Data Visualization in Applied Economics Instruction and Outreach

To assess the impact of patient health literacy, numeracy, and graph literacy on perceptions of hypertension control using different forms of data visualization. Participants (Internet sample of 1079 patients with hypertension) reviewed 12 brief vignettes describing a fictitious patient; each vignette included a graph of the patient's blood pressure (BP) data. We examined how variations in mean systolic blood pressure, BP standard deviation, and form of visualization (eg, data table, graph with raw values or smoothed values only) affected judgments about hypertension control and need for medication change. We also measured patient's health literacy, subjective and objective numeracy, and graph literacy. Judgments about hypertension data presented as a smoothed graph were significantly more positive (ie, hypertension deemed to be better controlled) then judgments about the same data presented as either a data table or an unsmoothed graph. Hypertension data viewed in tabular form was perceived more positively than graphs of the raw data. Data visualization had the greatest impact on participants with high graph literacy. Data visualization can direct patients to attend to more clinically meaningful information, thereby improving their judgments of hypertension control. However, patients with lower graph literacy may still have difficulty accessing important information from data visualizations. Addressing uncertainty inherent in the variability between BP measurements is an important consideration in visualization design. Well-designed data visualization could help to alleviate clinical uncertainty, one of the key drivers of clinical inertia and uncontrolled hypertension.

Background and Research Problem – Presentation is one of the best ways to influence other parties. For example, company is presenting the progress of performance in the form of a table or verbal data presentation; it is significant to show data by using a graphical method or other creative dashboard to have a positive impact on stockholders. Data Visualization (DV) changes crude information into numerical and pictorial dimensions that recount a story. In today’s era, several software packages are available in the market for data presentation and visualization. Every company should try to incorporate these software’s into their operation to increase efficiency but on the other hand, It is also necessary to know about these softwares’ pros and cons and use their benefits according to the company’s requirements.   Objective – To explore the Concept of DV. To know how DV is useful in the different areas of working. Identify and discuss various DV tools for the organisation.   Data Collection and Research Method – Secondary Data and fundamental research were used for the research purpose. Finding and Conclusion – Having a set of data is not sufficient for decision-making purposes. It is necessary to know the story behind data and what it says. The powerful DV platform enables business firms to present their data with actionable insights drive, valuable decision-making and improve all working performance. It becomes necessary for business firms or managers to be familiar with this software to be effective in current market trends.

Data Visualization as Documentary Form:The Murmur of Digital Magnitude Tess Takahashi (bio) In the last decade, data visualization has emerged as a form of documentary. While data visualization is not typically thought of as being in the same category as documentary film, these visually pleasing and often amusing depictions of data culled from the natural and human world pop up repeatedly on our web feeds, often over geographic maps of the world that are detached from their larger context. In other words, data visualization is a rhetorical form that visualizes a relationship between the material world and its particular form of representation. At a time when both documentary forms in the art world and popular feature-length documentaries have flourished, data visualizations have become increasingly popular and powerful forms of documentary. It goes without saying that data visualizations are primarily visual, not aural, representations. Rather than documentary cinema's authoritative voice-over or the voicings of authentic witness, data visualization is typically silent. Yet I argue that data visualization not only has a metaphorical "voice," like the voice of documentary film, but also claims to represent the literal material "voices" of others, even if those voices are seen as inarticulate, unrecognizable, or impossible—the voice of Earth, for example. This essay [End Page 376] asks how we might figure the documentary voice of data visualization as a metaphorical form that "speaks" to the eye. Further, it asks what thinking sonically about data visualization might reveal about voice and documentary. At stake here is what becomes of material embodied voices as they are absorbed into the authoritative voice of what is now our most ubiquitous documentary form: the data visualization. Today, data visualizations often draw on a wealth of "Big Data," which Steve Lohr has described as "the rising flood of digital data from many sources, including the Web, biological and industrial sensors, video, e-mail and social network communications."1 In the face of the incomprehensible scale of Big Data, data visualizations present an image that squeezes data from the big world into the instant of a glance—decades of rising sea levels, one hundred years of increasing temperatures, the extinction of species after species—by drawing on a combination of numerical measurement and photographic evidence. The most common contemporary forms of data visualization are static maps or looping, bite-size gifs, but data visualization has a longer history of attempts to make enormous amounts of data graspable in a glance. This tradition includes the work of Scottish engineer William Playfair, who in the late 1700s created the bar chart, the pie chart, and the line graph—forms that, in the words of nineteenth-century civil engineer Charles Minard, can be used to "speak to the eyes."2 At that time, the supposedly immediate form of communication offered by charts and graphs constituted "visual breakthroughs, innovations that allowed people to see patterns in data that they would otherwise have missed if they just stared at long tables of numbers."3 In more recent history, from the 1980s through the early 2000s, MIT professor Edward Tufte's three influential books on data visualization have chronicled the numerous ways that we have envisioned information over past centuries, ranging from hand-drawn hatch marks over sailors' maps to suggest the turbulence of the wind to clunky, artifact-ridden digital clouds generated by 1990s computer software.4 Today in the age of Big Data, the sophistication of data visualization tools has grown by orders of magnitude, like the sheer volume of data in the world. If the amount of data generated from the beginning of recorded time to 2003 rings in at a measly five billion gigabytes, we now generate that amount every two days.5 How might what William Davies describes as the now "default" collection of Big Data change what we think of as a "voice," and what counts as "speech" for data visualization as a documentary form?6 While data visualization allows the eye to take in large amounts of data in the space of a glance, the embodied human voice cannot [End Page 377] be taken into the ear "at a glance." Steven Connor has described the space of...

This article addresses the urgency of improving hydrological monitoring and effective water resource management, which is particularly crucial for flood prevention and rapid emergency response.The problem lies in the need to develop a tool for efficient collection, processing, and visualization of water level data in the rivers of the Lviv region. The research objective is to develop and implement an interactive web application based on ArcGIS for visualizing and analyzing water level dynamics. This tool is designed to display the location of hydrological posts, provide access to their current status information, and analyze time series of hydrological data. The key feature of this approach is the integration and visualization of data from both automated and manual (gauge) posts, significantly expanding the cover-age of hydrological information.Based on the stated objectives, the geoinformation approach has been implemented for collecting and visualizing hydro-logical post data in the Lviv region using ArcGIS tools. The data source for this system comprises observations provided by the Basin Water Resources Management of the Western Bug and Sian Rivers. As a result, the interactive ArcGIS monitoring dash-board has been developed. It visualizes spatial and temporal water level data, integrating a web map with tabular time series data. This ensures automatic synchronization between selecting a post on the map and displaying dynamic charts and analytical tables. The web application facilitates comprehensive analysis of hydrological data.The proposed solution significantly enhances hydrological monitoring and supports managerial decision-making regarding flood prevention and emergency response. Its practical value lies in its application for water resource management and flood risk assessment, including the visualization of indicators and access to operational information for specialists and au-thorities. Future research will focus on real-time data updates, integration with meteorological indicators, and development of models for forecasting water levels and potential flood zones.

Data on construction resources (personnel, equipment, materials) is vast and the effort to collect and analyze it automatically is a priority in the construction industry. Once remote sensing and intelligent data processing technology are applied to supplement manual data recording, however, very few data visualization tools in construction exist that allow visualizing dynamic resource data in a field realistic virtual reality environment and are at the same time able to perform this task in or near real-time. Moreover, technology to assist in real-time data visualization and situational awareness can have a significant impact on stakeholders’ successful and safe completion of construction projects. This research addresses the need for realtime data collection and visualization technology in construction applications. It reviews state-of-the-art technology in this field and presents a new framework that implements real-time remote sensing and data visualization technology in two significant construction applications: (1) Real-time pro-active construction safety assessment and training, and (2) Real-time construction productivity and performance monitoring. Preliminary results to each of these scenarios are presented and discussed.

The Digital Oil Field (DOF) has been exhaustively discussed for production enhancement and optimization, but there has been little focus on its use in other areas. This paper describes an integrated approach by multiple business units on how data management and visualization is been applied to enhance decision making, improve cost control, and increase asset integrity in Murphy’s onshore and offshore developments. Data visualization and the automation of data reporting play an important role in achieving the goal of reducing OPEX and optimizing field operation activities. As more data becomes available, a tool for maximizing the benefits of how data is presented and used in day-to-day decision making is required. This begins with reducing man-hours associated with data acquisition, report-generation, analytical tool development and key performance indicator (KPI) tracking. A data management and visualization tool is currently in-use to enhance offshore operations in chemical management, cost-tracking, and production forecasting, as well as unconventional onshore operations for asset integrity monitoring systems. Since implementation, the program minimizes duplicate work by field personnel, as well as ensures they are engaged and involved in OPEX reduction and increasing field uptime. Effective visualization of data streamlines decision-making on chemical performance, cost-benefit analysis, and effective treatment. It also maximizes the amount of data available for use and interpretation. In remote areas onshore field data is entered via mobile devices, providing a fast, simple, and effective tool for managing onshore maintenance campaigns, pigging programs, cathodic protection, & vessel inspections. New workflows provide real-time data and metrics to help make on the fly ‘fit-for-purpose’ decisions. Utilization of apps and dashboards has drastically changed the performance of the asset integrity & maintenance programs and significantly reduced OPEX across onshore and offshore assets, and improves reliability across pipeline and gathering systems by identifying high-risk areas and reducing system upsets. This shift has moved focus from effective data collection to using the existing data in an efficient and cost-effective way in helping the operations engineering team and field operations in data analysis, KPI-tracking and achieving production and OPEX targets. It also provides indication of existing data gaps and identifies where more data collection would add value to business decisions.

Data visualization has become a hot topic over the last few years. This popularity can be seen everywhere. The New York Times revolutionized itself by creating gorgeous, interactive visualizations of everything from political campaigns to nutrition. (1) There is a suddenly vibrant data visualization blog scene, lead by stellar resources FlowingData and Information is Beautiful. (2) More and more software programs have appeared that make creating compelling visualizations easier and easier, but also more and more data are collected and analyzed digitally. Our new means of collecting data necessitates new means of representation to communicate the message of massive and messy sets of data. The immense success of computing in the second half of the twentieth century has brought about a correspondingly immense challenge: how do we deal with all of this data? Design thinking stepped up to the challenge by allying with statistics to create the half-art, half-science of data visualization. Libraries have not been left behind; everywhere the rise of new forms of data presentation is visible. The Seattle Public Library features a live-updating dashboard showing recent circulations and intricate networks of keywords. (3) The Harvard Library Lab is working on a powerful tool to view collection size and circulation by subject heading. (4) The Indianapolis Museum of Art has a web dashboard that boldly presents their changing quantities of artwork, memberships, visitors, and of course Facebook fans. (5) Brown University Libraries are working on a similar idea that presents live data such as checkouts in embeddable widget form. (6) The North Carolina State University Libraries have an ambitious data visualization project that aims to visualize the usage of reference services, course tools, computer workstations, and group study rooms. (7) These are all great strides being made by innovative libraries. Hopefully, as more examples appear and these frontrunners release their techniques as open-source code, the barrier to entry will diminish for all libraries. In the years to come, public data dashboards on library websites may be as common as catalog search boxes. It is not the aim of this column, however, to enumerate the most beautiful graphs of library data on the web but to demystify the practice of data visualization so that we can begin to create our own. THE PURPOSE OF VISUALIZATION Data visualization has a clear purpose: to aid in our understanding of data. Visualizations help us recognize otherwise obscure trends. Many visualizations offer means of interaction, they do not merely report a single, unassailable truth, but give the end-user an opportunity to explore the data and reach possibly unanticipated conclusions. They help us simplify the interpretation of an intimidating universe of data, intimidating both in terms of the sheer size of datasets, which can consist of millions of data points but also in terms of the dimensions of the data. A dataset might have only a dozen distinct points, but each point could in turn have thousands of aspects to it, a veritable world unto itself. Think of library branches: even large public library systems may have a single digit number of branches, but each of those branches has distinct sets of opening hours, geographic coordinates, items in the collection, staff members, and services. Distilling those differences into a meaningful representation is a challenge. [FIGURE 1 OMITTED] Data visualization approaches the challenges of size and complexity by fusing the art of design with the logic of statistics. Success hinges on both; a brilliant statistician can produce incoherent spreadsheets, while a talented designer can create misleading visuals. Above all, visualization strives to accurately represent data; mere artistry descends into chart junk and delusion. Figure 1 is representative of everything data visualization seeks to overcome. …

In the age of information explosion, users are exposed to overwhelmingly visual information every day. The raw unprocessed data are not attractive enough to the human brain. Thankfully, humans are extremely sensitive to graphic image perception and can understand the meaning behind numbers from graphic images. For this reason, data visualization is becoming the best way to communicate with people. In the context of big data, how to display complex data efficiently, what kind of drawing technology to use, and how to improve user interaction with data are urgent problems to be solved by data visualization technology. On the other hand, researchers’ understanding of data visualization is not consistent; there is no clear standard; and it is relatively confusing. Researchers engaged in data visualization and executives engaged in related data visualization industries have different interpretations of it, and the core theoretical basis and research methods are still in the exploration stage. Firstly, I systematically introduce the design principles of data visualization, software development related technologies, data visualization research methods, basic charts, and characteristics of data visualization. Secondly, based on the software development process, I analyzed the key issues of data visualization for the e-commerce system, gave the objectives of the design plan, and designed the whole architecture and development framework of the project. In particular, I designed the class diagram and timing diagram of the control layer, service layer, and data access layer for the visualization of user purchase preferences in the data visualization and analysis module as an example. Then, with the structure and characteristics of the data in the visualization studied, the business logic layer and the front-end visualization layer are implemented, and a good user interaction function is provided for the users. The data visualization is loaded asynchronously and on demand to improve the performance of data visualization and user interaction experience. Finally, the system data is presented with the analysis of the user population’s region, the analysis of user preferences, and the analysis of the product price sales relationship, and the product category tree diagram and the results of the data visualization run are given, providing a comprehensive platform for shopping, data analysis, and data visualization for the next generation e-commerce system.

Researchers can acquire insights from complex data sets and better share their findings with others when they employ data visualization and exploration tools. We discuss existing techniques and tools for visualizing and exploring complex scientific data, identify the key concepts and principles of data visualization, and propose a new technique to address some of the limitations of existing approaches to data exploration and visualization. Our suggested method utilizes cloud computing and ML to deliver dynamic, interactive visualizations in real-time, regardless of data size or complexity. Our research provides a unique method for overcoming the limits of existing data visualization and exploration tools in the context of scientific inquiry, in addition to a detailed overview of existing methodologies and tools. We hope our results will stimulate greater investigation into this vital area, leading to improved methods and tools for visualizing and navigating intricate scientific data

The term “visual data” is often connected with strategies related to developing graphs or other types of quantitative visual data arrays. Visual data provide quantitative statistical information about our natural and constructed worlds. There is great power in the graphical visual data; they can provide portraits of our world that might escape our notice. This chapter focuses on portraying certain qualitative aspects of visual data that allow for a sense of the deeper nature (essence) of selected data sets. This approach can be termed aesthetically enhanced visual data. The data drive image making, while emphasis is given to aesthetic concerns. The goal is to identify and portray the nature of the nature of the aesthetic visual data. In this chapter the artist-author presents aesthetic visual data focused on describing certain aspects of the world. Artworks created through the aesthetic data visualization are presented along with clarifying notations.

The past years’ uncertainties and pressures resulted from the pandemic, alongside new developments in social technology, 5G, cloud computing, augmented and virtual reality, have generated the perfect setting for the metaverse to gain traction. Several companies found there’s a critical need to redefine the work environment and started exploring the metaverse concept beyond the entertainment sector. Thus, new tools for collaboration and data visualization within a digital shared space are being created, aiming for a fully immersive interaction between the virtual and the physical worlds within the next few years. While still in its early developments, the metaverse can be seen as an extension of the social media platforms, and an opportunity to leverage remote work even further. ICESS 2022 provides a space for all those interested in Economics and Social Sciences to discuss and exchange research ideas in the light of the work environment, business model, and technological changes driven by COVID-19. We welcome both empirical and theoretical work that is broadly consistent with the conference’s general theme. The main topics of the conference are focused on, but not limited to, the following sections: Applied Economics, Statistics and Data Science

The past years’ uncertainties and pressures resulted from the pandemic, alongside new developments in social technology, 5G, cloud computing, augmented and virtual reality, have generated the perfect setting for the metaverse to gain traction. Several companies found there’s a critical need to redefine the work environment and started exploring the metaverse concept beyond the entertainment sector. Thus, new tools for collaboration and data visualization within a digital shared space are being created, aiming for a fully immersive interaction between the virtual and the physical worlds within the next few years. While still in its early developments, the metaverse can be seen as an extension of the social media platforms, and an opportunity to leverage remote work even further. ICESS 2022 provides a space for all those interested in Economics and Social Sciences to discuss and exchange research ideas in the light of the work environment, business model, and technological changes driven by COVID-19. We welcome both empirical and theoretical work that is broadly consistent with the conference’s general theme. The main topics of the conference are focused on, but not limited to, the following sections: Applied Economics, Statistics and Data Science

The past years’ uncertainties and pressures resulted from the pandemic, alongside new developments in social technology, 5G, cloud computing, augmented and virtual reality, have generated the perfect setting for the metaverse to gain traction. Several companies found there’s a critical need to redefine the work environment and started exploring the metaverse concept beyond the entertainment sector. Thus, new tools for collaboration and data visualization within a digital shared space are being created, aiming for a fully immersive interaction between the virtual and the physical worlds within the next few years. While still in its early developments, the metaverse can be seen as an extension of the social media platforms, and an opportunity to leverage remote work even further. ICESS 2022 provides a space for all those interested in Economics and Social Sciences to discuss and exchange research ideas in the light of the work environment, business model, and technological changes driven by COVID-19. We welcome both empirical and theoretical work that is broadly consistent with the conference’s general theme. The main topics of the conference are focused on, but not limited to, the following sections: Applied Economics, Statistics and Data Science

The past years’ uncertainties and pressures resulted from the pandemic, alongside new developments in social technology, 5G, cloud computing, augmented and virtual reality, have generated the perfect setting for the metaverse to gain traction. Several companies found there’s a critical need to redefine the work environment and started exploring the metaverse concept beyond the entertainment sector. Thus, new tools for collaboration and data visualization within a digital shared space are being created, aiming for a fully immersive interaction between the virtual and the physical worlds within the next few years. While still in its early developments, the metaverse can be seen as an extension of the social media platforms, and an opportunity to leverage remote work even further. ICESS 2022 provides a space for all those interested in Economics and Social Sciences to discuss and exchange research ideas in the light of the work environment, business model, and technological changes driven by COVID-19. We welcome both empirical and theoretical work that is broadly consistent with the conference’s general theme. The main topics of the conference are focused on, but not limited to, the following sections: Applied Economics, Statistics and Data Science

The past years’ uncertainties and pressures resulted from the pandemic, alongside new developments in social technology, 5G, cloud computing, augmented and virtual reality, have generated the perfect setting for the metaverse to gain traction. Several companies found there’s a critical need to redefine the work environment and started exploring the metaverse concept beyond the entertainment sector. Thus, new tools for collaboration and data visualization within a digital shared space are being created, aiming for a fully immersive interaction between the virtual and the physical worlds within the next few years. While still in its early developments, the metaverse can be seen as an extension of the social media platforms, and an opportunity to leverage remote work even further. ICESS 2022 provides a space for all those interested in Economics and Social Sciences to discuss and exchange research ideas in the light of the work environment, business model, and technological changes driven by COVID-19. We welcome both empirical and theoretical work that is broadly consistent with the conference’s general theme. The main topics of the conference are focused on, but not limited to, the following sections: Applied Economics, Statistics and Data Science