Random Notes from Various Research
Knowledge Theory
From: http://www.kbs.twi.tudelft.nl/mmdb/ASC_2003_385-022.pdf
http://www.kbs.twi.tudelft.nl/mmdb/ASC_2003_385-023.pdf
List of all papers: http://www.kbs.twi.tudelft.nl/mmdb/research.html
Modeling Two types:
1) Modeling data with definite and inherent structural relationships. (such as relational modeling)
2) Modeling data with recursive and variable relationships. (such as XML)
Recursive Relationships:
A collection of objects O1,O2,..,On have a recursive relationship if O1 is defined on known concepts and On+1 is based on the definition of On.
Nesting Relationships:
(Non First Normal Form?)
Design
Apophenia – based on a Gibson novel – the experience of seeing patterns where they may not exists. False positive of pattern recognition. leads to bad design.
Types of Data
There are essentially five types of data in corporations:
- Unstructured—This is data found in e-mail, white papers like this, magazine articles, corporate intranet portals, product specifications, marketing collateral, and PDF files.
- Transactional—This is data related to sales, deliveries, invoices, trouble tickets, claims, and other monetary and non-monetary interactions.
- Metadata—This is data about other data and may reside in a formal repository or in various other forms such as XML documents, report definitions, column descriptions in a database, log files, connections, and configuration files.
- Hierarchical—Hierarchical data stores the relationships between other data. It may be stored as part of an accounting system or separately as descriptions of real-world relationships, such as company organizational structures or product lines. Hierarchical data is sometimes considered a super MDM domain, because it is critical to understanding and sometimes discovering the relationships between master data.
- Master—Master data are the critical nouns of a business and fall generally into four groupings: people, things, places, and concepts. Further categorizations within those groupings are called subject areas, domain areas, or entity types. For example, within people, there are customer, employee, and salesperson. Within things, there are product, part, store, and asset. Within concepts, there are things like contract, warrantee, and licenses. Finally, within places, there are office locations and geographic divisions. Some of these domain areas may be further divided. Customer may be further segmented, based on incentives and history. A company may have normal customers, as well as premiere and executive customers. Product may be further segmented by sector and industry. The requirements, life cycle, and CRUD cycle for a product in the Consumer Packaged Goods (CPG) sector is likely very different from those of the clothing industry. The granularity of domains is essentially determined by the magnitude of differences between the attributes of the entities within them.
