Earlier today, Virginia Carlson, president of the Metro Chicago Information Center (MCIC), commented extensively upon proposed deep Congressional cuts to funding for open government data platforms. Carlson provided more context for other federal open data initiatives that may also be cut. Her thoughts are shared below as a guest post. -Editor
Recent news that data transparency initiatives at the federal level are set to be shut down are coupled with an attack on long-standing federal data initiatives that produce critical economic and demographic data.
In March 2011, H.R. 931 was introduced to make participation in the American Community Survey voluntary by removing the legal penalty for not responding to the survey. Without compulsory participation, the ACS likely would not capture the broad swath of the American populace it needs to, –such citizens in towns and rural counties– and would become inaccurate and thus irrelevant. Congress relies on ACS data to guide the distribution of $485 billion annually in federal grants to states and localities. Already cash-strapped state and local governments would be hindered in their ability to efficiently target tax dollars in public investments such as roads, schools and health clinics. Private sector investments that rely on economic and demographic profiles of people in places (real estate and media industries for example) would also suffer.
At the same time, the Census Bureau budget for Fiscal Year 2012 submitted to Congress proposes to terminate six programs for a total of $10.3 million, about 1 percent of the Census Bureau budget. Among those items on the chopping block are online and print versions of the U.S. Statistical Abstract, State and Metropolitan Area Data Book, Population Change in Central and Outlying Counties of Metropolitan Statistical Areas, and the Consolidated Federal Funds Report.
What does this apparent diminishing commitment to federal data leadership mean for our future ability to make good policy, prioritize public investments, and compete globally? One scenario is that we turn to other, perhaps less democratic and more expensive, sources: internet-generated data (social apps, web scrapes), business-gathered data (market research firms) or harnessing administrative data (from driver’s license files, Medicare records, etc.). Who then will be counted? How do we ensure privacy?