by Clark Humphrey
In our last article, we discussed the origins of the term “Information Architecture” (IA), and how the term is defined differently within different branches of IT and Library/Information Science.
This time, we’ll focus on various ways IA is defined within the database world.
Most definitions of IA in the enterprise describe it as an overall system of planning for an organization’s entire information/IT needs.
IASA (“An Association for All IT Architects”) defines IA as:
“…the art of expressing a model or concept of information used in activities that require explicit details of complex systems. Among these activities are library systems, Content Management Systems, web development, user interactions, database development, programming, technical writing, enterprise architecture, and critical system software design. Information architecture has somewhat different meanings in these different branches of IS or IT architecture. Most definitions have common qualities: a structural design of shared environments, methods of organizing and labeling websites, intranets, and online communities, and ways of bringing the principles of design and architecture to the digital landscape.”
Hayley Carter, writing for the journal Work Study, invokes IA as an approach for that modern DB problem of merging information from multiple legacy computer systems:
“Most organizations, in spite of the attention and investment focused on ERP software, have a number of discrete computer systems that operate independently of one another. In addition to the problems of unmanageability, this results in an inability to fully exploit the information resources available. The concept of an information architecture, which draws on the architectural profession, is an attempt to focus discipline on the design and building of information systems, to facilitate prioritization and decision making, in support of business strategy.”1
Carter (as quoted in the Journal of Information Architecture), further describes his vision of IA in large organizations:
“…a holistic way of planning which meets the organization’s information needs and avoids duplication, dispersion, and consolidation issues. The information architecture is the collective term used to describe the various components of the overall information infrastructure, which take the business model and the component business processes and deliver information systems that support and deliver it. Prime components are the data architecture, the systems architecture and the computer architecture.”
Paul Nielsen, who describes himself as a “Microsoft SQL Server Data Architect,” offers his own “Information Architecture Principle” as a foundation for understanding the concept of IA as he sees it:
“Information is an organizational asset, and, according to its value and scope, must be organized, inventoried, secured, and made readily available in a usable format for daily operations and analysis by individuals, groups, and processes, both today and in the future.”
Nielsen’s statement means, among other things, that data must not get locked up in proprietary file formats that could become obsolete: “Current designs must be de-coupled to avoid locking the data in a rigid, but brittle, database.”
In his presentation “Information Systems Planning and the Database Design Process”, Ray R. Larsen of UC Berkeley defines IA, or “Information Systems Architecture” (ISA), as a framework for “‘enterprise-wide’ computing.” Larsen asserts that “to support enterprise-wide computing, there must be enterprise-wide planning,” but that “most organizations “do NOT have that architecture.”2
Larsen quotes Fred R. McFadden, co-author of the textbook Modern Database Management, in describing an ISA as a “conceptual blueprint or plan that expresses the desired future structure for information systems in an organization.” It provides a “context within which managers throughout the organization can make consistent decisions concerning their information systems.”
A contrary definition states that every organization already has an IA, whether it was deliberately designed or not. And, depending on its size and complexity, you may be stuck with the IA you’ve got.
Peter Aiken, Ph.D. of Data Blueprint says,
“All organizations have information architectures (IA). The question is: How effectively do they use these assets? It is rare that organizations are satisfied with their existing information architecture–i.e., the support it provides for their business strategy. Thus, improving their existing information architecture is an important goal for all data managers. Since information architectures are inherited and cannot be simply replaced, the only practical approach here is to improve by re-engineering specific components.”
Others insist that large legacy architectures can, and should, be updated and upgraded.
A 2011 Oracle paper on “Revitalizing Your Information Architecture Initiative” asserts that today’s explosive growth in the amount of data being generated, analyzed, and stored:
“…presents huge IT challenges, especially for corporations where information architecture is highly segmented, lacking standards, or dependent on aging components. As a result of these challenges, organizations spend billions of dollars in managing their Information Technology instead of focusing on their core business challenges.
“In contrast, modern, standards-based information architecture provides readily accessible, secured, trusted information that enables business performance and dramatically lowers costs.”
As Envizion Information Strategies puts it on a promotional website for its services:
“For Information Systems, there are often cases where large applications are built, with little or no consideration for the essential role of architecture. It is not difficult to find examples of large failed projects, which might have had better chances of success if more time was invested to be sure that the Information Architecture was correct.
“Information Architecture includes plans, principles, models, standards, guidelines and the supporting organization to ensure that the information deliver business value and aligns the enabling Information Technology with business objectives, as formulated by the stakeholders. Information Architecture is a coherent set of models with Information as the focal point of management.”
Envizion’s site also promotes the idea of “data” and “information” as two different subjects:
“The unprecedented information explosion in recent years has resulted in a ‘data rich, information poor’ situation today in many organizations, hindering their operations, often making it difficult to analyze or improve their business, or comply with regulations.”
As we have covered in previous articles, the various descriptions of Database Information Architecture (as opposed to “Data Architecture”) seem to fall into two main categories:
Integrating, into your DB, records and documents that fall outside the realms of structured “data;”
Enabling the kinds of metadata analysis that lead beyond mere number crunching and toward “big picture” business decision-making and planning.
Despite the notion of IA as an all-encompassing “blueprint” for Information Management, some warn against making your enterprise information project too all-encompassing.
One of these is Dr. David Loffredo. Writing at Microsoft’s Developer Network site, Loffredo says:
“While information architecture is a central aspect of many projects, an architect who strays into irrelevancy will never succeed. There are three areas in which it is particularly easy to stray from the path.
“…It is crucial to set bounds on a project; and, with information models, even more so. It is easy to keep going. Someone always wants to do a bit more; the siren song of “completeness” has drawn many off into irrelevant waters.”
Looking for a longer view? The British IT consulting firm Tellura has a web page describing IA, and the disciplines which, in Tellura’s view, IA does and does not encompass.
References
1. Hayley Carter, (1999) “Information architecture”, Work Study, Vol. 48/5, pp.182 – 185.
2. Fred R. McFadden, Jeffrey A. Hoffern, and Mary R. Prescott, Modern Database Management, Seventh Edition. Pearson Education, 2005.
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