Knowledge Visualization Tool Research Articles

Bridging knowledge gaps: a bibliometric analysis of non-invasive ventilation in palliative care studies

BackgroundDespite being a useful strategy for providing respiratory support to patients with advanced or terminal illnesses, non-invasive ventilation (NIV) requires in-depth investigation in several key aspects.ObjectivesThis bibliometric analysis seeks to comprehensively examine the existing research on the subject. Its goal is to uncover valuable insights that can inform the prediction trajectory of studies, guide the implementation of corrective measures, and contribute to the improvement of research networks.MethodsA comprehensive review of literature on NIV in the context of palliative care was conducted using the Web of Science core collection online database. The search utilized the key terms “non-invasive ventilation” and “palliative care” to identify the most relevant articles. All data were gathered on November 7, 2023. Relevant information from documents meeting the specified criteria was extracted, and Journal Citation Reports™ 2022 (Clarivate Analytics) served as the data source. The analysis employed literature analysis and knowledge visualization tools, specifically CiteScope (version 6.2.R4) and VOSviewer (version 1.6.20).ResultsA dataset with bibliometric findings from 192 items was analyzed. We found a consistent upward of the scientific output trend over time. Guidelines on amyotrophic lateral sclerosis management received the highest number of citations. Most documents were published in top-ranked journals. Less than one-third of the documents pertain to clinical studies, especially retrospective analyses (25%). Key topics such as “decision making”, and “communication” were less addressed.ConclusionsGiven the substantial clinical implications, further high-quality studies on this subject are recommended. Encouraging international collaborations is needed. Despite the growing volume of documents in the field, this bibliometric analysis indicates a decline in collaborative networks.

Organizing decision making process in public administration: the impact of knowledge visualization

The growing complexity of the competitive context imposes on organizations the necessary to make effective decisions in a short time. Consequently, the organization must make decisions on an ever-increasing volume of data and information to increase their competitive advantage. For this reason, the decision- making process must be supported by new tools capable of facilitating and time reduction the knowledge transfer. The public administrations are a particular and very emblematic case. Indeed, public administrations are characterized as bureaucratic organizations with lengthy, often ineffective decision-making processes. The main consequence is a loss of value for the reference community. Hence, improving decision-making in public administrations can have a direct impact on society. On this wise, knowledge visualization by transforming knowledge into different visual tools (e.g., images, tables, graphs, knowledge maps, etc.) can support the decision-making process, speeding up the knowledge transfer process. A growing field of studies is focusing on the knowledge visualization, and on tools to support the decision-making process. The knowledge visualization in complex organizations appears to be a subject that has not yet been fully explored. The objective of this study is to understand the impact that knowledge visualization has on the decision-making process in public administration. In this study the methodological approach implemented has qualitative and exploratory nature. The exploratory nature aims to build the theoretical premises regarding knowledge visualization, the use of knowledge visualization in public administration, and the operational and strategic capacity to support decision- making. The data was collected through the analysis of a case study. This study is part of knowledge management studies, with particular emphasis on knowledge. visualization. The results of this study, based on the observation of a case study, offer theoretical reflections on the impact of knowledge visualization in the decision-making processes of public administration. The managerial implications of this study offer an overview of the knowledge visualization tools used in public administration and the impact of knowledge visualization in the decision- making process.

The Landscape of Public Art Research: A Knowledge Map Analysis

This is the first article to date that employs a knowledge map analysis to provide insights into the landscape of public art research, a multidisciplinary area that is concerned with issues around the geographies of art, space, and community. This study uses bibliometric analysis and knowledge visualization tools provided by CiteSpace mapping software to review scholarly journal output on “public art” since 1964—which is the first occurrence of this term in an article indexed in the Web of Science Core Collection database covering English-language journal publications. The analysis reveals the value of bibliometric analysis for engaging data on the growth and popularity of public art as a research landscape—which is perceived as both a research field and research discourse. Accordingly, this study constructs knowledge maps, and thereby trends, of popular topics and networks of authors and institutions that have emerged in the public art research landscape. Such knowledge maps exhibit a “metageography” of cross-disciplinary connections within public art research (where these knowledge maps in themselves can be rendered as artworks, too). This study, as such, provides new reference points for scholars to position themselves in, and further deepen bibliometric investigation into, the landscape of public art research.

Soil information management and knowledge sharing in Victoria, Australia—user perspectives

AbstractFor twenty‐one years, soil information and knowledge in Victoria, Australia has been shared via the Victorian Resources Online (VRO) website. VRO has been the primary online repository for soil and landscape information generated from land resource assessment studies, field days, training workshops, and the visualization and animation of soil and landscape processes. User surveys and qualitative feedback have highlighted the value of online soil information to users, with many considering it a useful “tool of trade,” particularly those involved in agricultural research, extension, planning and education. An extensive series of “Healthy Soils” training workshops (2007–2010) focused on topics such as “soil types and structure,” “soil chemical testing,” “soil biology,” “soil erosion” and “organic matter.” Evaluation has demonstrated their usefulness and relevance, with learning outcomes achieved by >80% of overall participants, many of whom planned to make better management decisions and change management practices on‐farm. The information and knowledge generated through the series of workshops remains a valuable online resource. The development of more sophisticated knowledge visualization tools, such as animations, has broadened the potential audience for soil‐related information. Analytical profiling of VRO users in recent years has highlighted it as a source of information and knowledge for a local, national and international audience. This supports the notion that increasing access to public‐sector data and information provides significant benefits. Lessons learnt from enduring programs such as VRO can inform future information and knowledge management initiatives.

A Concept Map-Based Learning Paths Automatic Generation Algorithm for Adaptive Learning Systems

A concept map is an important knowledge visualization tool in adaptive learning systems. The weak concepts of students can be identified by analyzing the concept maps to provide learning guidance and teaching suggestions to students and teachers. However, in the current researches, it is difficult to analyze effective information from the concept maps when the number of concepts is large and the associations between concepts are complicated. It rarely reflects the learning performance of different student groups, which do not reflect the characteristics of the adaptive learning systems. A learning path automatic generation algorithm, Learning paths generation (LPG) algorithm, for adaptive learning systems is proposed. The LPG algorithm fully considers the learning performance of different student groups. The concept maps with different learning features are generated by the clustering algorithm and association rules mining, and several simplified learning paths are generated by using the topological sorting algorithm. Experiments show that the LPG algorithm has a good discrimination for the student groups and can generate different learning paths according to the students’ learning performance.

INTERACTIVE KNOWLEDGE VISUALIZATION TOOLS FOR EXHIBITION CURATION

This paper presents interactive knowledge visualization tools supporting knowledge workers in the process of curating digital content for exhibitions, showrooms, visitor centers or museums. The tools developed in the research project DKT (Digital Curation Technologies), funded by the Federal Ministry of Education and Research (BMBF), use language and knowledge technologies (such as information extraction, image recognition, classification and clustering) to automatically process digital multimedia content and then provide interactive visualizations of the results. The tools are thus not meant to replace knowledge workers but rather to support them and allow them to handle more content in a shorter span of time while maintaining or even increasing the quality of the curation process. Given this particular application scenario, the performance and accuracy of current state-of-the-art algorithms from Artificial Intelligence, though far from being perfect, is already good enough. The focus of the project work presented in this paper is on information extraction and text content.

MIND – Semantic Based Knowledge Visualization

In what has come to be known as the ‘Knowledge Era’, economy relies more than ever on knowledge-based activities. The need to capture, integrate and capitalize on knowledge within organizations, in an efficient and effective way has become crucial to maintaining a competitive edge in the market. Knowledge, Information and Data have always been of importance in human history, however, as technology advances and knowledge becomes more readily available, the requirement of providing knowledge workers with relevant knowledge inline and online to their ongoing activities has become a significant modern industrial and academic challenge. Whilst in the past the challenge was to maximize benefit retrieved from data (i.e. ERP, CRP solutions) and later from information (Business Intelligence (BI) tools) the new task is to provide equivalent knowledge solutions. This paper will present MIND, a multipurpose and user friendly, semantic analysis and knowledge visualization tool. MIND is applicable to a wide spectrum of applications, three of which will be presented in this paper, knowledge community mapping, CAD part profiling and an advanced BI application.

Quantitative Characterization of the Research Productivity of Interdisciplinary

Interdisciplinary research has been developed so quickly in recent decades and lots of research productivities have been achieved already. To trance the evolution pathway, reveal the research hotspots and obtain the fronts of interdisciplinary research as well as its development characteristics, informetric methods were employed in this study. From the Web of Science database, papers using in the topic word, like interdisciplinary related words from 1950 to 2012 were listed as the research objects. Some characteristics such as publication language, publication trend, publication contributors and knowledge basement for interdisciplinary were also analysed. Then the raw data was visualized in a number of co-citation maps through the knowledge visualization tool Citespace III to identify critical node documents during the evolutionary history of interdisciplinary research. The research hotspot and research front were carefully analysed using Citespace III's keyword clustering and burst terms detecting function. About ten key articles reflected the evolution pathway of interdisciplinary research, more than two main clusters and top twenty burst terms identified the research hotspots and research fronts. It was also found that research perspective and approach are two mainstreams words of interdisciplinary research. Interdisciplinary related keywords are current research hotpots and represent future directions of interdisciplinary development/research. In addition, interdisciplinary are research areas with some promising prospects.

Visualizing Composite Knowledge in Emergency Responses using Spatial Hypertext

Having the right information at the right time is crucial to make decisions during emergency response. To fulfill this requirement, emergency management systems must provide emergency managers with knowledge management and visualization tools. The goal is twofold: on one hand, to organize knowledge coming from different sources, mainly the emergency response plans (the formal knowledge) and the information extracted from the emergency development (the contextual knowledge), and on the other hand, to enable effective access to information. Formal and contextual knowledge sets are mostly disjoint; however, there are cases in which a formal knowledge piece may be updated with some contextual information, constituting composite knowledge. In this paper, the authors extend a knowledge framework with the notion of composite knowledge, and use spatial hypertext to visualize this type of knowledge. The authors illustrate the proposal with a case study on accessing to information during an emergency response in an underground transportation system.

Internet-based remote supervision of industrial processes using self-organizing maps

In upcoming years, the strategies for maintenance, traceability, management and operation of productive processes will demand the use of novel information and communication technologies. Supervisory systems in these new scenarios will have to be able to integrate large volumes of information and knowledge coming both from local and remote points of large processes. These systems will therefore require new tools for management and integration of information and knowledge. In this work, the authors present an internet-based remote supervision system of industrial processes that incorporates powerful data and knowledge visualization tools based on self-organizing maps (SOM). This architecture adds an intermediate layer (database) to the well-known client and server layers, that isolates the client part from the industrial process, allowing to incorporate the required data management and neural network processing tasks. Remote users have access to advanced information visualization tools based on SOM, including both static visualizations, such as component planes or distance maps, and dynamical ones, such as residuals and state trajectory, allowing the interpretation of knowledge extracted by the SOM as well as the analysis and detection of possible abnormal conditions. This architecture has been validated through the supervision of an industrial pilot plant.

Domain visualization using VxInsight® for science and technology management

AbstractWe present the application of our knowledge visualization tool, VxInsight®, to enable domain analysis for science and technology management within the enterprise. Data mining from sources of bibliographic information is used to define subsets of information relevant to a technology domain. Relationships between the individual objects (e.g., articles) are identified using citations, descriptive terms, or textual similarities. Objects are then clustered using a force‐directed placement algorithm to produce a terrain view of the many thousands of objects. A variety of features that allow exploration and manipulation of the landscapes and that give detail on demand, enable quick and powerful analysis of the resulting landscapes. Examples of domain analyses used in S&T management at Sandia are given.

Towards on-line analytical mining in large databases

Great efforts have been paid in the Intelligent Database Systems Research Lab for the research and development of efficient data mining methods and construction of on-line analytical data mining systems.Our work has been focused on the integration of data mining and OLAP technologies and the development of scalable, integrated, and multiple data mining functions. A data mining system, DBMiner, has been developed for interactive mining of multiple-level knowledge in large relational databases and data warehouses. The system implements a wide spectrum of data mining functions, including characterization, comparison, association, classification, prediction, and clustering. It also builds up a user-friendly, interactive data mining environment and a set of knowledge visualization tools. In-depth research has been performed on the efficiency and scalability of data mining methods. Moreover, the research has been extended to spatial data mining, multimedia data mining, text mining, and Web mining with several new data mining system prototypes constructed or under construction, including GeoMiner, MultiMediaMiner, and WebLogMiner.This article summarizes our research and development activities in the last several years and shares our experiences and lessons with the readers.