Information Visualization Research Articles

Research on the Application of Information Visualization Design Based on the Three-level Theory of Emotions

As society progresses, environmental challenges have emerged as a central concern in modern discourse. The degradation of ecosystems has led to the endangerment and extinction of numerous plant species. Moreover, the overwhelming influx of information available to individuals often hampers their understanding of the significance of these endangered species. Conventional written narratives are frequently inadequate in fulfilling the audience’s informational needs. As a nascent medium for scientific communication, information visualization presents an innovative and effective approach for individuals to swiftly acquire and interpret data. This paper concentrates on the endangered aquatic flora within the South China Botanical Garden, grounded in a three-tiered emotional theory framework. Strategies are developed across instinctual, behavioral, and reflective dimensions. The outlined strategic goals aim to elevate design aesthetic literacy, broaden cognitive processing capability, and enhance the efficiency of information dissemination. By employing endangered aquatic plants as a focal point for design initiatives in the South China Botanical Garden and integrating it with the theoretical framework, the objective is to present information regarding these vulnerable species in a more direct, inventive, and concise manner. This methodology aspires to raise public awareness surrounding the conservation of endangered plant life.

Usability of Pseudo-Haptic Feedback for Manual Precise Manipulation of Objects in Augmented Reality

Manual precise manipulation of objects is a critical skill in daily life, and Augmented Reality (AR) is increasingly used to support such tasks. In this study, we propose a system utilizing pseudo-haptic feedback to support precise manipulation for six degrees of freedom (6DOF). Two types of AR instruction interfaces were developed: Visual Deviation Instruction Interface (VDI) and Pseudo-Haptic Instruction Interface (PHI). A user study with 18 participants compared the two instruction interfaces in terms of performance and user experience. The objective measures of performance (task completion time, deviation), and the subjective measures (system usability scale, NASA Task Load Index) were collected. Results show that both instruction interfaces effectively support manual precise manipulation, achieving position deviations under 2 mm and orientation deviations under 1°. PHI outperformed VDI in speed, mental effort, physical demand, performance, perceived workload, custom user experience elements and reduction deviations of manual precise manipulation. Finally, we discuss research limitations and future directions.

Augmentative and Alternative Communication Interventions in Critical and Acute Care With Mechanically Ventilated and Tracheostomy Patients: A Scoping Review.

Communication with nonspeaking patients is a critical challenge of person-centered care. This scoping review aimed to map the literature on augmentative and alternative communication (AAC) interventions for nonspeaking mechanically ventilated and tracheostomy patients in critical and acute care settings. Electronic database, ancestry, and forward citation searches were conducted using eligibility criteria established a priori. Data were extracted, synthesized, and summarized according to scoping review methodology. Studies were categorized by type of intervention and summarized in terms of purpose, participants, design, quality appraisal (including validity and reliability of selected efficacy measures), and efficacy. Small-to-large treatment effect sizes indicated demonstrable impact on patient health and communication efficacy with high-tech and no-tech visual interface-based interventions and systematic nurse training interventions. Treatment effects primarily pertained to dependent variables of patient anxiety, communication satisfaction, comfort, symptom self-reporting, and nursing practice changes. There is a paucity of high-quality AAC intervention research for mechanically ventilated and tracheostomy patients in critical and acute care settings. Emergent evidence suggests that select visual interface and nurse training interventions can impact efficacy of patient-provider communication and patients' overall health. https://doi.org/10.23641/asha.26506102.

SVbyEye: A visual tool to characterize structural variation among whole-genome assemblies.

We are now in the era of being able to routinely generate highly contiguous (near telomere-to-telomere) genome assemblies of human and nonhuman species. Complex structural variation and regions of rapid evolutionary turnover are being discovered for the first time. Thus, efficient and informative visualization tools are needed to evaluate and directly observe structural differences between two or more genomes. We developed SVbyEye, an open-source R package to visualize and annotate sequence-to-sequence alignments along with various functionalities to process alignments in PAF format. The tool facilitates the characterization of complex structural variants in the context of sequence homology helping resolve the mechanisms underlying their formation. SVbyEye is available at https://github.com/daewoooo/SVbyEye.

Simona: a comprehensive R package for semantic similarity analysis on bio-ontologies

BackgroundBio-ontologies are keys in structuring complex biological information for effective data integration and knowledge representation. Semantic similarity analysis on bio-ontologies quantitatively assesses the degree of similarity between biological concepts based on the semantics encoded in ontologies. It plays an important role in structured and meaningful interpretations and integration of complex data from multiple biological domains.ResultsWe present simona, a novel R package for semantic similarity analysis on general bio-ontologies. Simona implements infrastructures for ontology analysis by offering efficient data structures, fast ontology traversal methods, and elegant visualizations. Moreover, it provides a robust toolbox supporting over 70 methods for semantic similarity analysis. With simona, we conducted a benchmark against current semantic similarity methods. The results demonstrate methods are clustered based on their mathematical methodologies, thus guiding researchers in the selection of appropriate methods. Additionally, we explored annotation-based versus topology-based methods, revealing that semantic similarities solely based on ontology topology can efficiently reveal semantic similarity structures, facilitating analysis on less-studied organisms and other ontologies.ConclusionsSimona offers a versatile interface and efficient implementation for processing, visualization, and semantic similarity analysis on bio-ontologies. We believe that simona will serve as a robust tool for uncovering relationships and enhancing the interoperability of biological knowledge systems.

Use of Creative Frameworks in Health Care to Solve Data and Information Problems: Scoping Review.

Digitization is vital for data management, especially in health care. However, problems still hinder health care stakeholders in their daily work while collecting, processing, and providing health data or information. Data are missing, incorrect, cannot be collected, or information is inadequately presented. These problems can be seen as data or information problems. A proven way to elicit requirements for (software) systems is by using creative frameworks (eg, user-centered design, design thinking, lean UX [user experience], or service design) or creative methods (eg, mind mapping, storyboarding, 6 thinking hats, or interaction room). However, to what extent they are used to solve data or information-related problems in health care is unclear. The primary objective of this scoping review is to investigate the use of creative frameworks in addressing data and information problems in health care. Following JBI guidelines and the PRISMA-ScR framework, this paper analyzes selected papers, answering whether creative frameworks addressed health care data or information problems. Focusing on data problems (elicitation or collection, processing) and information problems (provision or visualization), the review examined German and English papers published between 2018 and 2022 using keywords related to "data," "design," and "user-centered." The database SCOPUS was used. Of the 898 query results, only 23 papers described a data or information problem and a creative method to solve it. These were included in the follow-up analysis and divided into different problem categories: data collection (n=7), data processing (n=1), information visualization (n=11), and mixed problems meaning data and information problem present (n=4). The analysis showed that most identified problems fall into the information visualization category. This could indicate that creative frameworks are particularly suitable for solving information or visualization problems and less for other, more abstract areas such as data problems. The results also showed that most researchers applied a creative framework after they knew what specific (data or information) problem they had (n=21). Only a minority chose a creative framework to identify a problem and realize it was a data or information problem (n=2). In response to these findings, the paper discusses the need for a new approach that addresses health care data and information challenges by promoting collaboration, iterative feedback, and user-centered development. Although the potential of creative frameworks is undisputed, applying these in solving data and information problems is a minority. To harness this potential, a suitable method needs to be developed to support health care system stakeholders. This method could be the User-Centered Data Approach.

Research on analytical customer relationship management in China: knowledge map analysis based on Citespace

With the rapid development of the social economy, customers have become the most critical resources of companies, and many companies have taken analytical customer relationship management (CRM) as the magic weapon to improve their core competitiveness. As the main driving force of global economic growth, China currently occupies an essential position in the worldwide economy. Using CiteSpace information visualization software, this paper quantitatively analyzed the relevant research of 98 Web of Science (WoS) studies and 616 Chinese papers in China National Knowledge Infrastructure (CNKI) from 2003 to 2023 regarding analytical CRM in China. The research results of analytical CRM in China draw a knowledge mapping to sort out the annual publication volume, topic, publishing institution, and keyword. It was found that Chinese scholars have focused on analytical CRM in China during the last 20 years, and it entered a relatively rapid growth period in 2013, forming a relatively complete body of knowledge. However, the overall number of publications in WoS is low, and the research field is narrow. According to the data, foreign scholars' research has certain limitations, primarily focusing on applying concepts in information technology. The layout between different research topics is scattered and the correlation is low. This paper provides a comprehensive analysis to point out the direction for researchers in the area of analytical CRM to engage in related research, provide data reference, and help to predict the future trend of this research. Future research should fully use big data and information technology and focus on analytical CRM in the network era to help Chinese companies improve their competitiveness.

Virtual Tours as Effective Complement to Building Information Models in Computer-Aided Facility Management Using Internet of Things

This study investigates the integration of Building Information Models (BIMs) and Virtual Tour (VT) environments in the Architecture, Engineering and Construction (AEC) industry, focusing on Computer-Aided Facility Management (CAFM), Computerized Maintenance Management Systems (CMMSs), and data Life-Cycle Assessment (LCA). The interconnected nature of tasks throughout a building’s life cycle increasingly demands a seamless integration of real-time monitoring, 3D models, and building data technologies. While there are numerous examples of effective links between IoT and BIMs, as well as IoT and VTs, a research gap exists concerning VT-BIM integration. This article presents a technical solution that connects BIMs and IoT data using VTs to enhance workflow efficiency and information transfer. The VT is developed upon a pilot based on the Controlled Environments for Living Lab Studies (CELLS), a unique facility designed for flexible monitoring and remote-control processes that incorporate BIMs and IoT technologies. The findings offer valuable insights into the potential of VTs to complement and connect to BIMs from a life-cycle perspective, improving the usability of digital twins for beginner users and contributing to the advancement of the AEC and CAFM industries. Our technical solution helps complete the connectivity of BIMs-VT-IoT, providing an intuitive interface (VT) for rapid data visualisation and access to dashboards, models and building databases. The practical field of application is facility management, enhancing monitoring and asset management tasks. This includes (a) sensor data monitoring, (b) remote control of connected equipment, and (c) centralised access to asset-space information bridging BIM and visual (photographic/video) data.

UniChromCD for Demultiplexing Time-Resolved Charge Detection-Mass Spectrometry Data.

Charge detection mass spectrometry (CD-MS) enables characterization of large, heterogeneous analytes through the analysis of individual ion signals. Because hundreds to thousands of scans must be acquired to produce adequate ion statistics, CD-MS generally requires long analysis times. The slow acquisition speed of CD-MS complicates efforts to couple it with time-dispersive techniques, such as chromatography and ion mobility, because it is not always possible to acquire enough scans from a single sample injection to generate sufficient ion statistics. Multiplexing methods based on Hadamard and Fourier transforms offer an attractive solution to this problem by improving the duty cycle of the separation while preserving retention/drift time information. However, integrating multiplexing with CD-MS data processing is complex. Here, we present UniChromCD, a new module in the open-source UniDec package that incorporates CD-MS time-domain data processing with demultiplexing tools. Following a detailed description of the algorithm, we demonstrate its capabilities using two multiplexed CD-MS workflows: Hadamard-transform size-exclusion chromatography and Fourier-transform ion mobility. Overall, UniChromCD provides a user-friendly interface for analysis and visualization of time-resolved CD-MS data.

AraTSum: Arabic Twitter Trend Summarization Using Topic Analysis and Extractive Algorithms

Twitter’s trending topics enable users to view the topics currently being discussed on the platform. Users can stay up to date with news, events, and conversations. However, the platform’s method of sorting tweets by time can make it hard to gather semantic information. To fully comprehend the various dimensions of trends and the diverse opinions surrounding them, users need to sift through a substantial number of results. Traditional techniques for content summarization, such as multi-document summarization, can facilitate information aggregation, categorization, and visualization of events, but there are two challenges. First, they fail to consider the topic’s polarity, which is essential to covering all aspects of the subject and incorporating less popular opinions. Second, some techniques only provide summaries at the topic level, potentially leaving out crucial dimensions that require representation in this summary. This research developed a novel summarization approach on Twitter which is known as ARAbic Trending SUMmarization (AraTSum). The proposed system generates the summary based on the extracted topics and aspects from the trend. The approach involves a topic sentiment-based technique that combines generative statistical Latent Dirichlet Allocation with a pre-trained model to automatically reflect the sentiments (negative or positive) of tweets in each topic; followed by extractive summarization algorithms in each cluster. The AraTSum was evaluated through several experiments on five different X datasets. The obtained results showed that AraTSum outperformed existing approaches on the ROUGE evaluation metric compared to state-of-the-art Twitter event summarizing algorithms. To ensure a comprehensive and accurate evaluation, three human experts were tasked with manually summarizing the utilized five datasets. The results demonstrated that the proposed AraTSum method is dependent on sentiment topical aspect analysis, and it enhances the summarization's performance.

TrafPS: A shapley-based visual analytics approach to interpret traffic

Recent achievements in deep learning (DL) have demonstrated its potential in predicting traffic flows. Such predictions are beneficial for understanding the situation and making traffic control decisions. However, most state-of-the-art DL models are considered “black boxes” with little to no transparency of the underlying mechanisms for end users. Some previous studies attempted to “open the black box” and increase the interpretability of generated predictions. However, handling complex models on large-scale spatiotemporal data and discovering salient spatial and temporal patterns that significantly influence traffic flow remain challenging. To overcome these challenges, we present TrafPS, a visual analytics approach for interpreting traffic prediction outcomes to support decision-making in traffic management and urban planning. The measurements region SHAP and trajectory SHAP are proposed to quantify the impact of flow patterns on urban traffic at different levels. Based on the task requirements from domain experts, we employed an interactive visual interface for the multi-aspect exploration and analysis of significant flow patterns. Two real-world case studies demonstrate the effectiveness of TrafPS in identifying key routes and providing decision-making support for urban planning.

A novel sensor-based digital instrument for assessment of quality of fibre extracted from banana pseudostem

Banana (Musa paradisiaca) farming generates huge quantities of biomass, all of which goes to waste due to the non-availability of suitable technology for its commercial application. The potential solution to this issue could be the conversion of pseudo-stems into valuable assets by converting them into fibres for various textile and non-textile applications. The specific characteristics of banana pseudo-stem fibre i.e. high absorptivity, breathability and biodegradability made it sustainable as well as suitable for the development of diversified products and blending with other natural fibres. However, non-uniformity in availability, obscurity of its intended uses and lack of knowledge for assessment of fibre quality posed a biggest hurdle to reach the fibre into the textile markets. Hence, a novel sensor-based digital instrument for assessing the quality parameters i.e. bundle strength and fineness along with overall grade of banana pseudo-stem fibre is presented in this research article. The developed instrument mainly consists of a fibre bundle strength measurement unit, fineness measuring unit and visual interface cum data acquisition unit. Test results indicated that bundle strength and fineness measured by developed instrument varied from 20.92 g/tex to 28.31 g/tex and 5.63 tex to 6.41 tex respectively. Furthermore, a good correlation between the measured and actual outputs of bundle strength (One-Way ANOVA, F28,2 = 3.914, P = 0.224), fineness (One-Way ANOVA, F51,2 = 4.730, P = 0.190) and overall quality of fibre (Independent sample T-Test, F34,1 = 0.95, P = 0.190). Was observed at 5 % level of significance. The present study also introduced a grading system for quality assessment of banana fibre based on the well-established and well-recognized grading system of jute fibre developed by Indian Standard (IS: 271 2020). The developed instrument is easy to build as well as easy to use and have an approximate cost of $1800.00. The combination of developed instrument and grading system is an accurate, feasible and time-ordered technique for the assessment of the overall quality of the banana fibre and well suited for the actual conditions.

Application and Development of Firefighting Technologies in Industrial Heritage: Experiences and Insights from Macau

Due to the irreversible nature of the consequences of fire, fire protection is a major challenge and source of problems for all types of built heritage. This study aims to establish sustainable fire protection technology strategies by generalizing fire prevention and control technologies and measures against extended burns. This study aims to explore Macau’s industrial heritage’s historical development and technological applications in the field of fire protection using literature analysis, field investigation, and spatial information visualization methods. It will be carried out using the industrial heritage of Macau as the object and systematic analyses from the screening and processing of fire protection historical data, fire risk assessment, and the migration of fire protection focus. The results show that (1) the fire protection of the industrial heritage of Macau has gone through a total of three phases: passive fire protection, transition of fire protection methods, and active fire protection, and the relied-upon fire protection technologies have been iterated and renewed continuously during this period. (2) When the fire load factors of industrial heritage increase, the fire vulnerability assessment substantially changes, and the center of gravity of heritage fire protection shifts from controlling the scope of disaster to reducing the fire risk. (3) The construction of a suitable and effective ecological model of fire protection technology can provide appropriate fire protection solutions for the preservation and reuse of Macau’s industrial heritage in a complex cultural context. Therefore, this study will help to solve the current dilemma of sustainable application and development of fire protection technology for industrial heritage. This study hopes to provide ideas and strategies for reference on industrial heritage fire protection issues in the development of similar world heritage cities.

History and future of business ecosystem: a bibliometric analysis and visualization

AbstractThe business ecosystem theory has developed rapidly in recent years and has become a hot topic in the field of business and management. However, the use of this concept is controversial. This study systematically reviewed literature published spanning nearly three decades from 1993 to 2022. In this paper, researchers designed an improved traceability method to retrieve literature based on data sources form Web of Science. VOSviewer and CiteSpace are adopted as two scientific atlas tools for information processing and visualization to evaluate the relationship between sub fields of business ecosystem. The findings show that the four branches of business ecosystem, i.e., innovation, platform, entrepreneurship and service, absorb theoretical ideas to varying degrees. Among them, the theoretical inheritance relationship of innovation branch is most clear, and gradually grows into the backbone of ecosystem research. Major contribution of this study is reflected in three aspects: Firstly, the improved traceability method provides a repeatable quantitative description process on the basis of significantly reducing researchers’ subjective participation. Secondly, from perspective of bibliometrics, the branch direction and key nodes of theory development are identified. Thirdly, the study helps identify the future development directions of business ecosystem, including innovation, digitalization, entrepreneurship, self-organization and the strategic transformation guided by emerging technologies.

Integrated deep learning model for automatic detection and classification of stenosis in coronary angiography

Coronary artery disease poses a significant threat to human health. In clinical settings, coronary angiography remains the gold standard for diagnosing coronary heart disease. A crucial aspect of this diagnosis involves detecting arterial narrowings. Categorizing these narrowings can provide insight into whether patients should receive vascular revascularization treatment. The majority of current deep learning methods for analyzing coronary angiography are mostly confined to the theoretical research domain, with limited studies offering direct practical support to clinical practitioners. This paper proposes an integrated deep-learning model for the localization and classification of narrowings in coronary angiography images. The experimentation employed 1606 coronary angiography images obtained from 132 patients, resulting in an accuracy of 88.9 %, a recall rate of 85.4 %, an F1 score of 0.871, and a MAP value of 0.875 for vascular stenosis detection. Furthermore, we developed the "Hemadostenosis" web platform (http://bioinfor.imu.edu.cn/hemadostenosis) using Django, a highly mature HTTP framework. Users are able to submit coronary angiography image data for assessment via a visual interface. Subsequently, the system sends the images to a trained convolutional neural network model to localize and categorize the narrowings. Finally, the visualized outcomes are displayed to users and are downloadable. Our proposed approach pioneers the recognition and categorization of arterial narrowings in vascular angiography, offering practical support to clinical practitioners in their learning and diagnostic processes.

The development of information and analytical competencies in the professional training of master's students in the "State and municipal management" direction

Information and analytical competencies are an integral part of the professional skills of state and municipal authorities, as they allow to effectively process and analyze large amounts of information, make informed decisions, and forecast the consequences of the actions taken. Such skills are especially relevant in the conditions of the modern information society, where access to the information has become wider and data volumes are growing every day. The development of information and analytical competencies is a necessary condition for the successful professional activity of graduates of the direction 38.04.04 “State and Municipal Management”. To form and improve these competencies in students it is necessary to use modern methods and tools for working with big data, such as data analysis, information visualization, with databases, and others. It is important to develop the critical thinking and self­control ability when working with information. Using the example of teaching the discipline “Information and analytical technologies in the state and municipal management” at the Peter the Great St. Petersburg Polytechnic University, the author proves the necessity of using B. Bloom’s taxonomy as the basis of the course methodology: thanks to the hierarchy of learning and research objectives, it is possible to effectively form information and analytical competencies and their consistent consolidation in the professional activities of master’s students.

RCDdb: A manually curated database and analysis platform for regulated cell death

Regulated cell death is a pivotal regulatory mechanism governing the development and homeostasis of multicellular organisms. A comprehensive understanding of RCD's regulatory mechanisms is crucial for developing novel therapeutic strategies against diseases associated with cell death, such as cancer and neurodegenerative diseases. However, existing data repositories support limited types of cell death data and lack comprehensive annotation and analytical functionalities. Thus, establishing an extensive cell death database is an urgent imperative. To address this gap, we developed the Regulated Cell Death Database (RCDdb, chenyclab.com/RCDdb), the first comprehensively manually annotated database designed to support annotations and analytical capabilities across all RCD types. We compiled 3090 marker gene annotations associated with 15 RCD types from 2180 relevant articles. The RCDdb includes annotation data on these marker genes concerning diseases, drugs, pathways, proteins, and gene expressions. Furthermore, it provides 49 diverse visualization methods to present this information. More importantly, the RCDdb features three online analysis tools for identifying and analyzing RCD-related features within user-submitted data. Furthermore, the RCDdb offers a user-friendly interface for querying, browsing, analysis, and visualization of detailed information associated with each RCD category. This resource promises to significantly aid researchers in better understanding the mechanisms of cell death, thereby accelerating progress in research and therapeutic strategies aimed at combating RCD-related diseases.

Design and Application Research of a UAV-Based Road Illuminance Measurement System

This paper presents a UAV-based road illumination measurement system and evaluates its performance through experiments. The system employs a HUBSAN Zino 2+ UAV, STM32F103RCT6 microcontroller, BH1750 illuminance sensor, and GPS and integrates flight, processing, measurement, cloud platform, obstacle avoidance, communication, and power supply units via the OneNET cloud platform. Both hardware and software designs were implemented, using the Z-score algorithm to handle outliers in illumination data. The system showed a single-point measurement error rate of 1.14% and a MAPE of 5.08% for multi-point measurements. In experiments, the system’s horizontal and vertical illuminance RMSE were 1.92 lx and 1.75 lx, respectively. The real-time visualization interface improved operational efficiency, cutting labor costs by half and time costs by nearly four-fifths. UAV control and monitoring from the roadside ensured safety during measurements. The system’s efficiency and wide measurement range enabled extended experiments, collecting illuminance data across multiple horizontal and vertical planes. This resulted in the creation of both horizontal and innovative vertical-plane illuminance distribution maps. These findings provide valuable data for evaluating road lighting quality, enhancing road traffic safety, and improving road illumination design.

Digital twin-driven proactive-reactive scheduling framework for port multi-equipment under a complex uncertain environment

The pervasive uncertainties in multiple port equipment scheduling frequently result in container handling delays or ineffective plans. To address the complexities and uncertainties of port multiple equipment integrated scheduling problem, this paper introduces a Digital Twin-driven (DT-driven) proactive-reactive scheduling framework for the first time. This framework is designed to promptly respond to uncertainties in the scheduling process and provide a transparent visualization of operational information. It specifically tackles the integrated scheduling problem of port quay cranes, Intelligent Guided Vehicles (IGVs), and yard cranes, considering uncertainties such as fluctuations in operating time, equipment failures, and IGV route conflicts. By developing a virtual container port simulation, which features a U-shaped port layout and double-cycling mode drawn from real-world scenarios, the paper evaluates the proposed framework's effectiveness. The experimental results demonstrate that the digital twin framework method significantly improves efficiency and conserves energy. Additionally, in large-scale conditions, the makespan difference between the DT-driven approach and the non-DT-driven approach is as much as 19.56 %. In terms of energy consumption savings, the DT-driven approach's scheduling plan can save 3.67 % of energy consumption under large-scale conditions. Moreover, as the fluctuation index increases, the energy consumption savings become even more significant. This paper also discusses the potential implications of adopting this framework for port companies, highlighting its benefits in enhancing operational and energy efficiency and its incorporation into port management systems. The sensitivity analysis can offer guidance to port companies on optimal equipment allocation strategies.

The Evaluation Purposes Visualization

Background: The article outlines the development of a visualization that aimed to represent the purpose of different evaluation theories. This visualization used a stream/river metaphor to show the evolution of different purposes (e.g. utilization, knowledge generation, accountability) of evaluation, and also highlighted the historical context that had influenced their development. The visualization shows that the end goal of all these evaluation approaches (i.e. the ocean in which the rivers flow towards) is societal improvement. Purpose: The article highlights the lessons learned and influences that led to the development of an evaluation theory categorization system. We hope that this would serve as an example (and maybe inspiration) for future efforts that aim to understand how evaluation theories have evolved and developed. Setting: Not applicable Intervention: Not applicable Research Design: Not applicable Data Collection and Analysis: Not applicable Findings: Not applicable Keywords: Evaluation theory, information visualization, evaluation historical context, organizing framework, theory development.