With info sharing, context is as important as content
Connecting state and local government leaders
Context is so critical that its implications are cropping up in more than a half-dozen areas of data architecture, such as process monitoring, business glossaries, master data management, metadata catalogs, information exchanges, data warehousing and much more, Reality Check columnist Michael Daconta writes.
Daconta is chief technology officer at Accelerated Information Management LLC and former metadata program manager at the Homeland Security Department. His latest book is entitled, “Information as Product: How to Deliver the Right Information to the Right Person at the Right Time.”
In commenting on the recent Shirley Sherrod incident, Fox News host Glenn Beck, among many other news commentators, said “context matters.” Context, which is the environment or situation surrounding a particular target, is also a critical component of federal data architectures that needs to be planned and implemented before an incident occurs in which it is needed.
Every chief information officer must ask, “How do we create a data architecture that captures the context around our federal records?” A rich context enables you to assemble a complex picture on the fly because you know where the puzzle pieces fit. In fact, context is so critical that I see its implications and implementations cropping up in more than a half-dozen areas of data architecture, such as process monitoring, business glossaries, master data management, metadata catalogs, information exchanges and data warehousing.
In this article, we will examine three information management projects in which context plays a key role in the solution.
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First, I was recently reviewing some Extensible Markup Language schemas that represented an important government form. The schema defines the document for the applicant’s responses, which will be reported to multiple agencies that need to take action on those responses. Unfortunately, the XML design failed to take into account anything outside that single form, while the context of the data on the form was relevant to a number of external systems and indirect consumers.
The problem is that a narrow, project-only perspective fails to capture the semantics needed for a larger audience. A simple example would be to think only about a single role that a person plays rather than thinking about a person who can play multiple roles — for example, employee or parent could be different roles of one person. I cannot overemphasize how critical this is to effective information sharing.
Second, I am supporting a master data management project that is integrating asset data across multiple information technology systems. The integrated product team is connecting data via its financial and geospatial context. Let’s briefly ponder those two contexts: One involves a source — in this case, a source of funds — and the other involves a static element. Sometimes, the context of the data can even be more important than the data itself. That is especially true when you are primarily concerned with connections among things.
Finally, a new contextual approach is emerging for developing information exchanges that holds great promise. Like the XML design problem of our first example, information exchanges can fall prey to an overly narrow perspective. Given that modern development platforms can automatically generate code to process XML documents, a narrow perspective can affect the exchange and any code that processes that exchange. The new approach being spearheaded by forward-thinking elements of the Army and Air Force is to create the semantics first, via a high-fidelity data model called an ontology, and then generate the XML schemas from that model.
Although not based on the Web Ontology Language, the National Information Exchange Model takes a similar approach, in which the XML schemas are generated from a database-backed data model. The contextual nature of this approach is that the ontology uses a more top-down, enterprise perspective to guide the inclusion of bottom-up exchanges.
The heightened awareness and use of context were mirrored on the commercial front by Google’s purchase of Metaweb and the company’s Freebase entity graph.
The elevation of context in our information management activities is a sign of a more aggressive attitude toward actively managing our data so that we can take advantage of its potential. The key to mastering context is to understand the role of metadata in your organization and how to effectively design it. Simply put, metadata captures context, whereas your data is content. If you can trace a line from your content to its context and then the consumer, you will have mastered your information.
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