Don't Like the Data in a Government Publication?
GOVERNMENT – DATA QUALITY REPORT, HEAL THYSELF:Center for American Progress Report: July 14th, 2004
According to a new study by OMB Watch, a recent report by the Office of Management and Budget about challenges to the quality of data in government reports was riddled with errors.
Some mistakes were factual: For example, while OMB claims that agencies only had 35 information quality challenges last year, the actual number is 98 – "nearly triple the number in the report." And although the OMB report claims "most" information quality challenges "that were denied were appealed," in reality, only 28 percent of denied challenges were appealed -- clearly not "most."
Some mistakes were misleading: critics feared information quality challenges would be dominated by interested industries. OMB accurately points out that a wide range of stakeholders have filed information quality challenges. What they failed to disclose, however, was that "72 percent of the challenges - nearly three-quarters - were from industry."
Note: The Guidelines for Ensuring and Maximizing the Quality, Objectivity, Utility, and Integrity of Information Disseminated by Federal Agencies by the Office of Management and Budget are progressive, and meaningful. One of the key elements is objectivity of data, which the OMB defined thusly:
"Objectivity" involves two distinct elements, presentation and substance.
"Objectivity" includes whether disseminated information is being presented in an accurate, clear, complete, and unbiased manner. This involves whether the information is presented within a proper context. Sometimes, in disseminating certain types of information to the public, other information must also be disseminated in order to ensure an accurate, clear, complete, and unbiased presentation. Also, the agency needs to identify the sources of the disseminated information (to the extent possible, consistent with confidentiality protections) and, in a scientific or statistical context, the supporting data and models, so that the public can assess for itself whether there may be some reason to question the objectivity of the sources. Where appropriate, supporting data should have full, accurate, transparent documentation, and error sources affecting data quality should be identified and disclosed to users.
In addition, "objectivity" involves a focus on ensuring accurate, reliable, and unbiased information. In a scientific or statistical context, the original or supporting data shall be generated, and the analytical results shall be developed, using sound statistical and research methods.
If the results have been subject to formal, independent, external peer review, the information can generally be considered of acceptable objectivity.
In those situations involving influential scientific or statistical information, the results must be capable of being substantially reproduced, if the original or supporting data are independently analyzed using the same models. Reproducibility does not mean that the original or supporting data have to be capable of being replicated through new experiments, samples or tests.
Making the data and models publicly available will assist in determining whether analytical results are capable of being substantially reproduced. However, these guidelines do not alter the otherwise applicable standards and procedures for determining when and how information is disclosed. Thus, the objectivity standard does not override other compelling interests, such as privacy, trade secret, and other confidentiality protections.And here is where the slippery slope toward biased data finds it's justification
...now all that we need is for journalists, pundits, and authors en masse to incorporate the principle and practice of this concept in their works! Failing this inclusion we can easily end up with subjective data points that have no independent validity in fact or reality as discernable by a neutral party, and objective truth degrades into opinions which have much less value in guiding decisions and actions.
Applying a label such as Liberal or Conservative to opinions, decisions, and rulings by an Administration Agency is no where near as potentially destructive to reasoned enquiry as would Government agencies failure to adhere to the principle and practice of providing objective data in their reports.
posted by Richard at
Wednesday, July 14, 2004
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