Data visualization is the study of the visual representation of data The term data refers to groups of information that represent the qualitative or quantitative attributes of a variable or set of variables. Data are typically the results of measurements and can be the basis of graphs, images, or observations of a set of variables. Data are often viewed as the lowest level of abstraction from which information and, meaning "information which has been abstracted in some schematic form, including attributes or variables for the units of information".^[1]

According to Friedman (2008) the "main goal of data visualization is to communicate information clearly and effectively through graphical means. It doesn’t mean that data visualization needs to look boring to be functional or extremely sophisticated to look beautiful. To convey ideas effectively, both aesthetic form and functionality need to go hand in hand, providing insights into a rather sparse and complex data set by communicating its key-aspects in a more intuitive way. Yet designers often fail to achieve a balance between design and function, creating gorgeous data visualizations which fail to serve their main purpose — to communicate information".^[2]

Data visualization is closely related to Information graphics Information graphics or infographics are visual representations of information, data or knowledge. These graphics are used where complex information needs to be explained quickly and clearly, such as in signs, maps, journalism, technical writing, and education. They are also used extensively as tools by computer scientists, mathematicians, and, Information visualization Information visualization is the interdisciplinary study of "the visual representation of large-scale collections of non-numerical information, such as files and lines of code in software systems, library and bibliographic databases, networks of relations on the internet, and so forth", Scientific visualization Scientific visualization is an interdisciplinary branch of science according to Friendly (2008) "primarily concerned with the visualization of three dimensional phenomena (architectural, meteorological, medical, biological, etc.), where the emphasis is on realistic renderings of volumes, surfaces, illumination sources, and so forth, perhaps and Statistical graphics Statistical graphics, also known as graphical techniques, are information graphics in the field of statistics used to visualize quantitative data. In the new millennium data visualization has become active area of research, teaching and development. According to Post et al (2002) it has united the field of scientific and information visualization".^[3]

Data visualization scope

There are different approaches on the scope of data visualization. One common focus is on information presentation such as Friedman (2008) presented it. On this way Friendly (2008) presumes two main parts of data visualization: statistical graphics Statistical graphics, also known as graphical techniques, are information graphics in the field of statistics used to visualize quantitative data, and thematic cartography A thematic map is a type of map or chart especially designed to show a particular theme connected with a specific geographic area. These maps "can portray physical, social, political, cultural, economic, sociological, agricultural, or any other aspects of a city, state, region,nation , or continent".^[1] In this line the "Data Visualization: Modern Approaches" (2007) article gives an overview of seven subjects of data visualization:^[4]

• Mindmaps
• Displaying news News is the communication of information on current events which is presented by print, broadcast, Internet, or word of mouth to a third party or mass audience
• Displaying data The term data refers to groups of information that represent the qualitative or quantitative attributes of a variable or set of variables. Data are typically the results of measurements and can be the basis of graphs, images, or observations of a set of variables. Data are often viewed as the lowest level of abstraction from which information and
• Displaying connections
• Displaying websites A website is a collection of related web pages, images, videos or other digital assets that are addressed relative to a common Uniform Resource Locator (URL), often consisting of only the domain name, or the IP address, and the root path ('/') in an Internet Protocol-based network. A web site is hosted on at least one web server, accessible via a
• Articles A news article is an article published in a print or Internet news medium such as a newspaper, newsletter, news magazine, news-oriented website, or article directory that discusses current or recent news of either general interest or on a specific topic (i.e. political or trade news magazines, club newsletters, or technology news websites) & resources A resource is any physical or virtual entity of limited availability that needs to be consumed to obtain a benefit from it. In most cases, commercial or even ethic factors require resource allocation through resource management
• Tools and services

All these subjects are all close related to graphic design Graphic design is a creative process — most often involving a client and a designer and usually completed in conjunction with producers of form — undertaken in order to convey a specific message (or messages) to a targeted audience. The term "graphic design" can also refer to a number of artistic and professional disciplines that and information representation.

On the other hand, from a computer science Computer science or computing science is the study of the theoretical foundations of information and computation, and of practical techniques for their implementation and application in computer systems. It is frequently described as the systematic study of algorithmic processes that create, describe, and transform information. Computer science perspective, Frits H. Post (2002) categorized the field into a number of sub-fields: ^[3]

• Visualization algorithms In mathematics, computer science, and related subjects, an 'algorithm' is an effective method for solving a problem expressed as a finite sequence of instructions. Algorithms are used for calculation, data processing, and many other fields and techniques
• Volume visualization
• Information visualization Information visualization is the interdisciplinary study of "the visual representation of large-scale collections of non-numerical information, such as files and lines of code in software systems, library and bibliographic databases, networks of relations on the internet, and so forth"
• Multiresolution methods
• Modelling techniques and
• Interaction techniques and architectures

Related fields

Data acquisition

Data acquisition Data acquisition is the process of sampling of real world physical conditions and conversion of the resulting samples into digital numeric values that can be manipulated by a computer. Data acquisition and data acquisition systems (abbreviated with the acronym DAS) typically involves the conversion of analog waveforms into digital values for is the sampling of the real world to generate data that can be manipulated by a computer. Sometimes abbreviated DAQ or DAS, data acquisition typically involves acquisition of signals and waveforms and processing the signals to obtain desired information. The components of data acquisition systems include appropriate sensors that convert any measurement parameter to an electrical signal, which is acquired by data acquisition hardware.

Data analysis

Data analysis Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of highlighting useful information, suggesting conclusions, and supporting decision making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social is the process of looking at and summarizing data The term data refers to groups of information that represent the qualitative or quantitative attributes of a variable or set of variables. Data are typically the results of measurements and can be the basis of graphs, images, or observations of a set of variables. Data are often viewed as the lowest level of abstraction from which information and with the intent to extract useful information Information, in its most restricted technical sense, is an ordered sequence of symbols. As a concept, however, information has many meanings. Moreover, the concept of information is closely related to notions of constraint, communication, control, form, instruction, knowledge, meaning, mental stimulus, pattern, perception, and representation and develop conclusions. Data analysis is closely related to data mining Data mining is the process of extracting patterns from data. Data mining is becoming an increasingly important tool to transform the data into information. It is commonly used in a wide range of profiling practices, such as marketing, surveillance, fraud detection and scientific discovery, but data mining tends to focus on larger data sets, with less emphasis on making inference Inference is the process of drawing a conclusion by applying heuristics to observations or hypotheses; or by interpolating the next logical step in an intuited pattern. The conclusion drawn is also called an inference. The laws of valid inference are studied in the field of logic, and often uses data that was originally collected for a different purpose. In statistical applications Statistics is the formal science of making effective use of numerical data relating to groups of individuals or experiments. It deals with all aspects of this, including not only the collection, analysis and interpretation of such data, but also the planning of the collection of data, in terms of the design of surveys and experiments, some people divide data analysis into descriptive statistics Descriptive statistics are used to describe the main features of a collection of data in quantitative terms. Descriptive statistics are distinguished from inferential statistics , in that descriptive statistics aim to quantitatively summarize a data set, rather than being used to support inferential statements about the population that the data, exploratory data analysis Exploratory data analysis is an approach to analysing data for the purpose of formulating hypotheses worth testing, complementing the tools of conventional statistics for testing hypotheses. It was so named by John Tukey to contrast with Confirmatory Data Analysis, the term used for the set of ideas about hypothesis testing, p-values, confidence and confirmatory data analysis A statistical hypothesis test is a method of making statistical decisions using experimental data. In statistics, a result is called statistically significant if it is unlikely to have occurred by chance. The phrase ‘test of significance’, like much of modern statistics, was coined by Ronald Fisher "Critical tests of this kind may be, where the EDA focuses on discovering new features in the data, and CDA on confirming or falsifying existing hypotheses.

Types of data analysis are:

• Exploratory data analysis Exploratory data analysis is an approach to analysing data for the purpose of formulating hypotheses worth testing, complementing the tools of conventional statistics for testing hypotheses. It was so named by John Tukey to contrast with Confirmatory Data Analysis, the term used for the set of ideas about hypothesis testing, p-values, confidence (EDA): an approach to analyzing data for the purpose of formulating hypotheses A hypothesis is a proposed explanation for an observable phenomenon. The term derives from the Greek, ὑποτιθέναι – hypotithenai meaning "to put under" or "to suppose." For a hypothesis to be put forward as a scientific hypothesis, the scientific method requires that one can test it. Scientists generally base worth testing, complementing the tools of conventional statistics Statistics is the formal science of making effective use of numerical data relating to groups of individuals or experiments. It deals with all aspects of this, including not only the collection, analysis and interpretation of such data, but also the planning of the collection of data, in terms of the design of surveys and experiments for testing hypotheses. It was so named by John Tukey Tukey was born in New Bedford, Massachusetts in 1915, and obtained a B.A. in 1936 and M.Sc. in 1937, in chemistry, from Brown University, before moving to Princeton University where he received a Ph.D. in mathematics.
• Qualitative data analysis (QDA) or qualitative research Qualitative research is a method of inquiry appropriated in many different academic disciplines, traditionally in the social sciences, but also in market research and further contexts. Qualitative researchers aim to gather an in-depth understanding of human behavior and the reasons that govern such behavior. The qualitative method investigates the is the analysis of non-numerical data, for example words, photographs, observations, etc..

Data governance

Data governance Data governance is an emerging discipline with an evolving definition. The discipline embodies a convergence of data quality, data management, business process management, and risk management surrounding the handling of data in an organization. Through data governance, organizations are looking to exercise positive control over the processes and encompasses the people, processes and technology required to create a consistent, enterprise view of an organisation's data in order to:

• Increase consistency & confidence in decision making
• Decrease the risk of regulatory fines
• Improve data security
• Maximize the income generation potential of data
• Designate accountability for information quality

Data management

Data management The official definition provided by DAMA or Boucher: "Data Resource Management is the development and execution of architectures, policies, practices and procedures that properly manage the full data lifecycle needs of an enterprise."[citation needed] This definition is fairly broad and encompasses a number of professions which may not comprises all the academic disciplines related to managing data The term data refers to groups of information that represent the qualitative or quantitative attributes of a variable or set of variables. Data are typically the results of measurements and can be the basis of graphs, images, or observations of a set of variables. Data are often viewed as the lowest level of abstraction from which information and as a valuable resource. The official definition provided by DAMA Dama is a village in southern Syria, in As Suwaydā' Governorate. It is located in the heart of the Lejah lava plateau, 29 km north west of the city of As Suwayda is that "Data Resource Management is the development and execution of architectures, policies, practices and procedures that properly manage the full data lifecycle needs of an enterprise." This definition is fairly broad and encompasses a number of professions which may not have direct technical contact with lower-level aspects of data management, such as relational database Such a grouping uses the relational model . Hence, such a database is called a "relational database." management.

Data mining

Data mining Data mining is the process of extracting patterns from data. Data mining is becoming an increasingly important tool to transform the data into information. It is commonly used in a wide range of profiling practices, such as marketing, surveillance, fraud detection and scientific discovery is the process of sorting For sorting we can either specify a weak order "should not come after" or a strict weak order "should come before" . For the sorting to be unique, these two are restricted to a total order and a strict total order, respectively through large amounts of data and picking out relevant information. It is usually used by business intelligence Business Intelligence refers to computer-based techniques used in spotting, digging-out, and analyzing business data, such as sales revenue by products and/or departments or associated costs and incomes organizations, and financial analysts A financial analyst, securities analyst, research analyst, equity analyst, or investment analyst is a person who performs financial analysis for external or internal clients as a core part of the job, but is increasingly being used in the sciences to extract information from the enormous data sets A data set is a collection of data, usually presented in tabular form. Each column represents a particular variable. Each row corresponds to a given member of the data set in question. Its values for each of the variables, such as height and weight of an object or values of random numbers. Each value is known as a datum. The data set may comprise generated by modern experimental and observational methods.

It has been described as "the nontrivial extraction of implicit, previously unknown, and potentially useful information Information, in its most restricted technical sense, is an ordered sequence of symbols. As a concept, however, information has many meanings. Moreover, the concept of information is closely related to notions of constraint, communication, control, form, instruction, knowledge, meaning, mental stimulus, pattern, perception, and representation from data The term data refers to groups of information that represent the qualitative or quantitative attributes of a variable or set of variables. Data are typically the results of measurements and can be the basis of graphs, images, or observations of a set of variables. Data are often viewed as the lowest level of abstraction from which information and"^[5] and "the science of extracting useful information from large data sets A data set is a collection of data, usually presented in tabular form. Each column represents a particular variable. Each row corresponds to a given member of the data set in question. Its values for each of the variables, such as height and weight of an object or values of random numbers. Each value is known as a datum. The data set may comprise or databases A database consists of an organized collection of data for one or more uses, typically in digital form. One way of classifying databases involves the type of their contents, for example: bibliographic, document-text, statistical. Digital databases are managed using database management systems, which store database contents, allowing data creation."^[6] In relation to enterprise resource planning Enterprise resource planning is an integrated computer-based system used to manage internal and external resources including tangible assets, financial resources, materials, and human resources. It is a software architecture whose purpose is to facilitate the flow of information between all business functions inside the boundaries of the, according to Monk (2006), data mining is "the statistical and logical analysis of large sets of transaction data, looking for patterns that can aid decision making".^[7]

See also

• Scientific visualization Scientific visualization is an interdisciplinary branch of science according to Friendly (2008) "primarily concerned with the visualization of three dimensional phenomena (architectural, meteorological, medical, biological, etc.), where the emphasis is on realistic renderings of volumes, surfaces, illumination sources, and so forth, perhaps

Software

• Data Desk Data Desk is a software program for visual data analysis, visual data exploration, and statistics. It carries out Exploratory Data Analysis and standard statistical analyses by means of dynamically linked graphic data displays that update any change simultaneously
• DAVIX
• Eye-Sys
• Ferret Data Visualization and Analysis
• GGobi
• IBM OpenDX
• IDL (programming language)
• Instantatlas
• OpenLink AJAX Toolkit OpenLink AJAX Toolkit is a JavaScript-based toolkit for browser-independent Rich Internet Application development. It includes a rich collection of UI Widgets/Controls, Event Management System, and a truly platform independent Data Access Layer called AJAX Database Connectivity. OpenLink AJAX Toolkit is fully OpenAjax Alliance Conformant
• ParaView
• Processing (programming language)
• ScienceGL (www.sciencegl.com)
• Smile (software)
• StatSoft
• Visifire
• VisIt
• VTK
• Yoix

References

1. ^ ^{a b} Michael Friendly Michael Lewis Friendly is a Professor of Psychology at York University in Ontario, Canada, and an Associate Coordinator with the Statistical Consulting Service (2008). "Milestones in the history of thematic cartography, statistical graphics, and data visualization".
2. ^ Vitaly Friedman (2008) "Data Visualization and Infographics" in: Graphics, Monday Inspiration, January 14th, 2008.
3. ^ ^{a b} Frits H. Post, Gregory M. Nielson and Georges-Pierre Bonneau (2002). Data Visualization: The State of the Art. Research paper TU delft, 2002..
4. ^ "Data Visualization: Modern Approaches". in: Graphics, August 2nd, 2007
5. ^ W. Frawley and G. Piatetsky-Shapiro and C. Matheus (Fall 1992). "Knowledge Discovery in Databases: An Overview". AI Magazine: pp. 213–228. ISSN 0738-4602.
6. ^ D. Hand, H. Mannila, P. Smyth (2001). Principles of Data Mining. MIT Press, Cambridge, MA. ISBN 0-262-08290-X.
7. ^ Ellen Monk, Bret Wagner (2006). Concepts in Enterprise Resource Planning, Second Edition. Thomson Course Technology, Boston, MA. ISBN 0-619-21663-8.

Further reading

• Chandrajit Bajaj, Bala Krishnamurthy (1999). 'Data Visualization Techniques.
• William S. Cleveland (1993). Visualizing Data. Hobart Press.
• William S. Cleveland (1994). The Elements of Graphing Data. Hobart Press.
• Alexander N. Gorban, Balázs Kégl, Donald Wunsch, and Andrei Zinovyev (2008). Principal Manifolds for Data Visualization and Dimension Reduction. LNCSE 58. Springer.
• John P. Lee and Georges G. Grinstein (eds.) (1994). Database Issues for Data Visualization: IEEE Visualization '93 Workshop, San Diego.
• Peter R. Keller and Mary Keller (1993). Visual Cues: Practical Data Visualization.
• Frits H. Post, Gregory M. Nielson and Georges-Pierre Bonneau (2002). Data Visualization: The State of the Art.

External links

• Milestones in the History of Thematic Cartography, Statistical Graphics, and Data Visualization, An illustrated chronology of innovations by Michael Friendly and Daniel J. Denis.

Categories: Visualization (graphic) | Data analysis | Data collection | Data management | Data mining | Information technology governance

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