Oversight

GAO frets about ambiguity in Data Act standards

Shutterstock image: financial data, magnifying glass.

The Digital Accountability and Transparency Act of 2014 requires the government to publish a detailed accounting of federal spending in uniform, machine-readable format on the USAspending.gov website, so the government is trying to get agencies on the same page when it comes to standards for that data.

According to a report from the Government Accountability Office released Jan. 29, some of the standardized data element definitions offered by the Treasury Department and the Office of Management and Budget are potentially unclear and inconsistent, and they leave too much room for interpretation.

The GAO report, required under the Data Act, is generally complimentary of government efforts. All of the 57 standard data elements required to track federal spending under the Data Act comport with international accounting best practices. Auditors wrote that "even the lowest-rated data elements in our review adhered to almost 70 percent of the...leading practices" of the International Organization for Standardization.

However, some of the data elements on place of performance and what constitutes program activity are open to multiple interpretations.

In a letter to OMB Director Shaun Donovan, members of the House Oversight and Government Reform Committee wrote that the potential for discrepancies creates the "risk of reporting data that cannot be aggregated," and "without the timely issuance of final guidance, federal agencies may not have the information needed to effectively implement Data Act standards by the statutory deadline" in 2017.

"This report is really important," Hudson Hollister, founder and executive director of the Data Transparency Coalition, told FCW. "OMB and Treasury need to come up with clear, technical instruction as to how to link the financial and award reporting in order to create transparency. Without clear instruction, agencies cannot plan."

Agencies were required to submit program and spending activity under the new standards by the end of January. According to OMB's reply to the GAO report, agencies had submitted more than 250,000 lines of accounting data so far.

GAO recommended that OMB and Treasury clarify the ambiguous definitions, and the agencies generally concurred with the recommendations, according to the report.

About the Author

Chase Gunter is a staff writer covering civilian agencies, workforce issues, health IT, open data and innovation.

Prior to joining FCW, Gunter reported for the C-Ville Weekly in Charlottesville, Va., and served as a college sports beat writer for the South Boston (Va.) News and Record. He started at FCW as an editorial fellow before joining the team full-time as a reporter.

Gunter is a graduate of the University of Virginia, where his emphases were English, history and media studies.

Click here for previous articles by Gunter, or connect with him on Twitter: @WChaseGunter

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Reader comments

Mon, Mar 21, 2016 Howard

Not one SES will bite on this for the creator/issuer becomes by default Accountable/Responsible for all subsequent data model shortcomings. Nice try :)

Tue, Feb 2, 2016 Dennis Crow

I encountered "place of performance" issues in 1997 in a federal agency. One office in the agency was trying to match funding and project locations, as is the Data Act. There were three major problems: (1)rarely did anyone take into account the difference between the physical address and the mailing address, and why that mattered in the statistics. A homegrown "GIS" was used to map that asistance. For these same reasons, the funding could not be accurately mapped. In most instances, the grantee was a city, county, or state that itself distributed funds and did not necessarily keep records in this way, and (2) some funds were distributed directly to a single project, but that project received money from other agency sources that did not by law need to identified by location. Some assistance was linked to a simgle project and funds used in the same project for different purposes had area wide benefits not project specific benefits; (3) in a financial system, funding as kept track of by "activity," not funding and location specific and could have multiple "activities" at the same physical location but not identified as such. These could have been avoided if there had been a data model in the first place and provided for some kind of semantic continuity.

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