What Is Nonrepresentational Art

Nonrepresentational art is often used as another way to refer to abstract art, but there is a distinct difference between the two. Fundamentally, nonrepresentational art is work that does  not represent or depict a being, place, or thing. If representational art is a picture of something, for instance, nonrepresentational art is the complete opposite: Rather than directly portray something recognizable, the artist will use form, shape, color, and line—essential elements in visual art—to express emotion, feeling, or some other concept. Its also called complete abstraction or nonfigurative art.  Nonobjective art is related and often viewed as a subcategory of nonrepresentational art. Nonrepresentational Art Versus Abstraction The terms nonrepresentational art and abstract art are often used to refer to the same style of painting. However, when an artist works in abstraction, they are distorting the view of a known thing, person, or place. For example, a landscape can easily be abstracted, and Picasso often abstracted people and instruments. Nonrepresentational art, on the other hand, does not begin with a thing or subject from which a distinctive abstract view is formed. Instead, it is nothing but what the artist intended it to be and what the viewer interprets it as. It could be splashes of paint as we see in Jackson Pollocks work. It may also be the color-blocked squares that are frequent in Mark Rothkos paintings. The Meaning Is Subjective The beauty of nonrepresentational work is that it is up to us to give it meaning through our  own interpretation. Sure, if you look at the title of some piece of art you may get a glimpse into what the artist meant, but quite often thats just as obscure as the painting itself. It is quite the opposite of looking at a still life of a teapot and knowing that it is a teapot. Similarly, an abstract artist may use a Cubist approach to break down the geometry of the teapot, but you may still be able to see a teapot. If a nonrepresentational artist, on the other hand, was thinking of a teapot while painting a canvas, youd never know it. While this subjective point of view to nonrepresentational art offers freedom of interpretation to the viewer, it is also what bothers some people about the style. They want the art to be about something, so when they see seemingly random lines or perfectly shaded geometric shapes, it challenges what theyre used to. Examples of Nonrepresentational Art Dutch painter Piet Mondrian (1872–1944) is a perfect example of a nonrepresentational artist, and most people look to his work when defining this style. Mondrian labeled his work as neoplasticism, and he was a leader in De Stijl, a distinct Dutch complete abstraction movement. Mondrians work, such as Tableau I (1921), is flat; it is often a canvas filled with rectangles painted in primary colors and separated by thick, amazingly straight black lines. On the surface, it has no rhyme or reason, but it is captivating and inspiring nonetheless. The appeal is in the structural perfection combined with the asymmetrical balance, creating a juxtaposition of simple complexity. Confusion With Nonrepresentational Art Heres where the confusion with abstract and nonrepresentational art really comes into play: Many artists in the Abstract Expressionist movement were technically not painting abstracts. They were, in fact, painting nonrepresentational art. If you look through the work of Jackson Pollock (1912–1956), Mark Rothko (1903–1970), and Frank Stella (b. 1936), you will see shapes, lines, and colors, but no defined subjects. There are times in Pollocks work in which your eye grabs onto something, though thats simply your interpretation. Stella has some works that are indeed abstractions, yet most are nonrepresentational. These abstract expressionist painters are often not depicting anything; they are composing with no preconceived notions of the natural world. Compare their work to Paul Klee (1879–1940) or Joan Mirà ³ (1893–1983) and you will see the difference between abstraction and nonrepresentational art.

Characteristics Of Greek Mythology - 821 Words

The Ancient Greeks were known for believing in gods and goddesses, but they created these beings to be feared and related to. The Greeks used Mythology to better understand the world around them, but a few of the stories were purely for entertainment. Mythology was created by those who disliked the irrational, but loved facts. These mythologies consisted of the gods and goddesses encountering struggles, love, pain, and almost any human interaction. The Ancient Greeks applied the stories to overcome similar struggles in their own lives. Although these mythological deities were respected, they were not viewed as religious gods. Every god or goddess has a time to shine, but some had a bit more air time than others. Zeus is arguably the most†¦show more content†¦The theoretical absence of Zeus shows how different the Greek mythologies would be without this powerful god. Zeus appears in countless Greek mythologies, but an exceptionally important one involves Zeus’ father, Cronus. Cronus heard that one of his children were going to dethrone them when they grew up. Cronus response was to swallow all five of Zeus’ older siblings, including Poseidon, Hades, Hestia, Demeter, and Hera. Zeus’s mother, Rhea, wanted to protect her youngest child from being swallowed, so she devised a plan to save baby Zeus. Rhea disguised a stone as a child by wrapping it in swaddling clothes and feeding it to Cronus. Without a second thought, Cronus swallowed the fake, and Zeus was safely taken to the island of Crete where he was raised. When Zeus was fully grown he returned to challenge his father. First, he induced Cronus to throw up his five siblings, and then Zeus, his siblings, the cyclopes, and the hundred-handers started a ten-year battle that eventually overthrew Cronus. Zeus punished his father and the rebellious Titans by confining them to prison in Tartarus. This victory put Zeus in the position of king of the gods, and he chose to split divide up th e universe amongst his brothers. Olympus stayed common property, Poseidon got the sea, Hades had the underworld, and Zeus received the heavens. Although this was not the last of Zeus’ struggles, it did drastically impact his life by giving him considerable influence in theShow MoreRelatedGreek Mythology : The Origin Of The Stars And Sky1528 Words   |  7 PagesGreek mythology was very important in many cultures throughout the world and was utilized to clarify the earth and its circumstances in which mankind lived, the normal wonders they identified and how constellations explained the why the movement of the stars and sky were important in the lives of the Greeks. Greek mythology contained information about the livelihood of these gods and goddesses, humankind after death and simply how to live a joyous life. 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Statistical Methods and Data Analysis †Free Samples to Students

Question: Discuss about the Statistical Methods and Data Analysis. Answer: Introduction This section of the paper concentrates on the construction of a report that looks to define the process of data analysis and one of type of data analysis known as data mining. This section explains the process of data analysis and data mining and then discuses about the role of data mining in a contemporary organization (Aggarwal Reddy 2013). The paper even discuses about the recognition and explanation of ethical implications that requires to take place in order to gather, store and utilize the customer information for the process of data analysis. The process of data analysis is a vital tool for the development of an organization with respect to the information that are collected from the customers. Data analysis technique and software are severely used for the classification of the information that are obtained by the companies and thereby identifying the proclivities regarding the consumers and establish a sense of bonding. Gandomi Haider (2015) describes data mining as a type of data analysis technique that looks to discover the information that was hidden from the previous information by analysing the huge database. This process is undertaken in order to exploit the hidden data in an appropriate manner and thereby enhance the knowledge of the contemporary firm. Data mining is found to be the primary step for the revealing of the methods and gathering the information. The combination of data mining with the extraction of the data tries to enhance the understanding that web data or web-mining is the actual process of data mining and this process is along with the other processes are helpful in automatically discover and the obtain the data from the documents and the online services (Lin et al., 2013). This explanation of data mining is the most appropriate one for the concerned paper. Data mining functions by abiding by the ethical codes and the code of conducts and therefore limits the entry of any fr audulent activities thereby safeguarding the confidential information of the consumers. The safeguarding of the information maintains harmony within the society. The main objective of data mining other than extracting the information is protection of the information and the authoritarian standards that are established so that with the help of these standards, the firm can perform their practices as they are confident that the data that they are making use of safe from being stolen. Therefore it can be seen that with the implementation of data mining, the data collected are safe as the main function of data mining involves protection of the data. Role of Data Mining The initiation of the use of the online and web services leads to the extensive use of the customer information as the information that are given out by the consumers are collected by the companies and are stored and recorded as the these information can be used by the firms for future use and to have knowledge about the consumers in an efficient way. The use of data mining is helpful for the companies to understand the future trends that the consumers may have. The customers have knowledge that the information they provide to the organizations will be utilized by them and they have no issues with the utilization of the information unless the information are used for wrong purposes (Roiger 2017). The consumers do not wish their private information to be revealed by the organizations and therefore they try to share only the general information as much as possible. Therefore, the process of data mining is vital as it this technique has the ability to segregate the private information f rom the general one and then the companies can store the personal information in their core database so that these information are not leaked (Agarwal Dhar 2014). There are numerous reasons why the process of data mining is significant. With the advent of time, the benefits of data mining are understood by the organizations. Zaki et al., (2014) describes that with the use of this system, the confidential matters can be erased from the marketing suggestions and then the data permits the role of information sharing. The process of data mining take place in collaboration with the contemporary firm tries to exploit information about the desires that are demanded by the consumers. Data mining have mainly been used for the purpose of national security, and tracking of unscrupulous activities. However, recently the organizations have started using this method as it aids in discovering the products and services that are faulty. Larose (2014) even explains that the process data mining is influential for undertaking any researches and this technique helps the firms in understanding the expectations of the consumers from the organizations so that the com panies can live up to the expectations of the customers and change their strategies to satisfy them. The data mining technique is vital for the purpose of estimating the consumer patterns that will be available in the future and therefore the firms can initiate decisions that are knowledge based (Silverman 2016) . The process of data mining helps in answering the questions that arises in the minds of the companies and thereby rectifying the available issues. Data mining equipments buff up data bases for the hidden patterns and reveal the relevant information that may be overlooked by the researchers while completing their research (Miles et al., 2013). The mechanism of data mining consists of four aspects namely cite the data into the granary system; manage the database, examination of the data and accessibility of the information to the business researchers. Therefore, it can be said that data mining is a vital tool for statistical analysis. Explanation and Identification of Ethical Implication The investigation of the data mining ethics is important before the research starts. The ethical codes that are prepared by the organization regarding the ethical implication is based on the community and the culture that is prevalent in the concerned country. The ethical standards become the beliefs of the society and an idea about what is right and wrong can be determined (Ritchie et al., 2013). The ethical and unethical aspects are then properly understood by the firms with ease. The aspect of culture plays a vital role for the construction of the ethics that can be implemented by the organizations. Ott Longnecker (2015) describes ethics as the set of values that builds the behaviour of the individuals and the firms. One of the most significant ethical responsibilities of a company involves the looking after the sentiments of the customers and rectifying the discrepancies that are discovered in the obtained data. The implementation of ethics creates a strong bonding between the stakeholder and the company. The use of these codes creates a positive impact on the mind of the management if the firm (McKenzie et al., 2016). A harmonic work culture leads to better output from the firm. The ethical codes are created in order to satisfy the anxiety of the consumers regarding the originality of the ethics that are introduced by the management for undertaking decisions and therefore reveal that the organization is concerned about safeguarding the personal information and thereby gaining customer loyalty (Neuman 2016). The organization even concentrates on the fact of analyzing the ethical codes to construct data miner ethics. The implication of ethics leads to the constructions of strategies that have better confidence from the viewpoint of the data miners. The implication of ethics discovers the truthfulness of the data as the availability of any fraudulent information can injure the consumers lifestyle (Salazar et al., 2015). The information that are gathered by the industries are essential to be true and fair and thereby effective decisions can be taken by the management so that effective and comprehensive services can be given out by the firm according to the desires of the consumers (Garner Scott 2013). With respect to the accessibility of the data, it is seen that ethics play a vital role as the word of ethics helps preserving the information about the consumers (Bazeley 2013). The consumers are reluctant about sharing their information to others except the ones they share. The consumers share their information with the faith that their data will not be leaked to others for any fraudulent activities (Lewis 2015). The ethical implication within the firm restricts these activities as it creates an obligation to the employees and the management to safeguard the information of the consumers from being leaked out. Therefore the employees safeguard the information and the information can only used by the researchers and no else can access the central database (Carrington et al., 2014). Therefore the use of ethical implication leads to confidence among the consumers and they gain the assurance to share their original information to the organization, which in turn will give the firms with original results that can be used by the firm to obtain the accurate result for decision making. Conclusion The analysis of the paper reveals that data analysis and data mining is an important tool for the researchers in order to give out the best results that can improve the performance of the firm and can even up lift the life if the consumers. The role of data mining is discussed thereby understanding the need for data mining in modern companies. The next section deals with the ethical implications regarding the gathering, exploiting and storing the data as the use of ethics creates a good relationship among the consumers and the organizations and gains confidence among the consumers that their information is safe thereby influencing them to reveal the correct information that leads to appropriate results from the firms that would help them in decision making. Reference List Agarwal, R., Dhar, V. (2014). EditorialBig data, data science, and analytics: The opportunity and challenge for IS research. Aggarwal, C. C., Reddy, C. K. (Eds.). (2013).Data clustering: algorithms and applications. Chapman and Hall/CRC. Bazeley, P. (2013).Qualitative data analysis: Practical strategies. Sage. Carrington, M. J., Neville, B. A., Whitwell, G. J. (2014). Lost in translation: Exploring the ethical consumer intentionbehavior gap.Journal of Business Research,67(1), 2759-2767. Gandomi, A., Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics.International Journal of Information Management,35(2), 137-144. Garner, R., Scott, G. M. (2013).Doing qualitative research: designs, methods, and techniques. Pearson Education. Larose, D. T. (2014).Discovering knowledge in data: an introduction to data mining. John Wiley Sons. Lewis, S. (2015). Qualitative inquiry and research design: Choosing among five approaches.Health promotion practice, 1524839915580941. Lin, T. Y., Yao, Y. Y., Zadeh, L. A. (Eds.). (2013).Data mining, rough sets and granular computing(Vol. 95). Physica. McKenzie, J. F., Neiger, B. L., Thackeray, R. (2016).Planning, implementing evaluating health promotion programs: A primer. Pearson. Miles, M. B., Huberman, A. M., Saldana, J. (2013).Qualitative data analysis. Sage. Neuman, W. L. (2016).Understanding research. Pearson. Ott, R. L., Longnecker, M. T. (2015).An introduction to statistical methods and data analysis. Nelson Education. Ritchie, J., Lewis, J., Nicholls, C. M., Ormston, R. (Eds.). (2013).Qualitative research practice: A guide for social science students and researchers. Sage. Roiger, R. J. (2017).Data mining: A tutorial-based primer. CRC Press. Salazar, L. F., Crosby, R. A., DiClemente, R. J. (2015).Research methods in health promotion. John Wiley Sons. Silverman, D. (Ed.). (2016).Qualitative research. Sage. Zaki, M. J., MeiraJr, W., Meira, W. (2014).Data mining and analysis: fundamental concepts and algorithms. Cambridge University Press.