Monday 16 May 2011

why classification matters in government #opengov #eim

David Brooks explores the complexity of translating government policy into action in this thoughtful NYT article, What government does.  As he notes, too often the complexity of government is not acknowledged when factions get caught up arguing purely ideological positions.  It is good to see someone as thoughtful as Brooks write on the challenges of meeting policy goals.

The government employees he observes recognize, as much as any company, that numbers matter.  Brooks praises a joint meeting between government agencies, noting with respect that “they had achieved a herculean task of getting two government agencies to agree on a single data set, a single methodology and a single progress report.”

But what exactly are the numbers measuring? To measure performance, it is necessary to define and disambiguate services.  As I described recently, defining, measuring and delivering government services is no easy project.  And it becomes increasingly complex as more departments and jurisdictions become involved.  Anyone practicing or studying classification, cataloging or information organization knows that describing the subject of something is deceptively complicated.  Yet agreeing on a common descriptive language is important for sharing knowledge, measurement and providing access to services.

Brooks touches on the complexity of classification and service modelling when he asks “how do you set up services for a homeless female veteran who has a drug addiction, psychiatric problems and is a victim of domestic violence?”  It’s clear there are multiple facets and attributes that can be broken down in any number of ways.  In the language of the Municipal Reference Model, this person would be called a “client” or “target audience” of multiple services.  In the language of library and information science, we would say this sentence is filled with impressively pre-coordinated subject headings or terms.

If anyone studying library and information science is worried that technology will somehow make their skills obsolete, don’t.  Technology for managing information in organizations is only as good as the conceptual models that are used to make sense of that information.

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