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Information Visualization: Task by Data Type Taxonomy Report


Visualization of information is the process of transforming large and complex types of abstract data into a visual form. It allows creating the demonstrative images of both structured and unstructured information, which is difficult to comprehend otherwise. During recent years, the given technology became widely used in such areas as biological sciences, artificial intelligence, financial information analysis, et cetera. Due to the increasing interest in information visualization, a lot of new techniques and taxonomies became developed, which are meant to represent the data efficiently and effectively that would enable users to study the multiple variables at distinct levels in great detail. Visualization taxonomies for both simple one-dimensional and complex multi-dimensional data analyses that exist nowadays are usually data-centric and mainly concentrate on tasks to enable the perception of data category separation and conservation. The Task by Data Type Taxonomy (TTT) is one of them.

Visualization Taxonomy Overview

The TTT is first introduced by Ben Shneiderman in an attempt to address the problem of visual representation of big data. It is based on the assumption that “users are viewing collections of items, where items have multiple attributes1.” The taxonomy comprises seven distinct types of data sets, which can be arranged in various ways: one-, two-, three-, and multi-dimensional data, as well as the temporal, tree, and network data2. It is suggested that when investigating different types of data as per the primary search task in the TTT, all the information items that meet the values of a set of attributes will be selected3. At the same time, the tasks that one can perform by using the TTT depend on the kind of information, which the user wants to retrieve. They include the overview, the search of links between variables, the filtering, and other procedures.

In the Department of Tourism and Commerce Marketing, the way the TTT may be implemented at the individual, group, and organizational levels can be substantially defined by both the types of data used at those levels and the tasks performed by the team members. It is possible to presume that at the individual level, employees will likely perform less complicated procedures, such as overview and filtering, and analyze more straightforward kinds of information such as one-dimensional data, namely, linear/sequential data types, and temporal data, namely, historical presentations. However, the given presumption does not always reflect the actual situation. For instance, a person in the position of a National Marketing Manager may use multi-dimensional data to process statistics related to the rate of travel destination visits, the efficacy of implemented promotion and marketing plans, the alignment of performance with annual target goals, et cetera. The tasks one may carry out to investigate the given type of information are “finding patterns, clusters, correlations among pairs of variables, gaps, and outliers4.”As for the ways, these data can be represented, they include both two- and three-dimensional scattergrams.

At the same time, at the group level and the organizational level, the tasks aimed to process more complex data sets are likely to be performed. For example, the communities of practice such as the Tourism Development Department may choose to investigate the relationships between various items (for instance, tourists’ demographics, traveling activity preferences, duration of stay, et cetera) in the network structure. In either way, whatever task the organization, the group, or the individual would decide to use to analyze a data set, the main choice criterion should always be the contribution of the tool to the facilitation of the topic discussion and the overall usefulness of the research outcomes.

It is worth noticing that, at the current stage of the overall global technological advancement, the process of information analysis and visual representation of results provided at any organizational level must be monitored and attended by an employee or a group of employees who possess an appropriate set of competencies. It means that for the effective representation of information, in addition to the existing managerial competencies, including the ability to work with information, decision-makers must have the skills of visual communication and visual literacy. The latter term implies the ability to perceive and interpret information, and endow the data represented in a visualized form with relevant meaning.

Potentials and Objectives

The primary purpose of all the new types of graphical presentation of information is to make complex data arrays easier to understand. Overall, the visualization of information plays an essential role in both the acquisition and the transfer of knowledge. Visual languages complement the techniques of conceptual modeling, making the abstract concepts understandable not only for experts and analysts, but also for newbies in multiple spheres including management, finances, and science. It is possible to say that the main objective of the subject matter discussed in the paper by Shneiderman, that is to say, representing the information visually and improving the visualization user interface, is to enhance the readability of the analyzed data sets, particularly in the case when their volumes are large. As Shneiderman notes, the TTT “is useful only if it facilitates discussion and leads to useful discoveries5.” Based on the given statement, it is valid to conclude that the taxonomy and the techniques, which it contains, aim to improve users’ experiences and to facilitate the communication and comprehension of information.

Particular enablers allowing the achievement of the identified objectives and potentials are the visualization tools and their functions themselves. For instance, it refers to the creation of hierarchical data structures represented as trees. It is considered that a well-developed visualization of hierarchical information helps the user to find a required element in the hierarchy quickly, to understand the relation of the element to its context, and to ensure the possibility of direct access to information at the graph vertex6. For example, such a visualization method as Treemap, which was first introduced by Brian Johnson and Ben Shneiderman in 1991, aims to represent a tree, each vertex of which has a name and a numerical attribute, in the form of a rectangle7. This kind of visualization is beneficial when displaying the numerical characteristics of elements (size, value, and significance) organized in large hierarchies.

As for the factors that can block the visualization success, the volume of the represented data may be regarded as the main one. An algorithm that represents a few hundreds of vertexes well shall not necessarily be as good during the analysis of a few thousands of vertexes. Moreover, the visualization of a significant amount of information is not always useful ̶ sometimes it may deteriorate the readability of an image. The key to reducing the number of details represented in the graph simultaneously is the transition from the static methods of visualization to the interactive ones, which foster the implementation of navigation and such techniques as Focus + Context, including geometrical or semantic deformation, clustering, aggregation, and other methods8. Considering Shneiderman’s Visual Information Seeking Mantra, which states “overview first, zoom and filter, then details-on-demand,” it is valid to say that the TTT implies the interactive approach to data representation as well9. The function of zooming included in the given taxonomy helps users locate any item of interest. At the same time, such a task as details-on-demand assists in choosing “an item or group and get details when needed10.” Consequently, they allow mitigating the risks that can be encountered when dealing with large data volumes.

Gap Analysis and Recommendations

Currently, in the Department of Tourism and Commerce Marketing, information visualization is used to demonstrate statistical data related to such indices as the number of visitors in various touristic attractions, the types of accommodation, et cetera. Usually, the representation takes forms of bar and pie charts and similar graphs, and the main task conducted during the information visualization is the overview, while more complicated procedures, such as finding links between distinct variables, cannot be carried out by using the available data representation instruments. It is possible to suggest that the implementation of those visualization methods, which allow the transformation of data into graphs and also imply the possibility of interactive information representation, could provide more strategic advantages for the Department of Tourism and Commerce Marketing. The visualization tools that are in line with the TTT are oriented towards more advanced analysis of problems, ideas, objectives, and concepts, and the results of such an analysis can be consequently applied during strategic planning.

Different performance measures can help organizational leaders make informed decisions. However, Al-Kassab et al. note that one’s ability to benefit from the use of such data largely depends on “how the measure is shaped, communicated, and made accessible and interactive11.” It means that the company’s competitive advantage may indeed stem from the visualization technology it employs. Not only can a more innovative information visualization tool to improve data perception but also may enhance the insight and control over informational resources, and provide valuable and credible data, which may be inaccessible to major competitors. For this reason, the primary short-term recommendation for the Department of Tourism and Commerce Marketing is to integrate the interactive information visualization software, consistent with the TTT principles, into its strategic planning activities.

Secondly, it is apparent that without suitable information technology (IT) the implementation of data visualization programs would be impossible. The organization usually does not process excessively large volumes of information, so no significant changes in its current internal IT network are required to engage in advanced data visualization. For data representation, the Department of Tourism and Commerce Marketing may combine different off-the-shelf analytics and data processing instruments including MS Excel, Oracle PL/SQL, et cetera. Additionally, it may use self-programmed software for the automatic collection of raw data from various departments12. Along with this, to increase visualization success, it is critical to ensure that the analysis processes are conducted on a highly professional level. The creation of a centralized analytics entity in the organization may help achieve this. Moreover, when centralized, data processing and visualization management across the departments located in different geographic zones and distinct types of experts may be substantially facilitated as the evaluation of multiple interconnected organizational variables will become more coordinated in this way. Thus, it may be recommended for the Department of Tourism and Commerce Marketing to establish the identified corporate body in the short term.

Thirdly, the organization needs to increase all employees’ access to visual data. Information access is a crucial element of corporate knowledge management, and the existence of various knowledge management systems, such as organizational databases, online forums, and others, allows preserving valuable information sets, accumulating them, and updating them if needed. Knowledge management systems as such can be considered the foundation of the organizational memory, and information visualization can contribute to its development and strengthening because it may be regarded as an enabler of employee learning. According to Al-Kassab et al. “visualization operates as a catalyst for interpretations that are at the basis of knowledge extraction, exploration, and creation13.” It means that the very manner in which visual information is coded fosters knowledge development, as well as its consequent application in practice. Nevertheless, to attain the desired outcome, the company must have an environment that supports information sharing. The development of such a knowledge management culture can be regarded as a mid-term objective because it is pivotal to produce the visual data first before disseminating it among the staff members.

It may also be recommended for the organization to apply information visualization for a broader range of strategic areas including the evaluation of overall organizational performance. As it was mentioned before, the Department of Tourism and Commerce Marketing uses visual data almost exclusively to demonstrate performance outcomes, in particular, separate areas: tourist attraction rates, organizational finances, et cetera. However, various types of visual information may be utilized more creatively and more effectively for a wider number of purposes, including employee engagement. As stated by Burkhard, tree diagrams may be efficiently used for the promotion of a “shared and coordinated understanding of the strategy in the project team,” while maps demonstrating interrelationships among concepts, processes, and objects can help “engage persons from different backgrounds14.” The diversification of options for visual data implementation in the organization can take place simultaneously with the improvement of the corporate knowledge management practices and systems when the process of the visualization technology integration and allocation of responsibilities will be accomplished. It means that the given recommendation may be realized within the mid-term.

Lastly, to further improve the effectiveness of visualization efforts and maintain its competitive advantages associated with data representation and its functionality, it may be suggested for the Department of Tourism and Commerce Marketing to research recent advancements in visualization technologies continually. Like any other technology, visualization tools and methods continue to evolve, and researchers keep on suggesting novel processing tasks and solutions, which are meant to facilitate and improve data analysis and communication even more. Thus, the employed instruments can rapidly become obsolete and cease to produce relevant market benefits. A regular program and IT upgrade may help mitigate the given risk in the long run.

Conclusions

The TTT discussed in the reviewed article by Shneiderman offers an interactive approach to data analysis and representation. The user interfaces and search engines enabled within the given taxonomy allow one to find any small item in even excessively complex documents, graphs, and images. The tasks, which users may perform by using the TTT, include an overview, zooming, filtering, extracting, obtaining details on demand, relating variables, and history keeping. Different visual data models created by using those tasks serve various purposes. Some of them are the provision of in-depth insight into an issue under consideration due to the support of network structures and the accountability of relations between concepts, the depiction of processes and their history, the revelation of casual chains among the variables, and many others. It is valid to say that the utilization of the given models in the organization operating in any industry is highly beneficial in terms of performance evaluation and improvement, as well as strategic planning.

As for the state of information visualization in the Department of Tourism and Commerce Marketing, it remains underdeveloped, and the spheres of its implementation are limited. Mainly, employees utilize visual data models such as diagrams, tables, and pie charts to show the statistical data and various performance indices. The major purpose of doing so is the overview and the superficial assessment of the presented information. Overall, the visualization technologies currently employed in the organization do not allow a deeper insight into the links between distinct variables of performance and an innovative approach to data manipulation. At the same time, there are no significant barriers to the integration of advanced information representation tools in the Department of Tourism and Commerce Marketing, and the recommendations provided in the present report can thus be feasibly realized there.

The recommendations arranged by the degree of their significance are as follows: 1. integration of an interactive information visualization program into the corporate strategic planning activities, 2. preparation of the internal IT network and system upgrade, 3. establishment of the centralized analytics department and allocation of responsibilities, 4. enhancement of the existing knowledge management culture and improvement of employees’ access to data presentations, 5. diversification of options for visual data implementation, and 6. regular upgrade of information visualization tools and supporting systems. The former three suggestions may be regarded as the basis for the efficient use of visual data and, therefore, they must be carried out initially and simultaneously. Recommendations 4 and 5 are the mid-term ones because, for their realization, a well-adjusted information visualization process is needed along with some existing visual data outputs. Lastly, recommendation 6 is the long-term one because it implies the update of technology based on potential deficiencies and flaws identified during its implementation in the organization and the understanding of how to align visualization functions with corporate strategic goals.

Overall, by following the provided recommendations, the Department of Tourism and Commerce Marketing may significantly maximize the benefits associated with the application of visual data models. First of all, information representation by using the TTT makes it possible to visually demonstrate a great variety of the analyzed processes, phenomena, and concepts in those cases when direct perception is complicated. This method of information organization and graphical representation of data can be used as a powerful assessment tool applied to all areas of intellectual activity, including the organizational modeling, the renovation of complex corporate structures, as well as the development of business-learning processes.

Bibliography

Al-Kassab, Jasser, Zied M. Ouertani, Giovanni Schiuma, and Andy Neely. “Information Visualization to Support Management Decisions.” International Journal of Information Technology & Decision Making 13, no. 2 (2014): 408-428.

Burkhard, Remo Aslak. CiteSEERX. Web.

Johnson, Brian, and Ben Shneiderman. IEEE. Web.

Munzner, Tamara, Francois Guimbretiere, Serdar Tasiran, Li Zhang, and Yunhong Zhou. “TreeJuxtaposer: Scalable Tree Comparison Using Focus+Context with Guaranteed Visibility.” ACM Transactions on Graphics 22, no. 3 (2003): 453-462.

Shneiderman, Ben. IEEE. Web.

Theron, Roberto. Semantics Scholar. Web.

Footnotes

  1. Ben Shneiderman, “The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations,” IEEE, Web.
  2. Ibid., 337.
  3. Ibid., 337.
  4. Ibid., 338.
  5. Ibid., 339.
  6. Roberto Theron, “Hierarchical-temporal Data Visualization Using a Tree-Ring Metaphor,” Semantics Scholar, Web.
  7. Brian Johnson and Ben Shneiderman, “Tree-Maps: A Space-Filling Approach to the Visualization of Hierarchical Information Structures,” IEEE, Web.
  8. Tamara Munzner et al., “TreeJuxtaposer: Scalable Tree Comparison Using Focus+Context with Guaranteed Visibility,” ACM Transactions on Graphics 22, no. 3 (2003): 453.
  9. Shneiderman, “The Eyes Have It,” 337.
  10. Ibid., 340.
  11. Jasser Al-Kassab et al., “Information Visualization to Support Management Decisions,” International Journal of Information Technology & Decision Making 13, no. 2 (2014): 408.
  12. Ibid., 414.
  13. Ibid., 412.
  14. Remo Aslak Burkhard, “Strategy Visualization: A New Research Focus in Knowledge Visualization and a Case Study,” CiteSEERX, Web.
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IvyPanda. (2020, November 27). Information Visualization: Task by Data Type Taxonomy. Retrieved from https://ivypanda.com/essays/information-visualization-task-by-data-type-taxonomy/

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"Information Visualization: Task by Data Type Taxonomy." IvyPanda, 27 Nov. 2020, ivypanda.com/essays/information-visualization-task-by-data-type-taxonomy/.

1. IvyPanda. "Information Visualization: Task by Data Type Taxonomy." November 27, 2020. https://ivypanda.com/essays/information-visualization-task-by-data-type-taxonomy/.


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IvyPanda. "Information Visualization: Task by Data Type Taxonomy." November 27, 2020. https://ivypanda.com/essays/information-visualization-task-by-data-type-taxonomy/.

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IvyPanda. 2020. "Information Visualization: Task by Data Type Taxonomy." November 27, 2020. https://ivypanda.com/essays/information-visualization-task-by-data-type-taxonomy/.

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IvyPanda. (2020) 'Information Visualization: Task by Data Type Taxonomy'. 27 November.

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