As a father of a five year old, I must admit that I get a chance to see some very interesting television programs. One particular program that comes to mind is Playhouse Disney’s Stanley. Stanley enjoys life with his talking dog Harry, Dennis the goldfish and Elsie the cat. However, my favorite thing on this show is "The Great Big Book of Everything." Talk about your active based meta data! Oh man, you should see this thing in action. Stanley opens the book and his gang of four are transformed into a learning experience; goldfish bowl and all. They may very well hunt with the cheetahs or experience the life cycle of a raindrop. Now that’s the kind of repository we need in the world of meta data. Simply open the repository and right in front of our eyes is everything we ever wanted to know about the subject. What if ...What if we had such a book that we wanted to know about our organization. Pardon me Stanley, may I borrow your book and open to the index.

Meta Data Services Group see Enterprise Data and Services, Enterprise Meta Data
Meta Data Strategy, 31-32
Repository Development Methodology, 31-39
BellSouth Repository Collection, Appendix B
Team Roles and Responsibilities 31, 48-89, 120
See also Portal Development; Corporate Data Architecture

This is too cool. A traditional index is, in fact, a map of the knowledge contained in a book; it lists the topics covered, by whatever name users might be expected to want to look them up, and includes relevant references to those topics. A basic index contains a list of topics and the occurrences (i.e., pages, numbers and appendices). These features can be seen in our index. Typographical conventions are used to distinguish between different types of topic (the names of the repositories are shown in italic). Similarly, typographical conventions are used to distinguish between different types of occurrence (references to physical teams are shown in bold). The use of "see" references handles synonyms by allowing multiple points of entry (by different names) to the same topic. The "see also" references point to associated topics or subtopics.

The basic utility described here falls under the concepts and principles defined by the body of knowledge referred to as topic maps. Figure 1 provides the basic constructs of a topic map, which include topics, associations, roles and occurrences.

Figure 1. Meta Data Topic Map Elements

A topic is just about anything you can think of. Figure 1 provides a collection of topics including: an organization, philosophies, repositories and owners. These topics represent a subject that is indexed. In general, there should only be a one-to- one relationship between subject and topics. Topics can be categorized according to their kind or role they play. Associations are the second construct utilized within the topic map framework. Although this index doesn’t explicitly describe the relationships between the topics, topic maps are built upon the idea that topics are related and these relationships can be described. Suppose we have an additional topic as "Todd Stephens." The relationship between "Meta Data Services Group" and me is one of leadership. Figure 2 offers an alternative view of the relationship between topics, roles, relationships and occurrences.

Figure 2. Sample Topic Map

The "Meta Data Services Group" topic, located at the lower left of the diagram, is related to the "Todd" topic with a relationship of "leadership." Additionally, the relationship between "Meta Data Services Group" and "repository" is one of "publishing." With each relationship or association, the topic plays a specific role. In my example, there is a leadership association and I play the role of technical director. Meta Data Service Group plays the role of SME and organizational representation.

The final construct is the occurrence. A topic may be linked to one or more information resources that are deemed to be relevant to the topic in some way. An occurrence could be an article about the topic on a Web site, a picture or video depicting the topic, a simple mention of the topic in the context of something else or a commentary on the topic, e.g., an XML standard. (WebReference, 2003). Figure 2 provides three repository occurrences linked to the "repository" topic, which includes XML, reuse and database meta data applications. In the next example, you will see that occurrences are represented by URLs which could be hidden from the user depending on the interface used.

Now, let’s flip a page or two in the "Great Big Book of Everything" to take a look at a better index entry that you might find more interesting. How about "Customer Entity"? Ah, here it is.

Customer Entity see Party, Consumer, Shopper, Buyer
Customer Logical Model, http://local.repository/LM/cust.pdf
Customer XML Schema Definition, http://local.repository/XML/cust1.xsd Industry Standard,
Enterprise Customer Database V1.2, MVS Server
Systems that Hold Customer Entity Data, http://local.repository/CRX/run.asp
XYZ Data Warehouse Server, Oracle Instance V8.1
Applications that Hold Customer Entity Data, http://local.repository/app.asp
Interfaces that Hold Customer Entity Data, http://local.repository/int/run.asp
Customer Data Steward; John Doe,
Reusable Components (Customer), http://local.repository/reuse.asp?custentity
See also Customer Data Warehouse I; Operational Data Store XYZ

I told you this book is great. Where do we start? The topics, roles, associations and occurrences are everywhere. Due to the brevity required in a monthly column, I won’t go into the details but I hope you take the time to explore the power of topic maps and the underlying concepts. Topic maps intrigue me to say the least. They are simple, understandable and extremely powerful. I encourage you to research the concepts around topic maps and unlike the "Great Big Book of Everything," topic maps are real and a current ISO standard. Could you build a dynamic index of the knowledge assets located through out your organization? If you had a solid set of repositories and the power of the topic map, the answer would undoubtedly be yes.

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