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Data hierarchy refers to the systematic organization of data, often in a hierarchical form. Data organization involves characters, fields, records, files and so on. [1] [2] This concept is a starting point when trying to see what makes up data and whether data has a structure. For example, how does a person make sense of data such as 'employee ...
The model of hierarchical complexity (MHC) is a formal theory and a mathematical psychology framework for scoring how complex a behavior is. [4] Developed by Michael Lamport Commons and colleagues, [3] it quantifies the order of hierarchical complexity of a task based on mathematical principles of how the information is organized, [5] in terms of information science.
The General Concept Lattice (GCL) proposes a novel general construction of concept hierarchy from formal context, where the conventional Formal Concept Lattice based on Formal Concept Analysis (FCA) only serves as a substructure. [1] [2] [3] The formal context is a data table of heterogeneous relations illustrating how objects carrying attributes.
Lattice Miner [1] is a formal concept analysis software tool for the construction, visualization and manipulation of concept lattices.It allows the generation of formal concepts and association rules as well as the transformation of formal contexts via apposition, subposition, reduction and object/attribute generalization, and the manipulation of concept lattices via approximation, projection ...
The COBWEB data structure is a hierarchy (tree) wherein each node represents a given concept. Each concept represents a set (actually, a multiset or bag) of objects, each object being represented as a binary-valued property list. The data associated with each tree node (i.e., concept) are the integer property counts for the objects in that concept.
The original motivation of formal concept analysis was the search for real-world meaning of mathematical order theory.One such possibility of very general nature is that data tables can be transformed into algebraic structures called complete lattices, and that these can be utilized for data visualization and interpretation.
A standard representation of the pyramid form of DIKW models, from 2007 and earlier. [1] [2]The DIKW pyramid, also known variously as the knowledge pyramid, knowledge hierarchy, information hierarchy, [1]: 163 DIKW hierarchy, wisdom hierarchy, data pyramid, and information pyramid, [citation needed] sometimes also stylized as a chain, [3]: 15 [4] refer to models of possible structural and ...
Data cannot be shared electronically with customers and suppliers, because the structure and meaning of data have not been standardised. To obtain optimal value from an implemented data model, it is very important to define standards that will ensure that data models will both meet business needs and be consistent.