Using ArcGIS, anyone can quickly make and share a map-but creating an effective map requires knowing a few design fundamentals. Enroll in this plan to learn techniques to appropriately symbolize and label map features, apply settings that enhance user interaction with your maps, and create impactful data visualizations that resonate with your intended audience.Goals Choose appropriate map symbols to represent your data. Create attractive labels to provide information about map features. Visualize data in 2D and 3D.

The global Sensor Data Visualization market is projected to reach a value of USD 5.6 billion by 2033, exhibiting a CAGR of 16.2% during the forecast period (2023-2033). The increasing adoption of sensors in various industries, such as industrial, medical, and research, is a primary driver of market growth. Governments' ongoing initiatives to promote sustainable development and improve energy efficiency are also fueling demand for sensor data visualization solutions. The market is segmented into two types, 2D and 3D heat maps, mesh plots, and line traces, and three applications, industrial, medical, and research. The industrial segment is anticipated to hold the largest market share during the forecast period, driven by the surge in digitization and automation in industries such as manufacturing, energy, and transportation. The medical segment is also expected to grow significantly, owing to the increasing demand for real-time monitoring and visualization of patient data in hospitals and clinics. Key players in the market include SICK, Luna Innovations, Archilogic, Ripples IOT, LORD Sensing, PPS, VivoSense, GEOKON, b-plus, Worldsensing, IQ Home, NXP Semiconductors, Visualization Sciences Group (VSG), Vista Data Vision, Ouster, Kitware, Vernier, and myDevices.

Traditionally, zoning plans have been represented on a 2D map. However, visualizing a zoning plan in 2D has several limitations, such as visualizing heights of buildings. Furthermore, a zoning plan is abstract, which for citizens can be hard to interpret. Therefore, the goal of this research is to explore how a zoning plan can be visualized in 3D and how it can be visualized it is understandable for the public. The 3D visualization of a zoning plan is applied in a case study, presented in Google Earth, and a survey is executed to verify how the respondents perceive the zoning plan from the case study. An important factor of zoning plans is interpretation, since it determines if the public is able to understand what is visualized by the zoning plan. This is challenging, since a zoning plan is abstract and consists of many detailed information and difficult terms. In the case study several techniques are used to visualize the zoning plan in 3D. The survey shows that visualizing heights in 3D gives a good impression of the maximum heights and is considered as an important advantage in comparison to 2D. The survey also made clear including existing buildings is useful, which can help that the public can recognize the area easier. Another important factor is interactivity. Interactivity can range from letting people navigate through a zoning plan area and in the case study users can click on a certain area or object in the plan and subsequently a menu pops up showing more detailed information of a certain object. The survey made clear that using a popup menu is useful, but this technique did not optimally work. Navigating in Google Earth was also being positively judged. Information intensity is also an important factor Information intensity concerns the level of detail of a 3D representation of an object. Zoning plans are generally not meant to be visualized in a high level of detail, but should be represented abstract. The survey could not implicitly point out that the zoning plan shows too much or too less detail, but it could point out that the majority of the respondents answered that the zoning plan does not show too much information. The interface used for the case study, Google Earth, has a substantial influence on the interpretation of the zoning plan. The legend in Google Earth is unclear and an explanation of the zoning plan is lacking, which is required to make the zoning plan more understandable. This research has shown that 3D can stimulate the interpretation of zoning plans, because users can get a better impression of the plan and is clearer than a current 2D zoning plan. However, the interpretation of a zoning plan, even in 3D, still is complex.

WIDEa is R-based software aiming to provide users with a range of functionalities to explore, manage, clean and analyse "big" environmental and (in/ex situ) experimental data. These functionalities are the following, 1. Loading/reading different data types: basic (called normal), temporal, infrared spectra of mid/near region (called IR) with frequency (wavenumber) used as unit (in cm-1); 2. Interactive data visualization from a multitude of graph representations: 2D/3D scatter-plot, box-plot, hist-plot, bar-plot, correlation matrix; 3. Manipulation of variables: concatenation of qualitative variables, transformation of quantitative variables by generic functions in R; 4. Application of mathematical/statistical methods; 5. Creation/management of data (named flag data) considered as atypical; 6. Study of normal distribution model results for different strategies: calibration (checking assumptions on residuals), validation (comparison between measured and fitted values). The model form can be more or less complex: mixed effects, main/interaction effects, weighted residuals.

Dataset containing supplemental material for the publication "2D, 2.5D, or 3D? An Exploratory Study on Multilayer Network Visualizations in Virtual Reality" This dataset contains: 1) archive containing all raw quantitative results, 2) archive containing all raw qualitative data, 3) archive containing the graphs used for the experiment (.graphml file format), 4) the code to generate the graph library (C++ files using OGDF), 5) a PDF document containing detailed results (with p-values and more charts), 6) a video showing the experimentation from a participant's point of view. 7) complete graph library generated by our graph generator for the experiment

Heliophysics Data-Visualization Display Market Outlook

According to our latest research, the Global Heliophysics Data-Visualization Display market size was valued at $1.2 billion in 2024 and is projected to reach $3.4 billion by 2033, expanding at a CAGR of 12.1% during 2024–2033. The growing complexity and volume of heliophysical data, driven by advanced satellite missions and increased solar observation initiatives, are major factors propelling the global adoption of sophisticated data-visualization display solutions. These technologies are enabling researchers, government agencies, and commercial enterprises to derive actionable insights from vast datasets, enhancing the understanding of solar-terrestrial interactions and their impact on space weather, navigation, and communication systems. As the demand for real-time, interactive, and high-fidelity visualizations rises, the market is experiencing robust growth across both developed and emerging economies.

Regional Outlook

North America currently holds the largest share of the heliophysics data-visualization display market, commanding over 40% of the global revenue in 2024. This dominance is attributed to the region's mature technological ecosystem, significant investments in space research, and the presence of leading space agencies such as NASA and NOAA. These agencies have pioneered the deployment of advanced visualization platforms for solar observation and space weather monitoring, fostering collaborations with top-tier research institutes and commercial enterprises. The robust policy framework supporting space science, coupled with a high concentration of skilled professionals and R&D facilities, has further cemented North America's leadership. Additionally, the region's early adoption of cloud-based and interactive visualization tools has accelerated market growth, positioning it as a benchmark for innovation and capability in heliophysics data analysis.

Asia Pacific emerges as the fastest-growing region, projected to register a CAGR of 15.7% through 2033. This rapid expansion is fueled by substantial investments in national space programs, particularly in China, India, and Japan, which are launching new solar observation missions and enhancing their data-processing infrastructure. The region's governments are increasingly recognizing the strategic importance of space weather monitoring for telecommunications, navigation, and energy sectors. Academic and research institutions are also ramping up collaborations with international bodies, driving demand for state-of-the-art visualization solutions. The proliferation of cloud-based deployment models and the rising focus on STEM education are further catalyzing market penetration, as local vendors and global players target the region's vast untapped potential.

Emerging economies in Latin America, the Middle East, and Africa are gradually integrating heliophysics data-visualization technologies, albeit at a slower pace due to infrastructural and policy challenges. Limited access to cutting-edge hardware, insufficient funding for space research, and a lack of specialized talent are key barriers to widespread adoption. However, localized demand is growing as governments seek to improve disaster management, climate monitoring, and educational outreach. International partnerships and technology transfer initiatives are beginning to address these gaps, enabling gradual market entry. The adoption trajectory in these regions will depend heavily on regulatory reforms, public-private collaborations, and targeted investments in research capacity and digital infrastructure.

Report Scope

Abstract Technical graphic representation presents problems concerning the reduction of dimensionality from 3D to 2D. AEC (architecture, engineering and construction) projects usually adopt the top view paradigm with two-dimensional orthogonal projection. Recently, three major changes in technical representation were the alteration of orthogonal projection into a three-dimensional perspective view, inclusion of oriented object programing as in BIM (Building Information Model) and the interactions with AR (augmented reality). In this context, the present research evaluates the proposal of symbology based on color Hue as done in Cartography and the impact of three-dimensionality of the symbol in the identification of incompatibilities in a project of a residential building. An application of the visual variable color hue was proposed improve readability to representations and evaluations were performed with expert users, using representations in CAD 2D, BIM and AR in top and perspective views. Results indicate the color hue improve the cognitive process of read, interpret and find incompatibilities in civil projects, while the change of point of view contribute to interaction and manipulation in virtual environments. Both shows significance higher than 6% in ANOVA tests.

Discover how to display and symbolize both 2D and 3D data. Search, access, and create new map symbols. Learn to specify and configure text symbols for your map. Complete your map by creating an effective layout to display and distribute your work.

Recent advances in Computer Science and the spread of internet connection have allowed specialists to virtualize complex environments on the web and offer further information with realistic exploration experiences. At the same time, the fruition of complex geospatial datasets (point clouds, Building Information Modelling (BIM) models, 2D and 3D models) on the web is still a challenge, because usually it involves the usage of different proprietary software solutions, and the input data need further simplification for computational effort reduction. Moreover, integrating geospatial datasets acquired in different ways with various sensors remains a challenge. An interesting question, in that respect, is how to integrate 3D information in a 3D GIS (Geographic Information System) environment and manage different scales of information in the same application. Integrating a multiscale level of information is currently the first step when it comes to digital twinning. It is needed to properly manage complex urban datasets in digital twins related to the management of the buildings (cadastral management, prevention of natural and anthropogenic hazards, structure monitoring, etc.). Therefore, the current research shows the development of a freely accessible 3D Web navigation model based on open-source technology that allows the visualization of heterogeneous complex geospatial datasets in the same virtual environment. This solution employs JavaScript libraries based on WebGL technology. The model is accessible through web browsers and does not need software installation from the user side. The case study is the new building of the University of Twente-Faculty of Geo-Information (ITC), located in Enschede (the Netherlands). The developed solution allows switching between heterogeneous datasets (point clouds, BIM, 2D and 3D models) at different scales and visualization (indoor first-person navigation, outdoor navigation, urban navigation). This solution could be employed by governmental stakeholders or the private sector to remotely visualize complex datasets on the web in a unique visualization, and take decisions only based on open-source solutions. Furthermore, this system can incorporate underground data or real-time sensor data from the IoT (Internet of Things) for digital twinning tasks.

A high amount of published information on paper is contained in visualizations such as 2D and or 3D plots. Supporting a generic research workflow, plotID provides tools that can a) create and anchor a reference (ID code, URL,...) for and b) package figures, data, code and parameters used to create the figure. The code is provided as tools with small footprint, that need to be used consciously by the researcher and does not aim to relieve the researcher of his duty to keep his digital working environment organized. The exported packages help to make results reusable and repeatable.

Subsurface Data Visualization Market Outlook

According to our latest research, the global Subsurface Data Visualization market size reached USD 2.84 billion in 2024, and is expected to grow at a robust CAGR of 13.2% from 2025 to 2033. By the end of the forecast period, the market is projected to achieve a value of USD 8.38 billion. This impressive growth is primarily driven by the increasing demand for advanced visualization technologies in sectors such as oil & gas, mining, and environmental sciences, where accurate interpretation of subsurface data is crucial for operational efficiency and risk mitigation. As per our latest research, technological advancements, coupled with the rising adoption of cloud-based solutions and immersive visualization platforms, are further propelling the market forward.

A significant growth driver for the Subsurface Data Visualization market is the escalating complexity of subsurface data generated by modern exploration and monitoring technologies. With the proliferation of sensors and high-resolution imaging tools, industries like oil & gas and mining are now producing vast volumes of multidimensional data that require sophisticated visualization solutions for effective analysis. The ability to transform raw data into actionable insights through intuitive 2D and 3D models has become indispensable, enabling organizations to make informed decisions, optimize resource allocation, and minimize operational risks. This trend is further accentuated by the integration of artificial intelligence and machine learning algorithms, which enhance the analytical capabilities of visualization platforms, making them more adaptive and predictive.

Another key factor fueling the growth of the Subsurface Data Visualization market is the rapid adoption of cloud-based deployment models. Cloud solutions offer unparalleled scalability, flexibility, and cost-efficiency, allowing organizations to access advanced visualization tools without the need for significant upfront investments in hardware or infrastructure. This has democratized access to powerful analytics and visualization capabilities, particularly for small and medium enterprises (SMEs) and research institutions that previously faced budgetary constraints. In addition, the cloud facilitates seamless collaboration among geographically dispersed teams, accelerating project timelines and fostering innovation in subsurface data interpretation.

The emergence of immersive technologies such as virtual reality (VR) and augmented reality (AR) is also reshaping the Subsurface Data Visualization market. These cutting-edge visualization types enable users to interact with subsurface models in a highly intuitive and immersive manner, enhancing understanding and communication among stakeholders. For example, VR and AR solutions are increasingly being used in training, simulation, and remote operations, reducing the need for physical presence in hazardous environments. This not only improves safety but also enhances the efficiency of exploration, drilling, and monitoring activities across various sectors, thereby driving market growth.

Regionally, North America continues to dominate the Subsurface Data Visualization market due to its strong presence of leading technology providers, high investments in research and development, and advanced infrastructure in industries such as oil & gas and environmental science. However, the Asia Pacific region is witnessing the fastest growth, driven by increasing exploration activities, rapid industrialization, and government initiatives aimed at sustainable resource management. Europe also holds a significant share, supported by stringent environmental regulations and the adoption of innovative technologies in mining and construction. The Middle East & Africa and Latin America are emerging as promising markets, fueled by expanding energy and mining sectors and growing awareness of the benefits of advanced data visualization.

Component Analysis

The Subsurface Data Visualization market is segmented by component into software, hardware, and services. The software segment holds the largest share, accounting for over 50% of the total market revenue in 2024. This dominance is attributed to the continuous innovation in visualization algorithms, user interfaces, and integration capabilities with other data management and analytics platforms. Modern software solutions offer comprehensive toolsets for data p

In this paper, we present a transfer function-based approach to developing an interactive visualization algorithm for ocean mesoscale eddies. Spatiotemporal coherence and viewport coherence are achieved. Evenly spaced streamlines are only integrated for visible portions of the datasets that maintain a relatively stable visual pattern resolution. The interactive transfer function is introduced to extract 2D and 3D eddy features, such as the Okubo-Weiss parameter, from background ocean currents, and a highly efficient GPU-based framework with an output-sensitive performance is utilized. Using the high-resolution 2D/3D ocean current datasets Maps of Sea Level Anomalies (MSLA) and Hybrid Coordinate Ocean Model (HYCOM), the feasibility and efficiency of our framework are demonstrated.

Presentation Date: Wednesday, July 20, 2022. Location: Institut Pascal, Paris, France. Abstract: A talk at the 2022 Interstellar Institute on why 2D <--> 3D transformations, and paying attention to the dimensionality of data and display modes for it is so important in understanding the nature of the local interstellar medium.

Effective spatial visualization and reasoning skills are often credited for students’ success in science and engineering courses. However, students enrolled in these science courses are not always exposed to or trained properly on the best ways to utilize models to aid in their learning. Improving spatial visualization techniques with 3D models, such as molecular and DNA modeling kits, is often suggested to facilitate students’ ability to conceptualize compounds in two and three dimensions. Here, we investigate what techniques students use to conceptualize 2D representations of various biomolecules with the use of 3D models by interviewing undergraduate students from various natural science and engineering disciplines in task-based, think-aloud sessions. After scoring and analyzing the participant data we explored some of the techniques used among successful scoring participants, including the use of informal models to transition between 2D and 3D. Additional techniques used by students who were able to successfully conceptualize 3D images included starting with smaller, granular details to inductively make conclusions when thinking between two and three dimensions. We find that (1) students who anchor their thinking in 3D models show a deeper level of understanding in initially solving science problems successfully, and (2) proper 3D model use and spatial visualization techniques may improve students’ abilities to accurately visualize 2D and 3D representations of molecules in science courses. Our results demonstrate that implementing spatial visualization training to teach students how to effectively use 3D models may improve students’ problem-solving techniques in science curricula.

The global data visualization market, currently valued at $9.84 billion (2025), is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 10.95% from 2025 to 2033. This expansion is fueled by several key drivers. The increasing volume and complexity of data generated across various sectors necessitate efficient tools for analysis and interpretation. Businesses are increasingly recognizing the importance of data-driven decision-making, leading to significant investments in data visualization solutions. Furthermore, the rising adoption of cloud-based platforms and the growing demand for advanced analytical capabilities, such as predictive analytics and machine learning integration within visualization tools, are significantly contributing to market growth. The market is segmented by organizational department (Executive Management, Marketing, Operations, Finance, Sales, Other), deployment mode (On-premise, Cloud/On-demand), and end-user industry (BFSI, IT & Telecommunication, Retail/E-commerce, Education, Manufacturing, Government, Other). The competitive landscape is characterized by a mix of established players like Salesforce (Tableau), SAP, Microsoft, and Oracle, and smaller, specialized vendors. The competitive intensity is likely to remain high, with vendors focusing on innovation, strategic partnerships, and expanding their product portfolios to cater to specific industry needs. The North American market currently holds a significant share, driven by early adoption of advanced technologies and a robust IT infrastructure. However, the Asia-Pacific region is anticipated to witness the fastest growth due to increasing digitalization across various sectors and rising demand for data-driven insights in rapidly developing economies. While the on-premise deployment model still holds a considerable market share, the cloud/on-demand model is gaining traction owing to its scalability, cost-effectiveness, and accessibility. Factors such as data security concerns, integration complexities, and the need for specialized skills could act as potential restraints on market growth. However, ongoing technological advancements, coupled with increasing awareness of data visualization benefits, are expected to mitigate these challenges and drive market expansion in the coming years. Recent developments include: September 2022: KPI 360, an AI-driven solution that uses real-time data monitoring and prediction to assist manufacturing organizations in seeing various operational data sources through a single, comprehensive industrial intelligence dashboard that sets up in hours, was recently unveiled by SymphonyAI Industrial., January 2022: The most recent version of the IVAAP platform for ubiquitous subsurface visualization and analytics applications was released by INT, a top supplier of data visualization software. IVAAP allows exploring, visualizing, and computing energy data by providing full OSDU Data Platform compatibility. With the new edition, IVAAP's map-based search, data discovery, and data selection are expanded to include 3D seismic volume intersection, 2D seismic overlays, reservoir, and base map widgets for cloud-based visualization of all forms of energy data.. Key drivers for this market are: Cloud Deployment of Data Visualization Solutions, Increasing Need for Quick Decision Making. Potential restraints include: Cloud Deployment of Data Visualization Solutions, Increasing Need for Quick Decision Making. Notable trends are: Retail Segment to Witness Significant Growth.

Data (trench) include XYZ- coordinate (column 1-3) and intensity information (column 4)

Although modern fluorescence microscopy produces detailed three-dimensional (3D) datasets, colocalization analysis and region of interest (ROI) selection is most commonly performed two-dimensionally (2D) using maximum intensity projections (MIP). However, these 2D projections exclude much of the available data. Furthermore, 2D ROI selections cannot adequately select complex 3D structures which may inadvertently lead to either the exclusion of relevant or the inclusion of irrelevant data points, consequently affecting the accuracy of the colocalization analysis. Using a virtual reality (VR) enabled system, we demonstrate that 3D visualization, sample interrogation and analysis can be achieved in a highly controlled and precise manner. We calculate several key colocalization metrics using both 2D and 3D derived super-resolved structured illumination-based data sets. Using a neuronal injury model, we investigate the change in colocalization between Tau and acetylated α-tubulin at control conditions, after 6 hours and again after 24 hours. We demonstrate that performing colocalization analysis in 3D enhances its sensitivity, leading to a greater number of statistically significant differences than could be established when using 2D methods. Moreover, by carefully delimiting the 3D structures under analysis using the 3D VR system, we were able to reveal a time dependent loss in colocalization between the Tau and microtubule network as an early event in neuronal injury. This behavior could not be reliably detected using a 2D based projection. We conclude that, using 3D colocalization analysis, biologically relevant samples can be interrogated and assessed with greater precision, thereby better exploiting the potential of fluorescence-based image analysis in biomedical research.