Towards a Framework and a Model for Knowledge Visualization: Synergies Between Information and Knowledge Visualization

Author(s):  
Remo Aslak Burkhard
2014 ◽  
Vol 27 (2) ◽  
pp. 197-227 ◽  
Author(s):  
Demosthenes Akoumianakis

Purpose – The purpose of this paper is to investigate boundary spanning tactics in a cross-organizational virtual alliance and discuss the analytical value of “digging” into technology for excavating boundaries and understanding their dynamic and emergent features. Design/methodology/approach – Although boundaries, their role and implications have been extensively investigated across a variety of online settings, the results are inconclusive as to the features of technology that create, dissolve or re-locate boundaries. This is attributed to the fact that in most cases technology is addressed as a black box – a discrete artefact of practice – without seeking justification for the inscribed functions that enable or constrain use. The paper overcomes these shortcomings by analysing digital trace data compiled through a virtual ethnographic assessment of a cross-organizational tourism alliance. Data comprise electronic traces of online collaboration whose interpretive capacity is augmented using knowledge visualization techniques capable of revealing dynamic and emergent features of boundary spanning. Findings – Boundary spanning in virtual settings entails micro-negotiations around several types of boundaries. Some of them are either enforced by or inscribed into technology, while others are enacted in practice. Knowledge visualization of digital trace data allows “excavation” of these boundaries, assessment of their implications on distributed organizing of online ensembles and discovery of “hidden” knowledge that drives boundary spanning tactics of collaborators. Practical implications – In cross-organizational collaborative settings, boundary spanning represents an enacted capability stemming from the intertwining between material and social/collective agencies. Consequently, boundaries surface as first class design constructs, directing design attention not only to features inscribed in technology (i.e. user profiles, registration mechanisms, moderation policies) but also the way such features are appropriated to re-shape, re-locate or dissolve boundaries. Originality/value – An empirical data pool compiled through virtual ethnographic assessment of online collaboration is revisited and augmented with knowledge visualization techniques that enhance the interpretive capacity of the data and reveal “hidden” aspects of the collaborators’ boundary spanning behaviour and tactics.


Themes and examples examined in this chapter discuss the fast growing field of visualization. First, basic terms: data, information, knowledge, dimensions, and variables are discussed before going into the visualization issues. The next part of the text overviews some of the basics in visualization techniques: data-, information-, and knowledge-visualization, and tells about tools and techniques used in visualization such as data mining, clusters and biclustering, concept mapping, knowledge maps, network visualization, Web-search result visualization, open source intelligence, visualization of the Semantic Web, visual analytics, and tag cloud visualization. This is followed by some remarks on music visualization. The next part of the chapter is about the meaning and the role of visualization in various kinds of presentations. Discussion relates to concept visualization in visual learning, visualization in education, collaborative visualization, professions that employ visualization skills, and well-known examples of visualization that progress science. Comments on cultural heritage knowledge visualization conclude the chapter.


Metaphors are present in our thoughts and make invisible concepts perceivable. The metaphorical way of perceptual imaging is discussed in this chapter, particularly the use of art and graphic metaphors for concept visualization. We may describe with metaphors the structure and the relations among several kinds of data. Metaphors may represent mathematical equations or geometrical curves and thus make abstract ideas visible. Most metaphors originate from biology-inspired thinking. Nature-derived metaphors support data visualization, information and knowledge visualization, data mining, Semantic Web, swarm computing, cloud computing, and serve as the enrichment of interdisciplinary models. This chapter examines examples of combining metaphorical visualization with artistic principles, and then describes the metaphorical way of learning and teaching with art and graphic metaphors aimed at improving one’s power of conveying meaning, integrating art and science, and visualizing knowledge.


Author(s):  
Demosthenes Akoumianakis ◽  
Giannis Milolidakis ◽  
George Vlachakis ◽  
Nikolas Karadimitriou ◽  
Giorgos Ktistakis

The present work rests and elaborates on the assumption that social technologies are increasingly turned into computer-mediated virtual settlements, thereby allowing the excavation of a variety of enacted cyber-phenomena such as ad hoc online ensembles, informal social networks and virtual communities, on the grounds of “digital” traces or remains. In this vein, the authors motivate and present a method for virtual excavations that is tightly coupled to a transformational technology such as knowledge visualization. The analytical and explanatory value of the method is assessed using two case studies addressing representative genres of social technologies, namely web sites augmented with social plug-ins and social networking services. Analysis reveals intrinsic aspects of “digital” traces and remains, the form they take in today’s social web and the means through which they can be excavated and transformed to useful information. It turns out that such virtual excavations, when organized and conducted carefully, can be of benefit to enterprises, service organizations and public sector institutions. In addition, their tight coupling with knowledge visualization eliminates extensive data analysis as much of this work can be done using the visualization. On the other hand, and depending on the size of digital trace data, the choice of visualizations and the underlying toolkit are of paramount importance.


Author(s):  
Ricardo Morais ◽  
Ian Brailsford

This chapter presents a case of information and communication technology use in doctoral research processes. In particular, it presents the use of the Idea Puzzle software as a knowledge visualization tool for research design at the University of Auckland. The chapter begins with a review of previous contributions on knowledge visualization and research design. It then presents the Idea Puzzle software and its application at the University of Auckland. In addition, the chapter discusses the results of a large-scale survey conducted on the Idea Puzzle software in 71 higher education institutions as well as its first usability testing at the University of Auckland. The chapter concludes that the Idea Puzzle software stimulates visual integrative thinking for coherent research design in the light of Philosophy of Science.


Author(s):  
Jean Constant

3D graphics visualization is equal part mathematics, geometry, and design. Based on the knowledge visualization framework, the author investigates the structure of a mineral to find if meaningful visualization pertaining to the field of art can be extracted from scientific resource. Working with the lines, spheres, and polygons that characterize crystal at the nanoscale provided the author an exceptional environment from which to extract coherent visualizations sustainable in the art environment. The outcome was tested in a variety of interactive platforms and opened a larger debate on cross-pollination between science and arts. Additionally, the experiment provided new ground of investigation for unexpected connections between mathematics, earth sciences, and local cultures.


Author(s):  
Vytautas Čyras

Knowledge visualization (KV) and knowledge representation (KR) are distinguished, though both are knowledge management processes. Knowledge visualization is subject to humans, whereas knowledge representation – to computers. In computing, knowledge representation leverages reasoning of software agents. Thus, KR is a branch of artificial intelligence. The subject matter of KR is representation methods. They are classified into (1) knowledge level and symbol level representations; (2) procedural and declarative representations; (3) logic-based, rule-based, frame- or object-based representations (supporting inference by inheritance); and (4) semantic networks. In legal informatics, methods of legal knowledge representation (LKR) are dealt with. An essential feature of LKR is the representation of deep knowledge, which is mainly tacit. It is easily understood by professional jurists and hardly by amateurs from outside law. This knowledge comprises the teleology of law and a whole implicit framework of legal system. The paper focuses on (1) identifying key features of KV and KR in the legal domain; and (2) distinguishing between visualization, symbolization, formalisation and mind mapping.


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