List of Figures | Semantics in Business Systems: The Savvy Managers Guide (The Savvy Managers Guides)

Chapter 1: Semantics—A Trillion-Dollar Cottage Industry

Figure 2.1: A highly simplified semantic representation of a sales contract.

Figure 3.1: Semantics = Data + Behavior.
Figure 3.2: Semantic interpretation and origination.
Figure 3.3: Message and meaning.
Figure 3.4: Application types based on their interactions.
Figure 3.5: Spreadsheet.
Figure 3.6: A small portion of a tax return.
Figure 3.7: Semanticness of applications.
Figure 3.8: Primary types of business processes.
Figure 3.9: Cutting with more (left) and less (right) capital investment.
Figure 3.10: Lathe with some automation.
Figure 3.11: Hard automation lathe.

Figure 4.1: Relative size of vocabularies.
Figure 4.2: Excerpt from a contract.
Figure 4.3: Excerpt from a legal opinion.
Figure 4.4: Two industries' vocabularies, barely overlapping.
Figure 4.5: The biologic taxonomy showing some related species.
Figure 4.6: Order codes.
Figure 4.7: Code that implies a category.
Figure 4.8: Diagnosis can be perplexing. (Original artwork created by Brian Loner, Fort Collins, CO, 2003.)
Figure 4.9: Garage door state machine.

Figure 5.1: Business correspondence.
Figure 5.2: A "structured data" version of Figure 5.1, as cast in a database.
Figure 5.3: A tagged form of the letter in Figure 5.1.
Figure 5.4: Electronic data interchange (EDI) data.
Figure 5.5: A fixed-field data record.
Figure 5.6: Conceptual model.
Figure 5.7: Semantic model.
Figure 5.8: High-level logical model.
Figure 5.9: Logical model, normalized with some attributes.
Figure 5.10: Physical data model.
Figure 5.11: Object model in a unified modeling language (UML) class diagram.
Figure 5.12: Object design in UML with inheritance.

Figure 6.1: Data and metadata.
Figure 6.2: As built metadata.
Figure 6.3: The data dictionary.
Figure 6.4: Active Data Dictionary.
Figure 6.5: CASE tools generating metadata and some code.
Figure 6.6: Data definition language and data manipulation language.
Figure 6.7: DTD schema with an SGML document.
Figure 6.8: Part of an XSD document.
Figure 6.9: Types of metadata.
Figure 6.10: A diatom. (Photograph by P. Roger Sweets.)
Figure 6.11: Any lot can have many samples.
Figure 6.12: Control charts showing actual results compared with control limits.
Figure 6.13: An early, typical relational design of the QC system.
Figure 6.14: The original design, with test data. AT, alpha time; SD, standard deviation; WD, wet density.
Figure 6.15: A metadata-inspired design.
Figure 6.16: The columns-to-rows pattern.

Figure 7.1: A model of interpretation.
Figure 7.2: Na ve assumption about translation ("wort" is German for "word").
Figure 7.3: Translation as words to meaning to words.
Figure 7.4: Semantics in two languages.
Figure 7.5: Expression is far easier than interpretation.
Figure 7.6: Smart Tags in Microsoft Office.

Figure 8.1: Human as information factory.
Figure 8.2: Partial automation of the information factory.
Figure 8.3: Business applications are form-oriented data entry.
Figure 8.4: Applications affect the world.
Figure 8.5: Door hinge with screw holes.
Figure 8.6: New door hinge.
Figure 8.7: Procedural code.
Figure 8.8: Declarative code.
Figure 8.9: Part of the model behind a user interface.
Figure 8.10: A sample rule.
Figure 8.11: Rule as data structure.
Figure 8.12: Rule-based approach versus procedural approach.
Figure 8.13: Simple price assignment, procedurally.
Figure 8.14: Slightly more complex procedural algorithm.
Figure 8.15: Rules for the pricing algorithm.
Figure 8.16: Evolution of rule usage.
Figure 8.17: A declared fact.
Figure 8.18: An asserted fact.
Figure 8.19: Business rules form a semantic ontology and use a domain ontology.

Figure 9.1: Typical tasks in an application development and implementation project (waterfall method).
Figure 9.2: Excerpt from a requirements document.
Figure 9.3: Typical tasks in a common off-the-shelf (COTS) package implementation.
Figure 9.4: Typical tasks in an iterative development methodology.

Figure 11.1: HTML snippet.
Figure 11.2: XML snippet.
Figure 11.3: Sculpture as a graph.
Figure 11.4: Sculpture as tables.
Figure 11.5: Data in the sculpture tables.
Figure 11.6: A query to get the "tree" from the tables.
Figure 11.7: A tree from a graph.
Figure 11.8: XML version of sculpture.
Figure 11.9: Standard gauge.
Figure 11.10: A tagged value.
Figure 11.11: DTD schema. PCDATA is not "politically correct data," it is "parsed character data." In other words, data in this position is expected to be ASCII or Unicode data that the parser will interpret. CDATA is character data that the parser is not meant to interpret (e.g., an image).
Figure 11.12: XSD schema.

Figure 13.1: SOAP is an "envelope" for transmitting an XML message.
Figure 13.2: Using WSDL.
Figure 13.3: A UDDI-based registry of Web Services.
Figure 13.4: Navigationally oriented user interface.
Figure 13.5: Composite applications consolidating information from several other systems.
Figure 13.6: A UDDI search for a Web Service.

Figure 14.1: Some key Semantic Web technologies (the lines represent "begats" relationships).
Figure 14.2: Basic RDF model.
Figure 14.3: Tim Bray and RDF.
Figure 14.4: Tim Bray and RDF as resources.
Figure 14.5: Tim Bray and RDF as resources.
Figure 14.6: A snippet of a genealogy ontology in Notation3.
Figure 14.7: Inference rules in the genealogy ontology.
Figure 14.8: Al's ontology commitment.
Figure 14.9: A hospital and a drug interaction database.