Click for next page ( 73

The National Academies of Sciences, Engineering, and Medicine
500 Fifth St. N.W. | Washington, D.C. 20001

Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement

Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 72
72 Develop and/or Use Standardized data standards, the data architecture developer should for- Terminology and Definitions for Each Data mulate recommendations for communication protocols Architecture Component Developed with organizations responsible for developing relevant data standards and include "place holders" for data standard This requirement affects both information technology cross-references in the data architecture. terms (such as architecture, data architecture, system, data- base, and framework) and freight transportation business process terms. This report includes a number of definitions Challenges and Strategies the developer of the national freight data architecture should This section outlines some of the most relevant issues take into consideration. The developer also should note the and challenges that might block the implementation of the various sources of freight-related terms and definitions that national freight data architecture, as well as some candidate will need to be reconciled, particularly in the case of defini- strategies for developing, adopting, and maintaining the data tion sources at the federal level. Examples of sources include architecture. the following: BTS's dictionary (142), Challenges and Potential Impediments CFS definitions (33), to Successful Implementation Economic Census definitions (143), Technical Challenges Glossary from the Energy Information Administration (EIA) (144), Technical challenges refer to issues (e.g., technological lim- FAF2 data dictionary (63), and itations, hardware and software incompatibilities, and stan- IANA's glossary (145). dards incompatibilities) that might impede the successful implementation of the data architecture. Examples include the following: Implement Strong Privacy Protection Strategies The national freight data architecture will be successful The national freight data architecture will need to comply only if it meets the expectations of the freight community. with (and/or provide support to) the privacy provisions of This report laid out several implementation approaches the E-Government Act of 2002 (135, 136). Requirements in for a national freight data architecture. Are the approaches this act include conducting privacy impact assessments to appropriate? Will it be necessary to identify additional document what information is to be collected, its purpose alternatives? What is the implementation horizon for and intended use, information sharing practices and security each alternative? measures, opportunities for consent, and whether a system of Data storage requirements may be enormous, even under records is created following Privacy Act provisions. Beyond a distributed, multi-agency data repository model. Will the these legal requirements, the analysis will need to take into key agencies responsible for managing the data have the consideration confidentiality and anonymity requirements in necessary technical infrastructure and resources needed connection with the participation of private-sector stake- (e.g., servers, database system(s), and other applications) holders (e.g., producers, shippers, and carriers) in data col- to undertake that task successfully? lection programs that result from the implementation of the There may be tabulation errors and redundancies if more national freight data architecture. than one stakeholder needs to enter the same data. Ideally, data should be entered only once. However, is this scenario realistic with today's technologies, processes, and resources? Establish Integration Points with Other Many motor carriers still rely on fax transmissions to move Data Architectures and Standards freight. Who will enter relevant data into a database to facil- Although the main focus of the national freight data ar- itate the collection of shipment data at the national level? Is chitecture will be freight planning (at least initially), it will it necessary for all motor carriers to be computerized? Is it need to provide support to, or ensure compatibility with, necessary to collect data about all shipments? other data architectures. The national freight data architec- Upgrading computer systems at carriers and other freight ture will also need to provide support to, or ensure compat- stakeholders to support key elements of the national freight ibility with, applicable data standards. As previously men- data architecture might take many years to implement, tioned, although the developer of the national freight data particularly if the objective is to obtain commodity flow architecture will not be responsible for developing freight data at finer levels of resolution. Financial considerations

OCR for page 72
73 aside, how feasible is it to deploy EFM and other similar Different stakeholders have different data confidentiality initiatives throughout the entire supply chain? Even if and data security concerns. Incorporating strong data secu- computer systems are upgraded, one of the challenges rity measures will be critical. However, there are technical would be how to address issues such as the common use challenges that would need to be addressed to make sure of the generic freight-all-kinds freight classification to all proper access is provided to users while complying with shipments from a shipper regardless of freight commod- strong security standards. ity or type. Measurement units for commodities are different depend- Policy Challenges ing on the stakeholder. Further, commodity code classifi- cations are different depending on the stakeholder. Is it The national freight data architecture might fail if re- possible to develop a comprehensive classification sys- quired policies, both in the public and private sectors, fail or tem that enables all crosswalks so that it could work for all are not feasible. Examples of policy challenges include the stakeholders? following: Some data are not available in a timely fashion. For exam- ple, one agency reported that waiting for year-end reports Homeland security concerns may limit the dissemination did not allow the agency to find reporting irregularities early, of certain freight data. All import and export cargo is doc- forcing the agency to collect data on a quarterly basis. Feed- umented, yet the resulting data are not shared effectively back from the private sector indicates that the private sec- among transportation planning agencies. Can interagency tor does not make business decisions based on data they agreements be implemented to ensure that authorized per- perceive to be old (e.g., CFS data). Under what circum- sonnel have access to relevant data in a timely manner, not stances is it possible to collect data more frequently than the just for hazardous materials as in the case of the HIP? current practice? Today, a number of private-sector associations, such as AAR Data quality control practices vary widely. How will differ- and ATA, collect data from, or on behalf of, their members. ent datasets be compared and integrated in a reliable way, What would be the impact of a national-level data collection even if datasets are not physically merged? effort on those initiatives? There are substantial differences in terminology, data item Anecdotal information suggests that collecting freight and definitions, and data implementations among freight data company data is more difficult in the United States than stakeholders. How feasible is it to identify integration points in other industrialized countries due to differences in soci- among disparate data systems; document the location, char- etal perceptions about the needs for, and benefits of, gov- acteristics, and limitations of those integration points; and ernment regulation. However, freight and company data develop tools and processes (e.g., data conversion tools and are widely exchanged daily (and voluntarily) by millions of survey tools) to facilitate data exchange? trading partners in the private sector. Is it possible to recon- Not all data components may be necessary or should be cile these seemingly contradictory positions in a way that considered high priority. Of course, whether a data com- enables the collection of valuable data for freight transporta- ponent is important, urgent, or relevant is relative and tion planning purposes? Is it possible to guarantee confiden- depends on many factors. For example, a planner who is tiality and anonymity for data providers? engaged in freight forecasting at the national level might not be interested in regional correlations between carrier Economic and Financial Challenges operating data and transportation infrastructure charac- teristics and conditions. However, these data components The national freight data architecture might fail if the are important to a regional planner who is developing rec- perceived costs associated with its implementation exceed ommendations for transportation improvement plans at the benefits that stakeholders would receive. Examples of the regional or state levels. economic and financial challenges include the following: Integrating data from shippers and carriers to character- ize commodity movements properly may be challenging. The cost of data collection, storage, and quality assurance Although both shippers and carriers are increasingly using will be enormous. Who will bear the cost of the imple- EDI technologies, the type of data they collect is not neces- mentation and how will the implementation be funded? sarily the same. For example, a shipper might record com- Will users need to pay to access the data? If so, under what modities and O-D locations, but not routes. Similarly, a circumstances? carrier might record routes and some generalized descrip- Benefits from the implementation of the national freight tion of the commodities being transported, but not in a way data architecture might not materialize if the relation- that facilitates integration with shipper-produced data. ship between finer levels of data disaggregation and those

OCR for page 72
74 benefits has not been clearly established. What are the re- mentation approaches for a national freight data architec- quired levels of data disaggregation for different business ture, some more ambitious and comprehensive than others. processes? Completing the exercise of comparing data architecture Access to data produced by private-sector data aggregators concepts will enable stakeholders to develop a better under- could be limited if the cost to acquire the data is prohibitive. standing of the issues, which, in turn, will facilitate the Large organizations might be able to afford the data, but development of a data architecture that meets stakeholder smaller organizations would not. What are the implications? expectations. Different stakeholders have different data confidential- Identify business process and implementation level prior- ity and data security concerns. Incorporating strong data ities and develop high-quality data architecture concepts security capabilities may be expensive, although necessary. and applications that address the needs of the highest Who will bear the cost for the implementation of those priority items first. A successful initial implementation capabilities? will increase the chances of success for future expansions of the data architecture. Stakeholder Buy-In and Consensus Identify data architecture leaders and champions. It is important to include representatives of the public sector The national freight data architecture might fail if there is (including federal, state, regional, and local levels) and no stakeholder buy-in or consensus about the potential ben- the private sector (including producers, shippers, carriers, efits that could result from implementing the data architec- and third-party logistics and brokers). ture. Examples of related issues include the following: Engage the national freight data architecture champions early, identify major progress milestones, and maintain good Stakeholders might be reluctant to participate if there is communication channels with the various stakeholders dur- no clarity as to why they should participate or what kind ing all phases of the development and implementation of the of short-term and long-term benefits stakeholders could national freight transportation data architecture. derive from participating. It will be critical to involve stake- Identify funding mechanisms for the implementation of holders early and often. the data architecture. Confidentiality clauses are often included in the contracts Develop criteria for measuring the effectiveness in the between supply chain trading partners. Participation in a implementation of the national freight data architecture. national data collection program might compromise com- Tie the implementation of the national freight data archi- petitive advantages. Is it possible to implement strong pri- tecture to the development of metrics or performance mea- vacy and confidentiality elements in the data architecture sures that could benefit the entire freight transportation to satisfy the requirements of all the parties involved? Opposition could surface if there is a perception that data community. Participation is likely to increase if the value collected as part of a national freight data collection pro- proposition to stakeholders makes it clear how the data col- gram could be used to validate projects of national signifi- lected can help those stakeholders realize improvements in cance at the expense of small or rural communities. productivity (e.g., if the data collection program enables the Small carriers (e.g., independent owner-operators) might identification of potential chokepoints in the supply chain). Accelerate the implementation of programs such as EFM not have the ability to provide data about loads they move. If the number of stakeholder participants is too low, the re- and the freight performance measurement program. These sulting data might not be representative. It is important to programs are laying out the foundation for the collection of ensure a minimum sample size to guarantee data reliability. freight data at levels of disaggregation not possible before. Not all data standards may be adequate to support key Identify data needs at the finest disaggregation level and elements of the national freight data architecture. What implement data collection and data storage plans at that will be the challenges to obtain stakeholder support to level. This strategy will help stakeholders eliminate redun- upgrade those standards or to develop new standards that dancy in data collection. might be necessary? Develop brochures, presentations, and other materials that explain the national freight data architecture, its scope, high-level components, and what it expects to accomplish. Strategies for Successful Implementation It will also be critical to deliver effective messages on how Strategies to ensure the successful implementation of the the national freight data architecture will assist stakehold- national freight data architecture include the following: ers in the identification of strategies to address various freight-related issues ranging from data collection to analy- Develop and compare candidate data architecture concepts. sis and reporting. Just as importantly, it will be critical to As previously mentioned, there are several possible imple- deliver messages that provide clear, concise answers to the

OCR for page 72
75 various challenges highlighted in the previous section. As also affect the private sector, by contacting the right person previously mentioned, there is confusion in the freight at a sufficiently high administrative level for discussions transportation community about what the national freight about data access and sharing). A requirement for these data architecture initiative is. Presenting a clear message to partnerships is to ensure no competitive disruptions as a the community will increase the chances of success. result of participation. Articulate benefits of participation by the private sector Take into consideration lessons learned from the imple- and identify opportunities for publicprivate partnerships mentation and maintenance of existing freight-related sys- to make data accessible for transportation planning pur- tems and architectures. Chapter 2 included a detailed re- poses in a cost-effective manner. Obtaining data from the view of a sample of those systems, which included topics private sector frequently has been challenging, which high- such as purpose, content, institutional arrangements; chal- lights the need to identify creative strategies to address this lenges and issues faced; strategies and methods for dealing issue (e.g., by highlighting that existing freight data issues with data integration issues; and adaptability.