Johnny Data Can't Read

Captain Data Model Chronicles

When I started as data architect for Sun’s Web Publishing Engineering (WPE) department we were just coming out of pilot for Starlight, a unified content platform for Sun’s Web sites. (Back then, my team, Content Management Engineering - CME - didn't even exist yet!) As we began building Starlight, we had a few key goals: increased reuse, improved standardization and globalization. The system is a document-driven platform, which is a good thing, but back in its early days it suffered a bit from lack of a data modeler’s touch. I saw pretty quickly that it wouldn’t scale very well across the wide variety of applications on Sun’s Web space. We had to take a number of steps to improve the system to meet its ambitions.

At the beginning stage the document database was in what you can think of as preschool form. Documents, authoring and presentation templates were designed pretty much ad-hoc, as business needs drove them. There was no real organization to any of this, so that very often when similar needs came along later on, people ended up reinventing the wheel. This led to inefficiency throughout the content life-cycle. On one end, authors would have to get used to multiple templates to create similar documents. On the other end those developing Web applications on Starlight had to create multiple overlapping presentation templates. As a result the workflow was quite a tangle, as I illustrate below.

The first step was to formalize document design. Starlight initially focused on marketing Sun products, and we were exploring how we could better share content and data between the product marketing sites and the various e-commerce sites worldwide. This became an effort to create a Unified Product Data Model (UPDM). We then applied UPDM to formalize the design of many of the Starlight documents, and we used the extensibility of UPDM to establish a model for pages not as closely identified with products. I’d love to discuss UPDM more, because it was a core achievement that provided a foundation for so much of what followed, but for now I’ll continue with the main story.

Once we’d formalized document structures we could identify redundant templates and combine them, and we could also make the workflow much clearer and more efficient. We were able to accomplish this back in 2005 smoothly enough that you probably didn’t notice. For the most part, we made no change to the CMS toolkit or personnel, nor to the resulting pages. All we did was apply data architecture to make these more efficient. Call it data grammar school, illustrated in the following diagram.

Much less confusion. The document design is clearly defined, which makes it easier for Web applications to identify and pull the content they require, and makes useful middleware out of the ad-hoc authoring and presentation support tools. But regardless of how carefully you try to control the proliferation of document templates, you can’t fit every new need into existing ones. You may never regress all the way back to the chaos of preschool, but over time you can definitely lose some of the benefits of all the careful organization. As Starlight grew in application we quickly saw that we needed to organize things even further.

A Web space as broad as Sun’s may have thousands of different permutations of source documents and presentation pages, but for the most part there are basics that you use over and over again. You have titles, links, keywords, images, personal and organizational contact information, prose snippets, and so on. We turned that into a library of document components, defined in RELAX NG, and incorporating UPDM and other standards from inside and outside Sun (as an example of the latter we heavily reused components from XHTML 2.0). As such most of the document templates became nothing more than a bunch of components snapped together, so that the complexity of the middleware and application query no longer has to scale as dramatically with the number of document templates.

At the same time, we had to re-engineer our rendering technology to take advantage of componentization of content. Parallel to our library of document components there is a separate Sun project, Web Design Standards, that defines in fine detail how Sun material should be presented on the Web. We organized our rendering templates so that they gather the needed content components as input, and generate the needed Web Design components as output. The result is a system where building blocks can be readily identified and reused throughout the publication process. Call it data college.

At this point we have the foundations for efficiently creating and routing content, allowing publishers to focus on what they want to communicate and enable in their Web applications. Of course this is only the jumping-off point for tackling even harder problems, such as how to better find and sell our products and services, and how to engage the community more readily on the Web. These are the challenges to which we’ve turned our attention in the past year or so, and the most important factor allowing us to deal with these grown up problems is that finally, at least in CME, Johnny Data can read -- and write.

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About

Passionate about data engineering strategy and solutions for Sun’s external web sites. Happiest when building taxonomies, data models, and high performing teams.

Kristen Harris
Director,
Web Data Engineering

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