Abstract: The information visualization methods have been known as a tool providing the understanding of large data. The visualization of research publication collections is a special case of applying visualization methods to large data. This paper presents a survey of problems solved by means of visualization, document models and document analysis methods as well as of new approaches to visualization methods for research publication collections. Special attention is paid to the relation between the document analysis and visualization methods.

Abstract: Exponential size growth of such graphs as social networks, Internet graphs, etc. requires new approaches to their visualization. Along with node-link diagram representations, adjacency matrices and various hybrid representations are increasingly used for large graphs visualizations. This survey discusses new approaches to the visualization of large graphs using adjacency matrices and gives examples of applications where these approaches are used. We describe various types of patterns arising when adjacency matrices corresponding to modern networks are ordered, and algorithms making it possible to reveal these patterns. In particular, the use of matrix ordering methods in conjunction with algorithms looking for such graph patterns as stars, false stars, chains, near-cliques, full cliques, bipartite cores and near-bipartite cores enable users to create understandable visualizations of graphs with millions of vertices and edges. Examples of hybrid visualizations using node-link diagrams for representing sparse parts of a graph and adjacency matrices for representing dense parts are also given. The hybrid methods are used to visualize co-authorship networks, deep neural networks, to compare networks of the human brain connectivity, etc.

Abstract:

With the advent of network science, it has become possible to explore complex network systems, including social and information networks, by presenting them as graph models. The exponential growth of the total volume of scientific publications determines the relevance of the tasks of analyzing their interrelations. In network science, models and methods related to the field of so-called citation networks are being developed to solve these problems. However, network metrics are not used when analyzing publications in citation databases. The paper considers the issues of creating a decision support system for the selection of information sources based on data on the citation of scientific publications. A software package has been developed for making decisions on determining an important publication in a certain thematic area. The software package is based on a method of ranking publications by importance based on the analysis of citation networks, which allows you to identify publications that do not clearly stand out when ranking based on known bibliometric indicators or known measures of centrality of nodes in their pure form. A study and comparative analysis of software for visualization and research of all types of graphs and social networks has been conducted. Studies have been carried out confirming the effectiveness of the proposed decision support system in the selection of information sources.

Abstract: Due to the fast development of Semantic Web and its new branch of Linked Open Data, large amounts of structured information on various scientific areas become available. Digital libraries, information systems and portals based on ontologies are the most reliable sources of this information that need careful investigation in order to optimize science management. A generally accepted way to facilitate understanding of such large and complex data sets is graph visualization. This paper is devoted to newly developed visualization algorithms of co-authorship and citation networks extracted from information portals and digital libraries of the Linked Open Data cloud.

Abstract: Mass identification of a list of radio sources with the sky surveys of different ranges of the electromagnetic spectrum has undoubted interest to astronomers. Identification of the radio sources is not a straightforward procedure because of the different angular resolution, sensitivity limit, coordinate precision  of the radio catalogues, as well as due to the morphological structure of radio sources themselves.