On Birthing Dancing Stars: The Need for Bounded Chaos in Information Interaction

While computers causing chaos is acommon social trope, nearly the entirety of the history of computing is dedicated to generating order. Typical interactive information retrieval tasks ask computers to support the traversal and exploration of large, complex information spaces. The implicit assumption is that they are to support users in simplifying the complexity (i.e. in creating order from chaos). But for some types of task, particularly those that involve the creative application or synthesis of knowledge or the creation of new knowledge, this assumption may be incorrect. It is increasingly evident that perfect order—and the systems we create with it—support highly-structured information tasks well, but provide poor support for less-structured tasks.We need digital information environments that help create a little more chaos from order to spark creative thinking and knowledge creation. This paper argues for the need for information systems that offerwhat we term ‘bounded chaos’, and offers research directions that may support the creation of such interface

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

Applying a Topical Relevance Typology to Analyze Online Product Information Types and Their Effects on Internet Consumer Decision

This paper lays out a research proposal of systematically analyzing and comparing the decision effects of online product information types. Hardly any in-depth knowledge is currently available on how different information types influence online consumer trust and purchase intention. To address this research gap, we apply a generic function-based topical relevance typology to classify the variety of online product information and plan for focused comparisons of the functional roles played by different information types in e-retailing. Understanding the differential impacts of each information type provides a basis for prioritizing online information provisioning and organization, which becomes particularly meaningful in the current context of information overload. The paper briefly reviews information research in e-commerce, introduces the product type as an important moderating factor, and discusses the conceptual basis and applicability of applying the generic relevance typology to analyze product relevant information. The research model and preliminary hypotheses are also described

Closing the loop: assisting archival appraisal and information retrieval in one sweep

In this article, we examine the similarities between the concept of appraisal, a process that takes place within the archives, and the concept of relevance judgement, a process fundamental to the evaluation of information retrieval systems. More specifically, we revisit selection criteria proposed as result of archival research, and work within the digital curation communities, and, compare them to relevance criteria as discussed within information retrieval's literature based discovery. We illustrate how closely these criteria relate to each other and discuss how understanding the relationships between the these disciplines could form a basis for proposing automated selection for archival processes and initiating multi-objective learning with respect to information retrieval

Function-Based Categorization of Online Product Information Types

Hardly any in-depth knowledge is currently available on how different types of product-relevant information influence online consumer trust and purchase decision. To address this research gap, we apply a generic function-based information typology to systematically classify the large variety of online product information and plan for a focused comparison of their functional roles and differential effects on online consumer decision making. The ultimate goal is to provide a theoretical basis for guiding and prioritizing online information organization and provision, which becomes increasingly important in the current context of information overload. The paper briefly reviews information research in e-commerce, discusses the conceptual basis of applying the generic function-based topical relevance typology to analyze online product information, and uses a variety of product examples from Amazon.com to demonstrate the process. The paper concludes with preliminary findings from this pilot study