Defining and applying a language for discovery

In order to design better search experiences, we need to understand the complexities of human information-seeking behaviour. In this paper, we propose a model of information behaviour based on the needs of users across a range of search and discovery scenarios. The model consists of a set of modes that that users employ to satisfy their information goals. We discuss how these modes relate to existing models of human information seeking behaviour, and identify areas where they differ. We then examine how they can be applied in the design of interactive systems, and present examples where individual modes have been implemented in interesting or novel ways. Finally, we consider the ways in which modes combine to form distinct chains or patterns of behaviour, and explore the use of such patterns both as an analytical tool for understanding information behaviour and as a generative tool for designing search and discovery experiences

The Tetris model of resolving information needs within the information seeking process

Theoretical abstractions, of many different aspects of search, have played a crucial role in driving research into human information seeking and retrieval forward. From models of the Information Seeking Process, to how we perceive search systems, these models help us to 1) conceptually formalise and separate aspects of the model’s focus, 2) communicate more clearly about these aspects, 3) create hypotheses for subsequent research, and 4) produce implications for future systems. Implicit in these four aspects is that models and theories should have a focus and a purpose. After clarifying the relationships between models, theories, and meta-theories, this perspectives paper introduces the Tetris Model of Resolving Information Needs within the Information Seeking Process, the purpose of which is to better represent the behaviours around the Human Computer Interaction with Information Retrieval, which are often confounded within stage-based models of the Information Seeking Process. In particular, the possible sequence of actions performed by a searcher are typically linearly aligned from left-to-right, and thus imply a temporal progression. The differing focus of the Tetris model is to better capture the temporal experience of searching, by removing the implied progression of left-to-right. The aim of this perspectives paper, therefore, is to introduce this new Tetris Model, such that it can be used to formalise people’s interactive experiences in a new way, so that we can more clearly communicate about them, create hypotheses from the model, and consider novel design implications based upon it

Q Methodology as a research methodology for human computer interaction

This paper briefly introduces the reader to QMethodology and suggests its suitability for research with the field of He!. Furthermore, this paper takes the perspective that HCI is largely aform ofhuman to human interaction. Thus design for HC! would need to take into account human understandings, of computers, systems, networks and software, by all types ofparticipants, iffruitfUl interaction between computers and people and the people who use them is to occur. This paper describes and suggests the use of an established methodology, QMethodology, for the examination of human perceptions in HCI. The example this paper gives is a study that is currently being done in a cross cultural setting to \u27explore metaphorically based schema that individuals use to understand, information, information technology, and information seeking

MEDIATOR: TOWARDS A NEGOTIATION SUPPORT SYSTEM

MEDIATOR is a negotiation support system (NSS) based on evolutionary systems design (ESD) and database-centered implementation. It supports negotiations by consensus seeking through exchange of information and, where consensus is incomplete, by compromise. The negotiation problem is shown --graphically or as relational data in matrix form-- in three spaces as a mapping from control space to goal space (and through marginal utility functions) to utility space. Within each of these spaces the negotiation process is characterized by adaptive change, i.e., mappings of group target and feasible sets by which these sets are redefined in seeking a solution characterized by a single-point intersection between them. This concept is being implemented in MEDIATOR, a data-based micro-mainframe NSS intended to support the players and a human mediator in multi-player decision situations. Each player employs private and shared database views, using his/her own micro-computer decision support system enhanced with a communications manager to interact with the mediator DSS. Sharing of views constitutes exchange of information which can lead towards consensus. The human mediator can support compromise, as needed, through use of solution concepts and/or concession-making procedures in the NSS model base. As a concrete example, we demonstrate the use of the system for group car buying decisions.Information Systems Working Papers Serie

Understanding the information needs of public health practitioners: A literature review to inform design of an interactive digital knowledge management system

AbstractThe need for rapid access to information to support critical decisions in public health cannot be disputed; however, development of such systems requires an understanding of the actual information needs of public health professionals. This paper reports the results of a literature review focused on the information needs of public health professionals. The authors reviewed the public health literature to answer the following questions: (1) What are the information needs of public health professionals? (2) In what ways are those needs being met? (3) What are the barriers to meeting those needs? (4) What is the role of the Internet in meeting information needs? The review was undertaken in order to develop system requirements to inform the design and development of an interactive digital knowledge management system. The goal of the system is to support the collection, management, and retrieval of public health documents, data, learning objects, and tools.Method:The search method extended beyond traditional information resources, such as bibliographic databases, tables of contents (TOC), and bibliographies, to include information resources public health practitioners routinely use or have need to use—for example, grey literature, government reports, Internet-based publications, and meeting abstracts.Results:Although few formal studies of information needs and information-seeking behaviors of public health professionals have been reported, the literature consistently indicated a critical need for comprehensive, coordinated, and accessible information to meet the needs of the public health workforce. Major barriers to information access include time, resource reliability, trustworthiness/credibility of information, and “information overload”.Conclusions:Utilizing a novel search method that included the diversity of information resources public health practitioners use, has produced a richer and more useful picture of the information needs of the public health workforce than other literature reviews. There is a critical need for public health digital knowledge management systems designed to reflect the diversity of public health activities, to enable human communications, and to provide multiple access points to critical information resources. Public health librarians and other information specialists can serve a significant role in helping public health professionals meet their information needs through the development of evidence-based decision support systems, human-mediated expert searching and training in the use information retrieval systems

Interactive analogical retrieval: practice, theory and technology

Analogy is ubiquitous in human cognition. One of the important questions related to understanding the situated nature of analogy-making is how people retrieve source analogues via their interactions with external environments. This dissertation studies interactive analogical retrieval in the context of biologically inspired design (BID). BID involves creative use of analogies to biological systems to develop solutions for complex design problems (e.g., designing a device for acquiring water in desert environments based on the analogous fog-harvesting abilities of the Namibian Beetle). Finding the right biological analogues is one of the critical first steps in BID. Designers routinely search online in order to find their biological sources of inspiration. But this task of online bio-inspiration seeking represents an instance of interactive analogical retrieval that is extremely time consuming and challenging to accomplish. This dissertation focuses on understanding and supporting the task of online bio-inspiration seeking. Through a series of field studies, this dissertation uncovered the salient characteristics and challenges of online bio-inspiration seeking. An information-processing model of interactive analogical retrieval was developed in order to explain those challenges and to identify the underlying causes. A set of measures were put forth to ameliorate those challenges by targeting the identified causes. These measures were then implemented in an online information-seeking technology designed to specifically support the task of online bio-inspiration seeking. Finally, the validity of the proposed measures was investigated through a series of experimental studies and a deployment study. The trends are encouraging and suggest that the proposed measures has the potential to change the dynamics of online bio-inspiration seeking in favor of ameliorating the identified challenges of online bio-inspiration seeking.PhDCommittee Chair: Goel, Ashok; Committee Member: Kolodner, Janet; Committee Member: Maher, Mary Lou; Committee Member: Nersessian, Nancy; Committee Member: Yen, Jeannett

Foregrounding the “I” in IS Research : A Plea for Research on Computer-mediated Human Information Behaviour

Starting in the mid of the 20th century, the emergence of contemporary information technologies has dramatically changed the way information is disseminated and absorbed in organizational and private contexts. Recent advances in information technology make information ubiquitously available with the help of novel hardware and software, like mobile devices, corporate social networks or microblogging services. They enable organizational actors and private users to access information from multiple sources across a multitude of different computer-based channels. However, today’s abundance of information does not only result in higher organizational productivity and an enrichment of its recipients’ lives in general. It also introduces new challenges as the mental information processing capabilities of human IS users improve not at the same speed as hardware and software technologies do, being constrained by cognitive limitations and evolutionary-shaped behavioural patterns guiding the absorption and use of information. Hence, it appears to be paramount to consider the aforementioned limitations as one important facet of human information behaviour with respect to a more human-centric use and design of information systems. Faster and more intelligent data processing capabilities, which recently have often been expressed with the term "big data", does not automatically lead to a better understanding of mental information processing capabilities of humans. Thus, we propose to focus on the processes and states that occur when humans process information in their brain as well. The entity “information” is a constituent of the Information Systems discipline, thus underlining the field’s focus on the development and use of technologies that support humans in gathering and processing information that are required in various business and private contexts. Unfortunately, however, the analysis and explanation of the relationship between human technology users and the entity information has never been the discipline’s core research in3 terest. In fact, research on the behaviour of human beings when interacting with information in computer-based contexts is largely fragmented and frequently generates conflicting results. Consequently, the goal of this paper is twofold. First, it reviews existing research with respect to information or information related behaviours. Second, based on the findings of the review, it intend to demonstrate how the research on computer-mediated information behaviours could significantly enrich IS research. Thus, we provide a profound and structured overview of extant research on the relationship between human beings and the entity information in the IS domain. Then, the article aims at creating intertextual coherence by harmonizing fragmented pieces of research as well as to identify fundamental research gaps that motivate promising future research trajectories. The latter will be exemplified with the yet under-researched phenomena of channel-dependent information seeking, information stopping, and information avoidance behaviour. Toward this end, the IS literature on information behaviours is analyzed using a conceptual framework developed based upon a synthesis and extenbsion of previous work on human information behaviour. Where appropriate, articles from non-IS journals are integrated into the analysis to complement and extend the findings. The result is a review article centred around organizing our existing knowledge of human behaviour in relation to the entity information in computer-based contexts with the overarching goal of advancing theory development

Designing a system to mimic expert cognition: An initial prototype

In this paper, we present a proof-of-concept system to highlight the potential benefits of mimicking higher-order cognitive processes involved in ‘insight seeking’ to create the necessary context for expert sensemaking. We draw upon data from a realistic investigation exercise undertaken by 14 experienced intelligence analysts and use this to develop our prototype to mimic behaviours demonstrated by expert analysts. Our prototype system evaluates different strategies and provides recommendations for an analyst to explore, through a prototype user interface. The recommended strategies, and associated information retrieved, aligns with the actual investigations. We propose that our system presents a novel and promising approach to design AI support systems for tasks that typically require human expert cognitive processes