronographic

Using Web Archives to Enrich the Live Web Experience Through Storytelling

Much of our cultural discourse occurs primarily on the Web. Thus, Web preservation is a fundamental precondition for multiple disciplines. Archiving Web pages into themed collections is a method for ensuring these resources are available for posterity. Services such as Archive-It exists to allow institutions to develop, curate, and preserve collections of Web resources. Understanding the contents and boundaries of these archived collections is a challenge for most people, resulting in the paradox of the larger the collection, the harder it is to understand. Meanwhile, as the sheer volume of data grows on the Web, storytelling is becoming a popular technique in social media for selecting Web resources to support a particular narrative or story . In this dissertation, we address the problem of understanding the archived collections through proposing the Dark and Stormy Archive (DSA) framework, in which we integrate storytelling social media and Web archives. In the DSA framework, we identify, evaluate, and select candidate Web pages from archived collections that summarize the holdings of these collections, arrange them in chronological order, and then visualize these pages using tools that users already are familiar with, such as Storify. To inform our work of generating stories from archived collections, we start by building a baseline for the structural characteristics of popular (i.e., receiving the most views) human-generated stories through investigating stories from Storify. Furthermore, we checked the entire population of Archive-It collections for better understanding the characteristics of the collections we intend to summarize. We then filter off-topic pages from the collections the using different methods to detect when an archived page in a collection has gone off-topic. We created a gold standard dataset from three Archive-It collections to evaluate the proposed methods at different thresholds. From the gold standard dataset, we identified five behaviors for the TimeMaps (a list of archived copies of a page) based on the page’s aboutness. Based on a dynamic slicing algorithm, we divide the collection and cluster the pages in each slice. We then select the best representative page from each cluster based on different quality metrics (e.g., the replay quality, and the quality of the generated snippet from the page). At the end, we put the selected pages in chronological order and visualize them using Storify. For evaluating the DSA framework, we obtained a ground truth dataset of hand-crafted stories from Archive-It collections generated by expert archivists. We used Amazon’s Mechanical Turk to evaluate the automatically generated stories against the stories that were created by domain experts. The results show that the automatically generated stories by the DSA are indistinguishable from those created by human subject domain experts, while at the same time both kinds of stories (automatic and human) are easily distinguished from randomly generated storie