Complex Information Spaces Research Articles

«Язык» тела: тело в трансляции сенсорной информации в традиционном мировоззрении тюрко-монгольских народов

The article aims to study the information context of the body signs and the perception of this information by Inner Asian nomads in terms of man and nature interaction. Methods. The research is based on general scientific methods and particular methods of historical science, such as the historical-comparative research method and the method of cultural-historical reconstruction. Materials. In terms of studies of humans as social and biological beings, it is relevant to examine the human body in the system of traditional somatic representations of the Turkic-Mongolian peoples of Inner Asia. In their worldview, the human body represents a specialized “map” of messages of a physiological nature, where organs and body parts were seen as symmetrical and their messages were perceived as negative or positive, depending on location on the left or on the right. Of relevance was also whether the sign came from the upper or lower part of a particular organ. Special attention was paid to the “movements” of the liver and the heart. Conclusions. The study shows that the world that surrounds a person appeared as a complex multidimensional information space, with sensory information playing an important part in its perception. This information was not limited to images created by the senses. In fact, the entire body, including internal organs, was perceived as such a conductor, with various manifestations of a physiological nature, such as trembling, noises, itching, and pains serving as “messages”. Individuals that had special body sensitivity were described as those of “open flesh” or of “light bones”; these were usually the only child in the family or one of the twins.

A Novel Overlapping Method to Alleviate the Cold-Start Problem in Recommendation Systems

Recommendation systems (RSs) are tools for interacting with large and complex information spaces. They provide a personalized view of such spaces, prioritizing items likely to be of interest to the user. The main objective of RSs is to tool up users with desired items that meet their preferences. A major problem in RSs is called: “cold-start”; it is a potential problem called so in computer-based information systems which comprises a degree of automated data modeling. Particularly, it concerns the issue in which the system cannot draw any inferences nor have it yet gathered sufficient information about users or items. Since RSs performance is substantially limited by cold-start users and cold-start items problems; this research study takes the route for a major aim to attenuate users’ cold-start problem. Still in the process of researching, sundry studies have been conducted to tackle this issue by using clustering techniques to group users according to their social relations, their ratings or both. However, a clustering technique disregards a variety of users’ tastes. In this case, the researcher has adopted the overlapping technique as a tool to deal with the clustering technique’s defects. The advantage of the overlapping technique excels over others by allowing users to belong to multi-clusters at the same time according to their behavior in the social network and ratings feedback. On that account, a novel overlapping method is presented and applied. This latter is executed by using the partitioning around medoids (PAM) algorithm to implement the clustering, which is achieved by means of exploiting social relations and confidence values. After acquiring users’ clusters, the average distances are computed in each cluster. Thereafter, a content comparison is made regarding the distances between every user and the computed distances of the clusters. If the comparison result is less than or equal to the average distance of a cluster, a new user is added to this cluster. The singular value decomposition plus (SVD[Formula: see text]) method is then applied to every cluster to compute predictions values. The outcome is calculated by computing the average of mean absolute error (MAE) and root mean square error (RMSE) for every cluster. The model is tested by two real world datasets: Ciao and FilmTrust. Ultimately, findings have exhibited a great deal of insights on how the proposed model outperformed a number of the state-of-the-art studies in terms of prediction accuracy.

Investigating Information: A Qualitative Analysis of Expert Designers’ Information Representation and Structuring Behaviors

Abstract Information organization and utilization are integral to the design and development of creative ideas. However, navigating this often complex information space can be challenging, even for experienced designers. Therefore, a deep analysis of how expert software designers utilize and organize information is needed to provide qualitative insights into their information organization strategies. To address this, four professionals in the software design and development field were recruited for individual 3-hour design sessions. They were asked to generate ideas for a design challenge (reducing distraction-based pedestrian accidents) using information sheets specifically developed to contain different types of information, as identified by prior work. Results reveal individual differences in information approach and categorization, although these were motivated by similar underlying patterns of evaluating the relevance of the information for its ability to inform the project constraints, resources, or (user) requirements. Designer experience and use of design processes and knowledge transfer tools enhanced their ability to turn information into insights.

Designing a Periodic Table for Alloy Design: Harnessing Machine Learning to Navigate a Multiscale Information Space

We provide an overview of how to apply statistical learning methods to directly track the role of alloying additions in the multiscale properties of alloys. This leads to a mapping process analogous to the Periodic Table where the resulting visualization scheme exhibits the grouping and proximity of elements based on their impact on the properties of alloys. Unlike the conventional Periodic Table of elements, the distance between neighboring elements in our Alloy Periodic Table uncovers relationships in a complex high-dimensional information space that would not be easily seen otherwise. We embed this machine learning approach with an epistemic uncertainty assessment between data. We provide examples of how this data-driven exploratory platform appears to capture the alloy chemistry of known engineering alloys as well as to provide potential new directions for tuning chemistry for enhanced performance, consistent with accepted mechanistic paradigms governing alloy mechanical properties.

Piecing the Patient Story Back Together: Why the Patient and Caregiver Contribution Matters.

Clinicians make decisions based on a large and complex patient information space in time pressured situations. Through continuity, experience, and privileged knowledge, the patient and caregiver(s) are in a position to support clinician decisionmaking through information delivery. For example, they may make salient relevant information or provide an integrated patient story to help clinicians overcome challenges of making decisions based on incomplete information. Recommendations of engaging patient/caregiver(s) include fostering a culture of listening by clinicians, speaking up by patient/caregiver(s), effective patient education and health information technology, and family-centered rounding and hand-offs. Using a lived experience, I illustrate the value of the potential impact of caregiver’s informational contribution to patient safety.

Visualization of Cultural Heritage Collection Data: State of the Art and Future Challenges.

After decades of digitization, large cultural heritage collections have emerged on the web, which contain massive stocks of content from galleries, libraries, archives, and museums. This increase in digital cultural heritage data promises new modes of analysis and increased levels of access for academic scholars and casual users alike. Going beyond the standard representations of search-centric and grid-based interfaces, a multitude of approaches has recently started to enable visual access to cultural collections, and to explore them as complex and comprehensive information spaces by the means of interactive visualizations. In contrast to conventional web interfaces, we witness a widening spectrum of innovative visualization types specially designed for rich collections from the cultural heritage sector. This new class of information visualizations gives rise to a notable diversity of interaction and representation techniques while lending currency and urgency to a discussion about principles such as serendipity, generosity, and criticality in connection with visualization design. With this survey, we review information visualization approaches to digital cultural heritage collections and reflect on the state of the art in techniques and design choices. We contextualize our survey with humanist perspectives on the field and point out opportunities for future research.

Debating Technology for Dialogical Argument

Debating technologies, a newly emerging strand of research into computational technologies to support human debating, offer a powerful way of providing naturalistic, dialogue-based interaction with complex information spaces. The full potential of debating technologies for dialogical argument can, however, only be realized once key technical and engineering challenges are overcome, namely data structure, data availability, and interoperability between components. Our aim in this article is to show that the Argument Web, a vision for integrated, reusable, semantically rich resources connecting views, opinions, arguments, and debates online, offers a solution to these challenges. Through the use of a running example taken from the domain of citizen dialogue, we demonstrate for the first time that different Argument Web components focusing on sensemaking, engagement, and analytics can work in concert as a suite of debating technologies for rich, complex, dialogical argument.

Re(a)d wedding: A case study exploring everyday information behaviors of the transmedia fan

ABSTRACTAs practitioners of new forms of consumption and production, fans represent an important area for research. Specifically, fans of “transmedia systems” – media‐hopping networks of intertextualities that extend the narrative world of an original production – employ unique tactics for negotiating a complex information space. The study of such tactics provides valuable insights on the everyday information behaviors of modern post‐digital readers and media consumers that could benefit literacy and community engagement. Despite this, fans have received little attention in the information behavior literature. Therefore, this paper seeks to contribute new empirical understandings of the transmedia fan to the information behavior domain. The author undertook a pilot case study of the Game of Thrones transmedia fandom. Using a grounded theory approach, the qualitative coding of 400 online user comments revealed four types of tactics employed by fans to negotiate the transmedia system: sentimental, reasoned, relational and comic. A discussion of these tactics and the ways in which fans use them results in a preliminary definition and information behavior cycle model for the transmedia fan. The study's findings offer key observations about the everyday information behavior of fans and about reading and media consumption practices in general.

Supporting Sensemaking of Complex Objects with Visualizations: Visibility and Complementarity of Interactions

Making sense of complex objects is difficult, and typically requires the use of external representations to support cognitive demands while reasoning about the objects. Visualizations are one type of external representation that can be used to support sensemaking activities. In this paper, we investigate the role of two design strategies in making the interactive features of visualizations more supportive of users’ exploratory needs when trying to make sense of complex objects. These two strategies are visibility and complementarity of interactions. We employ a theoretical framework concerned with human–information interaction and complex cognitive activities to inform, contextualize, and interpret the effects of the design strategies. The two strategies are incorporated in the design of Polyvise, a visualization tool that supports making sense of complex four-dimensional geometric objects. A mixed-methods study was conducted to evaluate the design strategies and the overall usability of Polyvise. We report the findings of the study, discuss some implications for the design of visualization tools that support sensemaking of complex objects, and propose five design guidelines. We anticipate that our results are transferrable to other contexts, and that these two design strategies can be used broadly in visualization tools intended to support activities with complex objects and information spaces.

Discourses and Disciplines in the Enlightenment: Topic Modeling the French Encyclopédie

This paper describes the use of Latent Dirichlet Allocation (LDA), or topic modeling, to explore the discursive makeup of the18th-century Encyclopedie of Denis Diderot and Jean le Rond d’Alembert (1751-1772). Expanding upon previous work modeling the Encyclopedie’s ontology, or classification scheme, we examine the abstractions used by its editors to visualize the various ‘systems’ of knowledge that the work proposes, considered here as heuristic tools for navigating the complex information space of the Encyclopedie. Using these earlier experiments with supervised machine learning models as a point of reference, we introduce the notion of topic modeling as a ‘discourse analysis tool’ for Enlightenment studies. In so doing, we draw upon the tradition of post-structuralist French discourse analysis, one of the first fields to embrace computational approaches to discursive text analysis. Our particular use of LDA is thus aimed primarily at uncovering inter-disciplinary ‘discourses’ in the Encyclopedie that run alongside, under, above, and through the original classifications. By mapping these discourses and discursive practices we can begin to move beyond the organizational (and physical) limitations of the print edition, suggesting several possible avenues of future research. These experiments thus attest once again to the enduring relevance of the Encyclopedie as an exemplary Enlightenment text. Its rich dialogical structure, whether studied using traditional methods of close reading or through the algorithmic processes described in this paper, is perhaps only now coming fully to light thanks to recent developments in digital resources and methods.

Mapping Chemical Selection Pathways for Designing Multicomponent Alloys: an informatics framework for materials design.

A data driven methodology is developed for tracking the collective influence of the multiple attributes of alloying elements on both thermodynamic and mechanical properties of metal alloys. Cobalt-based superalloys are used as a template to demonstrate the approach. By mapping the high dimensional nature of the systematics of elemental data embedded in the periodic table into the form of a network graph, one can guide targeted first principles calculations that identify the influence of specific elements on phase stability, crystal structure and elastic properties. This provides a fundamentally new means to rapidly identify new stable alloy chemistries with enhanced high temperature properties. The resulting visualization scheme exhibits the grouping and proximity of elements based on their impact on the properties of intermetallic alloys. Unlike the periodic table however, the distance between neighboring elements uncovers relationships in a complex high dimensional information space that would not have been easily seen otherwise. The predictions of the methodology are found to be consistent with reported experimental and theoretical studies. The informatics based methodology presented in this study can be generalized to a framework for data analysis and knowledge discovery that can be applied to many material systems and recreated for different design objectives.

Visualizations in Time for a New Look at the Movies

Movies are considered an important art form, a source of entertainment, and a powerful method for educating, having great power to affect us, perceptually, cognitively, and emotionally. A huge amount of movies and related information are becoming increasingly available due to technological advances, demanding new and more powerful ways to search, browse, and view this interesting but complex information space that changes over time. Time-oriented visualization can help to capture, express, understand, and effectively navigate movies over time: both the time when they were released, or viewed, and the time along which their contents are weaved, in each movie. This paper presents the design and evaluation of the authors' work towards the inclusion of the time dimension in 2D and 3D visualizations, based on colors and tag clouds, at the movies space level, and down to the individual movies in an interactive Web application to access, explore, and visualize movies based on the information conveyed in the different tracks or perspectives of its content, especially audio and subtitles where most of the semantics is expressed. Moreover, it is the authors' aim to help provide insights through analytical, ludic, or artistic uses, since it is the aim of these visualizations to provide non-usual kinds of search, whether the user wants a movie to watch or to be aware of the properties in its content. The authors tested the pertinence and effectiveness of the main visualizations, and the results provided a better understanding of what is more effective and appreciated, and encouraged them to continue extending and refining their work.

Teacher Personal information management (PIM) practices: Finding, keeping, and Re‐Finding information

Primary and secondary (K–12) teachers form the essential core of children's formal learning before adulthood. Even though teaching is a mainstream, information‐rich profession, teachers are understudied as information users. More specifically, not much is known about teacher personal information management (PIM). Teacher PIM is critically important, as teachers navigate a complex information space complicated by the duality of digital and physical information streams and changing demands on instruction. Our research study increases understanding of teacher PIM and informs the development of tools to support educators. Some important unknowns exist about teachers as information users: What are teachers' PIM practices? What are the perceived consequences of these practices for teaching and learning? How can PIM practices be facilitated to benefit teaching and learning? This study employed a qualitative research design, with interviews from 24 primary and secondary teachers. We observed various systems for information organization, and teachers report their systems to be effective. Important sources for teachers' information in order of importance are personal collections, close colleagues, and the Internet. Key findings reveal that inheriting and sharing information play an important part in information acquisition for teachers and that information technology supporting education creates unintentional demands on information management. The findings on the nature of teacher information, teacher information finding, keeping, and organizational practices have important implications for teachers themselves, school principals, digital library developers, school librarians, curriculum developers, educational technology developers, and educational policy makers.

Tangible displays for the masses: spatial interaction with handheld displays by using consumer depth cameras

Spatially aware handheld displays are a promising approach to interact with complex information spaces in a more natural way by extending the interaction space from the 2D surface to the 3D physical space around them. This is achieved by utilizing their spatial position and orientation for interaction purposes. Technical solutions for spatially tracked displays already exist in research laboratories, e.g., embedded in a tabletop environment. Along with a large stationary screen, such multi-display systems provide a rich design space with a variety of benefits to users, e.g., the explicit support of co-located parallel work and collaboration. As we see a great future in the underlying interaction principles, the question is how the technology can be made accessible to the public. With our work, we want to address this issue. In the long term, we envision a low-cost tangible display ecosystem that is suitable for everyday usage and supports both active displays (e.g., the iPad) and passive projection media (e.g., paper screens and everyday objects such as a mug). The two major contributions of this article are a presentation of an exciting design space and a requirement analysis regarding its technical realization with special focus on a broad adoption by the public. In addition, we present a proof of concept system that addresses one technical aspect of this ecosystem: the spatial tracking of tangible displays with a consumer depth camera (Kinect).

Breaking the barriers of time and space: the dawning of the great age of librarians

This lecture, reflecting on future roles, posits the potential dawning of a "great age of librarians," if librarians make the conceptual shift of focusing on their own skills and activities rather than on their libraries. In the digital age, physical libraries are becoming less relevant to the communities that they serve. Librarians, however, are more necessary than ever in helping members of their communities navigate the increasingly complex information space. To meet their social responsibilities requires that librarians seek new roles and recognize that their most important activities will take place outside of the physical library. A great age of librarians is possible, but not guaranteed. We are at the very beginning of the development of a digital culture that parallels the print culture that has been dominant for five hundred years. Innovative and creative librarians have the potential to shape the development of that culture in ways that will truly serve the needs of their communities.

Visualizing explicit and implicit relations of complex information spaces

In this work, we describe how EdgeMaps provide a new method for integrating the visualization of explicit and implicit data relations. Explicit relations are specific connections between entities already present in a given data set, while implicit relations are derived from multidimensional data based on similarity measures. Many data sets include both types of relations, which are often difficult to represent together in information visualizations. Node-link diagrams typically focus on explicit data connections while not incorporating implicit similarities between entities. Multidimensional scaling considers similarities between items; however, explicit links between nodes are not displayed. In contrast, EdgeMaps visualize both explicit and implicit relations by combining graph drawing and spatiatization techniques. We have applied this technique to three case studies [philosophers, painters, and musicians] and explored how integrated visualizations of explicit and implicit relations reveal novel patterns and relationships.

Recommender Systems: An Overview

Recommender systems are tools for interacting with large and complex information spaces. They provide a personalized view of such spaces, prioritizing items likely to be of interest to the user. The field, christened in 1995, has grown enormously in the variety of problems addressed and techniques employed, as well as in its practical applications. Recommender systems research has incorporated a wide variety of artificial intelligence techniques including machine learning, data mining, user modeling, case‐based reasoning, and constraint satisfaction, among others. Personalized recommendations are an important part of many online e‐commerce applications such as Amazon.com, Netflix, and Pandora. This wealth of practical application experience has provided inspiration to researchers to extend the reach of recommender systems into new and challenging areas. The purpose of the articles in this special issue is to take stock of the current landscape of recommender systems research and identify directions the field is now taking. This article provides an overview of the current state of the field and introduces the various articles in the special issue.

W3P: Building an OPM based provenance model for the Web

The Web is evolving into a complex information space where the unprecedented volume of documents and data will offer to the information consumer a level of information integration and aggregation that has up until now not been possible. Indiscriminate addition of information can, however, come with inherent problems such as the provision of poor quality or fraudulent information. Provenance represents the cornerstone element which will enable information consumers to assess information quality, which will play a fundamental role in the continued evolution of the Web. This paper investigates the characteristics and requirements of provenance on the Web, describing how the Open Provenance Model (OPM) can be used as a foundation for the creation of W3P, a provenance model and ontology designed to meet the core requirements for the Web.

Telehealth on Advanced Networks

We address advanced Internet for complex telehealth applications by reviewing four hospital-based broadband telehealth projects and identifying common threads. These projects were conducted in Australia under a 6-year research project on broadband Internet applications. Each project addressed specific clinical needs and its development was guided by the clinicians involved. Each project was trialed in the field and evaluated against the initial requirements. The four projects covered remote management of a resuscitation team in a district hospital, remote guidance and interpretation of echocardiography, virtual-reality-based instructor-student surgical training, and postoperative outpatient consultations following pediatric surgery. Each was characterized by a high level of interpersonal communication, a high level of clinical expertise, and multiple participants. Each made use of multiple high-quality video and audio links and shared real-time access to clinical data. Four common threads were observed. Each application provided a high level of usability and task focus because the design and use of broadband capability was aimed directly to meet the clinicians' needs. Each used the media quality available over broadband to convey words, gestures, body movements, and facial expressions to support communication and a sense of presence among the participants. Each required a complex information space shared among the participants, including real-time access to stored patient data and real-time interactive access to the patients themselves. Finally, each application supported the social and organizational aspects of their healthcare focus, creating and maintaining relationships between the various participants, and this was done by placing the telehealth application into a wider functioning clinical context. These findings provide evidence for a significantly enhanced role for appropriate telemedicine systems running on advanced networks, in a wider range of clinical applications, more deeply integrated into healthcare systems.

Combination of Web page recommender systems

With the rapid growth of the World Wide Web (www), finding useful information from the Internet has become a critical issue. Web recommender systems help users make decisions in this complex information space where the volume of information available to them is huge. Recently, a number of Web page recommender systems have been developed to extract the user behavior from the user’s navigational path and predict the next request as s/he visits Web pages. However, each of these systems has its own merits and limitations. In this paper, we investigate a hybrid recommender system, which combines the results of several recommender techniques based on Web usage mining. We conduct a detailed comparative evaluation of how different combined methods and different recommendation techniques affect the prediction accuracy of the hybrid recommender. We then discuss the results in terms of using a hybrid recommender system instead of a single recommender model. Our results suggest that the hybrid recommender system is better in predicting the next request of a Web user.