Saturday, January 19, 2019

Data and Meaning Part 4: Query and Result Correctness


As we have seen in Parts 1, 2, and 3, the RDM is a formal theory adapted and applied to database management: database relations (1) preserve the formal properties of mathematical relations, but also (2) have interpretations -- carry a real world meaning assigned by a conceptual model: facts about entities, entity groups, and multigroups (i.e., their properties, some of which are relationships, specified by business rules (BR)). A relation is formally in 5NF and constrained for semantic consistency (i.e., to represent facts about an entity group).
“When we create specific domains, relations, and attributes we are constraining (restricting) an abstract logical system to a specific interpretation (meaning). Seen the other way around, an interpretation of the logical system is a representation of a specific segment of the world, and that is exactly the purpose of database design. For example, an attribute name created by the designer is assigned meaning intended by the modeler as representing an entity property, which is the very meaning of semantics. That is why full normalization cannot be achieved or assessed without reference to some conceptual model -- what attribute names mean, and how they are related to each other (i.e., their dependencies), and so on.” --David McGoveran
Yet requesting and giving design advice without a conceptual model is routine in the industry[1]. What is more, most practitioners are oblivious to the implications for correctness of queries and results[2].

Wednesday, January 9, 2019

Data and Meaning Part 3: Database Design


We have seen in Part 2 that the meaning of data in a database is the conceptual model that the database is intended to represent, namely (1) the three types of objects -- entities of multiple types that form entity groups that form a multigroup -- and (2) the business rules (BR) that specify their properties:
  • Properties in context (PiC) shared by entities of each type;
  • Collective group properties (i.e., relationships among entity group members);
  • Multigroup properties (i.e., inter-group relationships).
Often somebody produces one or more tables and asks if there's "anything wrong" with them,  or "if they are in some specific normal form and, if not, how to normalize them". This reflects lack of foundation knowledge. 

Tuesday, January 1, 2019

Data and Meaning Part 2: Types of Business Rules

 
Meaning is captured during conceptual modeling as information about objects of interest, specifically their properties (some of which are relationships), specified in business rules (BR). Because they are expressed informally in natural language, objects and BRs must be formalized into computable form. Data modeling (we prefer logical database design) uses a formal data model to formalize informal conceptual models as formal logical models for database representation: it assigns the meaning in the former to symbols and expressions in the latter[2]. Using the RDM:

  • Objects -- entities, entity groups, and multigroups -- formalize as tuples, relations, and databases, respectively;
  • Entity properties formalize as domains, and when associated with entities, as attributes;
  • Group and multigroup properties -- relationships among entities, and among groups[3] -- formalize as constraints on and among relations enforceable by the DBMS.