A Concept for a National Freight Data Program Special Report 276 (2003) / Chapter Skim
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D A Framework for the Development of National Freight Data: Dissenting Statement of Kenneth D. Boyer
D A Framework for the Development of National Freight Data: Dissenting Statement of Kenneth D. Boyer
Pages 100-109
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From page 100... ...
. The framework was to be conceptual in nature and not a detailed data collection plan.
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From page 101... ...
It does, however, offer an intellectually coherent recommendation for a framework for freight data development that is missing in Chapter 3. Using the framework, this appendix shows that Chapter 3 errs in several key areas, among them the following: · Failure to recommend a procedure for dealing with confidentiality issues, · Confusion on how data series like Waterborne Commerce of the United States and the 1 percent Railroad Waybill Sample should be owned and managed in relation to the new proposed data collection efforts, · Failure to clearly define the role of third-party data organizers, and · An apparent recommendation to shift resources away from the current Commodity Flow Survey (CFS)
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From page 102... ...
Realistically, a CODMRT data collection program will consist of a combination of investigations of data for specific projects along with a publication of summaries at a much coarser level of aggregation. Almost all of the entries in a CODMRT database will be zero, but such is the nature of transportation data -- one should not expect to find coal shipped to Newcastle or wheat shipped from Manhattan by any mode or route, much less by rail to Fargo, North Dakota, via I-20 through Shreveport at 3 in the afternoon.
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From page 103... ...
, and the fact that in the general case there is no individual who could fill out a survey to populate single entries in the database -- dictate the proposed framework for freight data collection. In fact, it is perhaps misleading to characterize the gathering of CODMRT data as data collection, since such data will require joint inference from records contained in more than one data set.
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From page 104... ...
Data fusion instead involves assumptions and judgment about matching records of steel shipments against records of truck movements, perhaps none of which will represent shipments of steel. As noted by Southworth (1999)
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From page 105... ...
There are several modal data sources, for example the 1 percent waybill sample collected by the Association of American Railroads and the U.S. Army Corps of Engineers' Statistics of Waterborne Commerce.
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From page 106... ...
One possible way to do this is to forbid data fusers who have access to confidential data from the BTS archive to fuse data from proprietary sources outside of the BTS archive. In this way, for example, an organization that continued to use proprietary data outside of the BTS archive would create products that were less accurate than other data sources since it would not have access to microdata in the BTS archive; organizations would then have an incentive to place their proprietary data in the BTS archive so that data fusers using the data could have access to other confidential data as well.
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From page 107... ...
The data summaries provided by data fusers should also meet the criteria for confidentiality that BTS must abide by. In order to maintain confidentiality, the Freight Data Advisory Board should publish guidelines for systematic aggregation criteria to mask activities of individual shippers.
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From page 108... ...
The Freight Data Advisory Board should also advise BTS on the desirability of starting new data collection efforts to augment the CFS and the data programs for which it acts as an archivist. One promising source of CODMRT data is roadside surveys like those conducted in Canada in which trucks are stopped randomly and the driver is asked to give information on routing, commodity, origin, and destination.
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From page 109... ...
BTS would be charged with overseeing a freight data archive composed initially of existing databases augmented with passively collected electronic transportation data. The data archive will then be queried by a separate group of third-party data fusers, whose job will be to combine data sets in the archive by using their own assumptions about the data generation process and to create reports under contract to data users.
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