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Synchrony and diachrony are two complementary viewpoints in linguistic analysis. A synchronic approach (from Ancient Greek: συν- "together" and χρόνος "time") considers a language at a moment in time without taking its history into account. Synchronic linguistics aims at describing a language at a specific point of time, often the present.
DIKW pyramid: Each step up the pyramid creates value based on the initial data, and can be used to answer high-level questions. The DIKW pyramid, also known variously as the DIKW hierarchy, wisdom hierarchy, knowledge hierarchy, information hierarchy, information pyramid, and the data pyramid, [1] refers to a class of models [2] representing purported structural or functional relationships ...
In ethics, intrinsic value is a property of anything that is valuable on its own. Intrinsic value is in contrast to instrumental value (also known as extrinsic value), which is a property of anything that derives its value from a relation to another intrinsically valuable thing. [1] Intrinsic value is always something that an object has "in ...
OpenAlex [32] is an open catalog of scholarly papers, authors, institutions, and more. OpenAlex launched in January 2022 with a free API and data snapshot. [33] The purpose of OpenAlex is to catalog publication sources, author information, and research topics.
Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. [1] Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science ...
Data valuation. Data valuation is a discipline in the fields of accounting and information economics. [1] It is concerned with methods to calculate the value of data collected, stored, analyzed and traded by organizations. This valuation depends on the type, reliability and field of data.
Data science is "a concept to unify statistics, data analysis, informatics, and their related methods " to "understand and analyze actual phenomena " with data. [5] It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. [6]
In statistics, homogeneity and its opposite, heterogeneity, arise in describing the properties of a dataset, or several datasets. They relate to the validity of the often convenient assumption that the statistical properties of any one part of an overall dataset are the same as any other part. In meta-analysis, which combines the data from ...