Visualization of individual's knowledge by analyzing the citation networks

Visual analysis of knowledge domain is an emerging field of study as science is highly dynamic and constantly evolving. Behind the scene, a knowledge domain is formed and contributed by enormous researchers' publications that describe the common subject of the domain. There is large number of significant activities have been carried out to visualize and identify the knowledge domains of research projects, groups and communities. However, the research on visualizing the knowledge structure at individual level is relative inactive. It is difficult to track down the individual's contribution to the subject and the degree of the knowledge they possess. In this paper, we are attempting to visualize the individual's knowledge structure by analyzing the citation and co-authorship relational structures. We try to analyze and map author's documents to the knowledge domains. By mapping the documents to knowledge domain, we obtain the skeleton of knowledge structure of an individual. Then, we apply the visualization technique to present the result. © 2007 IEEE

Analysis and visualization of co-authorship networks for understanding academic collaboration and knowledge domain of individual researchers

This paper proposed a new approach for collecting, analyzing and visualizing co-authoring data of individuals. This approach can be used for understanding the academic collaboration and knowledge domain of individual researchers in a past period through repetitive co-published works. Particularly we extracted the co-authoring data from the DBLP which is one of the largest on-line Computer Science bibliographic databases available on the Internet. To help users to understand the academic collaboration and knowledge domain of individuals, we developed an InterRing visualizer which shows not only the weight of co-authorship of an individual with other researchers in particular academic year, but also the knowledge domain of the individual that was covered by his/her publications published in a past period. © 2006 IEEE

Analysis and Visualization of Co-Authorship Network in Life Cycle Assessment Research Area: A case study of the International Journal of Life Cycle Assessment

This document focuses on the methods to study the collaboration patterns in co-authorship networks. As well as in other fields, no studies of collaboration patterns have been done in industrial ecology field. In this document we will collect data from scientific publications in this field for and then analyze it. Since there are a large amount of data, we will create a program for their extraction and placement in a database. Database can be used to create graphs with Gephi and statistics with Excel using the necessary data. We base our analysis on a model of undirected weighted graph to represent a collaborative network and to extract from it various network parameters. Results show that 53% of the graph forms a large cluster and the other 47% works in small communities and / or individually.Outgoin

Major Information Visualization Authors, Papers and Topics in the ACM Library

The presented work aims to identify major research topics, coauthorships, and trends in the IV Contest 2004 dataset. Co-author, paper-citation, and burst analysis were used to analyze the dataset. The results are visually presented as graphs, static Pajek [1] visualizations and interactive network layouts using Pajek’s SVG output feature. A complementary web page with all the raw data, details of the analyses, and high resolution images of all figures is available online a

An Exploration of Enterprise Architecture Research

Management of the enterprise architecture has become increasingly recognized as a crucial part of both business and IT management. Still, a common understanding and methodological consistency seems far from being developed. Acknowledging the significant role of research in moving the development process along, this article employs different bibliometric methods, complemented by an extensive qualitative interpretation of the research field, to provide a unique overview of the enterprise architecture literature. After answering our research questions about the collaboration via co-authorships, the intellectual structure of the research field and its most influential works, and the principal themes of research, we propose an agenda for future research based on the findings from the above analyses and their comparison to empirical insights from the literature. In particular, our study finds a considerable degree of co-authorship clustering and a positive impact of the extent of co-authorship on the diffusion of works on enterprise architecture. In addition, this article identifies three major research streams and shows that research to date has revolved around specific themes, while some of high practical relevance receive minor attention. Hence, the contribution of our study is manifold and offers support for researchers and practitioners alike

Analysis and Visualisation of Edge Entanglement in Multiplex Networks

Cette thèse présente une nouvelle méthodologie pour analyser des réseaux. Nous développons l'intrication d'un réseau multiplex, qui se matérialise sous forme d'une mesure d'intensité et d'homogénéité, et d'une abstraction, le réseau d'interaction des catalyseurs, auxquels sont associés des indices d'intrication. Nous présentons ensuite la mise en place d'outils spécifiques pour l'analyse visuelle des réseaux complexes qui tirent profit de cette méthodologie. Ces outils présente une vue double de deux réseaux,qui inclue une un algorithme de dessin, une interaction associant brossage d'une sélection et de multiples liens pré-attentifs. Nous terminons ce document par la présentation détaillée d'applications dans de multiples domaines.When it comes to comprehension of complex phenomena, humans need to understand what interactions lie within them.These interactions are often captured with complex networks. However, the interaction pluralism is often shallowed by traditional network models. We propose a new way to look at these phenomena through the lens of multiplex networks, in which catalysts are drivers of the interaction through substrates. To study the entanglement of a multiplex network is to study how edges intertwine, in other words, how catalysts interact. Our entanglement analysis results in a full set of new objects which completes traditional network approaches: the entanglement homogeneity and intensity of the multiplex network, and the catalyst interaction network, with for each catalyst, an entanglement index. These objects are very suitable for embedment in a visual analytics framework, to enable comprehension of a complex structure. We thus propose of visual setting with coordinated multiple views. We take advantage of mental mapping and visual linking to present simultaneous information of a multiplex network at three different levels of abstraction. We complete brushing and linking with a leapfrog interaction that mimics the back-and-forth process involved in users' comprehension. The method is validated and enriched through multiple applications including assessing group cohesion in document collections, and identification of particular associations in social networks.BORDEAUX1-Bib.electronique (335229901) / SudocSudocFranceF