Data - Wikipedia Jump to content Main menu Main menu move to sidebar hide Navigation Main page Contents Current events Random article About Wikipedia Contact us Contribute Help Learn to edit Community portal Recent changes Upload file Special pages Search Search Appearance Donate Create account Log in Personal tools Donate Create account Log in Contents move to sidebar hide (Top) 1 Etymology and terminology 2 Meaning 3 Data sources 4 Data documents Toggle Data documents subsection 4.1 Data collection 5 Data longevity, accessibility and reliability 6 In other fields 7 See also 8 References 9 External links Toggle the table of contents Data 104 languages Afrikaans العربية مصرى Asturianu Azərbaycanca تۆرکجه Беларуская Български বাংলা Bosanski Català Chavacano de Zamboanga کوردی Čeština Чӑвашла Cymraeg Dansk Deutsch Ελληνικά Esperanto Español Eesti Euskara فارسی Suomi Français Frysk Gaeilge Galego گیلکی Avañe'ẽ Hausa עברית हिन्दी Hrvatski Magyar Հայերեն Interlingua Bahasa Indonesia Ido Íslenska Italiano 日本語 La .lojban. 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For the journal, see Scientific Data (journal). For data in computer science, see Data (computer science). For other uses, see Data (disambiguation) and Datum (disambiguation). These are some of the different types of data: Geographical, Cultural, Scientific, Financial, Statistical, Meteorological, Natural, Transport Part of a series on Epistemology Outline Category Schools Coherentism Contextualism Dogmatism Empiricism Fallibilism Fideism Foundationalism Infallibilism Infinitism Naturalism Perspectivism Pragmatism Rationalism Relativism Skepticism Solipsism Structuralism Concepts Action Analytic–synthetic distinction A priori and a posteriori Belief Credence Certainty Data Experience Information Justification Induction Knowledge Meaning Rationality Reason Truth Wisdom Domains Applied epistemology Evolutionary epistemology Formal epistemology Historical epistemology Metaepistemology Social epistemology Virtue epistemology Epistemologists Aristotle Sextus Empiricus Edmund Gettier Wang Yangming René Descartes David Hume Immanuel Kant W. V. O. Quine more... Related fields Epistemic cognition Epistemic logic Philosophy of perception Philosophy of science v t e Data (/ˈdeɪtə/ DAY-tə, US also /ˈdætə/ DAT-ə) is a collection of discrete or continuous values that conveys information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A data point or datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and may itself be used as data in larger structures. Data may be used as variables in a computational process.[1][2] Data may represent abstract ideas or concrete measurements.[3] Data is commonly used in scientific research, economics, and virtually every other form of human organizational activity. Examples of data sets include price indices (such as the consumer price index), unemployment rates, literacy rates, and census data. In this context, data represents the raw facts and figures from which useful information can be extracted. Data is collected using techniques such as measurement, observation, query, or analysis, and is typically represented as numbers or characters that may be further processed. Field data is data that is collected in an uncontrolled, in-situ environment. Experimental data is data that is generated in the course of a controlled scientific experiment. Data is analyzed using techniques such as calculation, reasoning, discussion, presentation, visualization, or other forms of post-analysis. Prior to analysis, raw data (or unprocessed data) is typically cleaned: Outliers are removed, and obvious instrument or data entry errors are corrected. Data can be seen as the smallest unit of factual information that can be used as a basis for calculation, reasoning, or discussion. Data can range from abstract ideas to concrete measurements, including, but not limited to, statistics. Thematically connected data presented in some relevant context can be viewed as information. Contextually connected pieces of information can then be described as data insights or intelligence. The stock of insights and intelligence that accumulate over time, resulting from the synthesis of data into information, can then be described as knowledge. Data has been described as "the new oil of the digital economy".[4][5] Data, as a general concept, refers to the fact that some existing information or knowledge is represented or coded in some form suitable for better usage or processing. Advances in computing technologies have led to the advent of big data, which generally refers to very large quantities of data, typically at the petabyte scale. If restricted to traditional data analysis methods and computing, working with such large (and growing) datasets is difficult, even impossible. In response, the relatively new field of data science uses machine learning (and other artificial intelligence) methods that allow for efficient applications of analytic methods to big data. Etymology and terminology [edit source] Further information: Data (word) The Latin word data is the plural of datum, "(something) given", which is the neuter past participle of dare, "to give".[6] The first English use of the word data is from the 1645[7]. Data was first used to mean "transmissible and storable computer information" in 1946. The expression data processing was first used in 1954.[6] When data is used more generally as a synonym for information, it is treated as a mass noun in singular form. This usage is common in everyday language and in technical and scientific fields such as software development and computer science. One example of this usage is the term big data. When used more specifically to refer to the processing and analysis of sets of data, the term retains its plural form, a usage that has grown in popularity in the 20th and 21st centuries, being common in the natural sciences, life sciences, social sciences, computer science, and in software engineering. Some style guides do not recognize the different meanings of the term and simply recommend the form that best suits the target audience of the guide; for example, APA style as of the 7th edition requires data to be treated as a plural form.[8] Meaning [edit source] Adrien Auzout's "A TABLE of the Apertures of Object-Glasses" from a 1665 article in Philosophical Transactions See also: DIKW pyramid Data, information, knowledge, and wisdom are closely related concepts, but each has its role concerning the other, and each term has its meaning. According to a common view, data are collected and analyzed, and become decisionmaking-suitable information only after having been analyzed in some fashion.[9] One can say that the extent to which a set of data is informative to someone depends on the extent to which it is unexpected by that person. The amount of information contained in a data stream may be characterized by its Shannon entropy. Knowledge is the awareness of its environment that some entity possesses, whereas data merely communicates that knowledge. For example, the entry in a database specifying the height of Mount Everest is a datum that communicates a precisely measured value. This measurement may be included in a book along with other data on Mount Everest to describe the mountain in a manner useful for those who wish to decide on the best method to climb it. Awareness of the characteristics represented by this data is knowledge. Data are often assumed to be the least abstract concept, information the next least, and knowledge the most abstract.[10] In this view, data becomes information by interpretation; e.g., the height of Mount Everest is generally considered "data", a book on Mount Everest geological characteristics may be considered "information", and a climber's guidebook containing practical information on the best way to reach Mount Everest's peak may be considered "knowledge". "Information" bears a diversity of meanings that range from everyday usage to technical use. This view, however, has also been argued to reverse how data emerges from information, and information from knowledge.[11] Generally speaking, the concept of information is closely related to notions of constraint, communication, control, data, form, instruction, knowledge, meaning, mental stimulus, pattern, perception, and representation. Beynon-Davies uses the concept of a sign to differentiate between data and information; data is a series of symbols, while information occurs when the symbols are used to refer to something.[12][13] Before the development of computing devices and machines, people had to manually collect data and impose patterns on it. With the development of computing devices and machines, these devices can also collect data. In the 2010s, computers were widely used in many fields to collect data and sort or process it, in disciplines ranging from marketing, analysis of social service usage by citizens to scientific research. These patterns in the data are seen as information that can be used to enhance knowledge. These patterns may be interpreted as "truth" (though "truth" can be a subjective concept) and may be authorized as aesthetic and ethical criteria in some disciplines or cultures. Events that leave behind perceivable physical or virtual remains can be traced back through data. Marks are no longer considered data once the link between the mark and observation is broken.[14] Mechanical computing devices are classified according to how they represent data. An analog computer represents a datum as a voltage, distance, position, or other physical quantity. A digital computer represents a piece of data as a sequence of symbols drawn from a fixed alphabet. The most common digital computers use a binary alphabet, that is, an alphabet of two characters typically denoted "0" and "1". More familiar representations, such as numbers or letters, are then constructed from the binary alphabet. Some special forms of data are distinguished. A computer program is a collection of data, that can be interpreted as instructions. Most computer languages make a distinction between programs and the other data on which programs operate, but in some languages, notably Lisp and similar languages, programs are essentially indistinguishable from other data. It is also useful to distinguish metadata, that is, a description of other data. A similar yet earlier t…