Data Warehousing, Spatial Data Warehousing, and Data Marts

• Deriving or extracting aggregate data or views (e.g., database content slices) from primary enterprise transaction databases for online analysis and processing (OLAP)
• Employs "snowflake schema" as warehouse database data model (Example )
• Also sometimes referred to as "multi-dimension databases"
• Spatial data warehousing used to manage geographic, terrain, or other large data bases designed for data visualization and visual navigation (e.g., fly-overs)
• Case Study: Microsoft's TerraServer for spatial data warehousing
• UCI GSM Building from above
  
• Data marts are smaller-scale data warehouses
• Employed by small-medium size firms that seek the potential benefits of data mining from existing transaction databases

Data or Information Discovery

• Where is the data or information I need?
• Search Engines (e.g., altavista.com) and Index Servers (e.g., yahoo.com)
• Information Discovery: Internet, LAN, PC
• Personal Web site crawling (indexing) and posting on Web search engine (e.g., http://www.google.com/services/free.html )
• Web Farming: the systematic refining of Web-based information for business intelligence
• Data Mining a Data Warehouse, Data Mart, or Data Base
• Building and extracting views characterizing underlying data values
• OnLine Analytical Processing (OLAP)
• Query mechanisms designed to build Data Warehouses, or to support Decision Support applications and computations (e.g., clustering, concept formation)
• Report Generation/Visualization from Data Warehouses, Data Marts, Web
• Knowledge Discovery and Deductive Information Retrieval
• Deriving data relationships "hidden" in transaction database instance values

Knowledge Management

• Knowledge (possessed-- "know-what") vs. Knowing (knowledge practiced--"know-how: been there, done that")
• Formal knowledge representation schemes
• Semantic network data models (example )
• Shared ontologies (database with metadata content) and domain-specific terminology/notation
• Hierarchical Object-Relational Classification Schemes and Taxonomies
• Biological Classification Schemes (Kingdoms, Phyla, Classes, Orders, Families, Genera, and Species after Linneaus)
• Common Taxonomies
• Family Trees (Parent-Child): Child inherits attributes of Parent
• Abstraction (Whole-Part): Part belongs to, share interfaces, methods, and fits within Whole
• Genericity (General-to-specific): Industry, enterprise, division, department, group, individual
• Faceted or Hierarchical Naming Schemes
• Global telephone numbers -- 01-1-949-824-4130
• Internet Domain Names -- mobile01.gsm.uci.edu
• Sorting Things Out: Classification and its Consequences, MIT Press, 1999.
  
• Stories: Narrative (or multi-media) descriptions of knowledge/knowledge
• "Case studies"
• "Lessons Learned"
• "Best Practices" (example)
• Training materials with user annotations 
• Virtual learning and Web-based distance learning support environments 
• Engines for Education
• Scenarios and Simulations
• Manual, person-in-the-loop simulators (e.g., flight simulators), or network/process/workflow simulation packages 
• M. Schrage and T. Peters, Serious Play: How the World's Best Companies Simulate to Innovate , 1999.
• Work Practices -- ad hoc problem solving work and information flow
• Elicit, capture, analyze, and situated improvement 
• Source for best practices
• Intelligence Gathering (also surveillance and reconnaissance)
• Shared repositories (cf. Lotus Notes)
• Electronic documents (e.g., scan and OCR paper documents, save in e-doc repository or DB)
• Web site search and retrieval
• Email correspondence analysis 
• cf. Brint.com

• Content Analysis (cf. Autonomy.com, Semio.com)
• Filtering and Clustering
• Keyword and Concept Recognition 
• Content Management Systems 
• Web Portals 
• CRM 
• Example CMS: Zope (Flash demo)