20 Mar dimension
In physical space, a dimension refers to an abstract measure of direction. The first dimension may be described as length: a straight line has distance and direction. The second dimension is width. With these two dimensions we can create geometrical representations of information. The bell curve is a two-dimensional representation. The third dimension is depth. All objects in the physical universe have three dimensions. Other dimensions are duration and speed.
Keywords: abstraction
object
chaos
representation
References: context
knowledge representation
logic
taxonomy
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[…] In most operating business information models, database tables, rows and columns implicitly represent associations, though the exact nature of the associations may be undocumented. Associations in a database table are defined by the records in each row and named attributes in each column. The name of the table tells the symbolic association that is reflected in the rows: all the values in each row are associated the named instance at the head of the row. That could be the name of a person or product or the ID number of an order. Attribute relationships are reflected in the column names: every column of information shows an attribute of the head of each row. Two important elements or meaning are missing from the relational database model: explanation of where information elements fit into the overall enterprise hierarchy or ontology, and how information objects are associated with processes or capabilities. Both instance (row) and attribute (column) are hierarchical type associations. The added dimension in relational databases with primary and foreign keys enables us to express functional relationships of any arity, cardinality or modality (one-to-one, one-to-many, many-to-many). These are represented in the gray-scale image above as lines with different endings depending on the relationship. The relational model is a good representation for holding information on functions or transactions in day-to-day business, such as “orders” and “customers”, though it doesn’t necessarily reduce the amount of brain power required to interpret the data, though it provides needed context. Before relational databases, we had flat databases. Flat database models are conceptually one dimensional. A single dimension reflects only hierarchical or physical relations. Relational models add the conceptual dimension of function, making them conceptually two-dimensional. Object model databases can reflect even more dimensions. […]